Sophia Y. Wang, MD, MS
Assistant Professor of Ophthalmology
Bio
Dr Wang is a trained glaucoma and cataract surgeon and clinician scientist performing research in artificial intelligence in ophthalmology.
Dr Wang graduated magna cum laude from Harvard University with a degree in Biochemical Sciences. She went on to spend a year in Japan on a Fulbright Scholarship. She then attended medical school at the University of California, San Francisco, during which she also completed a research year in ophthalmology and a yearlong Advanced Training in Clinical Research Certificate Program offered by the UCSF Department of Epidemiology and Biostatistics. After a PGY-1 intern year at Kaiser Permanente Northern California Oakland, she went on to complete ophthalmology residency training at the University of Michigan Kellogg Eye Center. She pursued additional training in glaucoma through a fellowship at the Stanford Byers Eye Institute, after which she continued on as faculty in the Department of Ophthalmology.
Dr Wang specializes in the medical and surgical treatment of all different forms of glaucoma, as well as cataract surgery. Her research interests lie in "big data" for ophthalmology. Her research to develop artificial intelligence algorithms to predict glaucoma patients' outcomes using natural language processing for electronic health records data is supported by a Research to Prevent Blindness Career Development Award and a K23 Career Development Award from the National Eye Institute.
Clinical Focus
- Glaucoma
- Cataract Extraction
- Glaucoma Specialist
Academic Appointments
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Assistant Professor - University Medical Line, Ophthalmology
Honors & Awards
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Young Clinician Scientist Award, American Glaucoma Society (2023)
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McCormick-Gabilan Fellowship, Stanford (2021)
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Career Development Award, Research to Prevent Blindness (2020)
Professional Education
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Fellowship: Stanford Health Care Byers Eye Institute CA
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Residency: University of Michigan Dept of Ophthalmology (2017) MI
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MS, Stanford University, Biomedical Informatics (2021)
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Internship: Kaiser Permanente Oakland Internal Medicine Residency (2014) CA
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Board Certification: American Board of Ophthalmology, Ophthalmology (2018)
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Medical Education: University of California at San Francisco School of Medicine (2013) CA
Research Interests
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Data Sciences
Current Research and Scholarly Interests
My interests lie in “big data”, informatics, and artificial intelligence for ophthalmology research. I started my career in data science acquiring the tools of basic epidemiology and public health research during my Fulbright year studying diet and metabolic syndrome in Japan. Then during medical school, I was awarded a fellowship through the NIH-funded Clinical and Translational Sciences Institute at UCSF to spend an extra year pursuing glaucoma research while enrolled in the Advanced Training in Clinical Research program offered by UCSF’s epidemiology and biostatistics department. I worked through a curriculum identical to the first year of the Master’s Degree program in clinical research and analyzed data from the National Health and Nutrition Examination Survey (NHANES) to explore associations with glaucoma as diverse as depression and vitamin and nutrient intake. Moving to the University of Michigan Kellogg Eye Center for ophthalmology residency gave me further opportunities to branch into health services and health equity research, and to grapple with the nuances of longitudinal and “messy” real world data of health insurance claims and electronic health records (EHR) data.
In June 2019, I completed a glaucoma fellowship at Stanford University at the Byers Eye Institute and continued to stay on as faculty in the Department of Ophthalmology. Rather than the traditional one-year full-time clinical fellowship, I crafted a two-year fellowship experience combining clinical training with continued research efforts. The fertile interdisciplinary environment of Stanford University allows me to work on newest frontiers in data science by working with scientists in biomedical data science and health informatics. I completed a Master's Degree in Biomedical Informatics, which has given me the tools and skills I need as a clinician scientist at the interface of informatics and ophthalmology. I continue to expand my work in EHR data analysis, incorporating natural language processing and machine learning techniques to unlock insights from clinical and unstructured data in order to impact people’s health, health literacy, health attitudes, and health behaviors.
Currently, my work focuses on using and integrating a wide variety of data sources in my research, spanning both structured and unstructured forms, including national survey datasets, health insurance claims data, patient-generated online text, surgical video, and electronic health records. I investigate outcomes of treatments for glaucoma and cataract, as well as other areas of ophthalmology. My focus is on developing artificial intelligence methods to predict ophthalmology outcomes, and on applying novel methods for automated extraction of ophthalmic data, especially from free text and video. I am also building artificial intelligence tools to improve cataract surgical education (PhacoTrainer). I have an ongoing interest in health disparities and health equity, and am working to ensure that algorithms we develop for ophthalmology are fair.
For more information on our current projects, including recent papers and presentations, feel free to browse our research group website: https://optima.sites.stanford.edu/
All Publications
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The Impact of Race, Ethnicity, and Sex on Fairness in Artificial Intelligence for Glaucoma Prediction Models.
Ophthalmology science
2025; 5 (1): 100596
Abstract
Despite advances in artificial intelligence (AI) in glaucoma prediction, most works lack multicenter focus and do not consider fairness concerning sex, race, or ethnicity. This study aims to examine the impact of these sensitive attributes on developing fair AI models that predict glaucoma progression to necessitating incisional glaucoma surgery.Database study.Thirty-nine thousand ninety patients with glaucoma, as identified by International Classification of Disease codes from 7 academic eye centers participating in the Sight OUtcomes Research Collaborative.We developed XGBoost models using 3 approaches: (1) excluding sensitive attributes as input features, (2) including them explicitly as input features, and (3) training separate models for each group. Model input features included demographic details, diagnosis codes, medications, and clinical information (intraocular pressure, visual acuity, etc.), from electronic health records. The models were trained on patients from 5 sites (N = 27 999) and evaluated on a held-out internal test set (N = 3499) and 2 external test sets consisting of N = 1550 and N = 2542 patients.Area under the receiver operating characteristic curve (AUROC) and equalized odds on the test set and external sites.Six thousand six hundred eighty-two (17.1%) of 39 090 patients underwent glaucoma surgery with a mean age of 70.1 (standard deviation 14.6) years, 54.5% female, 62.3% White, 22.1% Black, and 4.7% Latinx/Hispanic. We found that not including the sensitive attributes led to better classification performance (AUROC: 0.77-0.82) but worsened fairness when evaluated on the internal test set. However, on external test sites, the opposite was true: including sensitive attributes resulted in better classification performance (AUROC: external #1 - [0.73-0.81], external #2 - [0.67-0.70]), but varying degrees of fairness for sex and race as measured by equalized odds.Artificial intelligence models predicting whether patients with glaucoma progress to surgery demonstrated bias with respect to sex, race, and ethnicity. The effect of sensitive attribute inclusion and exclusion on fairness and performance varied based on internal versus external test sets. Prior to deployment, AI models should be evaluated for fairness on the target population.Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
View details for DOI 10.1016/j.xops.2024.100596
View details for PubMedID 39386055
View details for PubMedCentralID PMC11462200
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The Impact of Race, Ethnicity, and Sex on Fairness in Artificial Intelligence for Glaucoma Prediction Models
OPHTHALMOLOGY SCIENCE
2025; 5 (1)
View details for DOI 10.1016/j.xops.2024.100596
View details for Web of Science ID 001325289200001
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Association of obesity and metabolic syndrome with incident primary open angle glaucoma in the UK Biobank.
Clinical & experimental ophthalmology
2024
Abstract
We sought to investigate the association between obesity, metabolic syndrome, and metabolic health with incident primary open-angle glaucoma (POAG).We included 103 249 UK Biobank participants without previously diagnosed glaucoma or glaucoma-related procedures at enrolment. The primary outcome was POAG identified from diagnostic coding via linked hospital inpatient and primary care data. We used multivariable Cox regression to evaluate the association of body mass index (BMI), and the interaction with metabolic syndrome (MetS) and a novel definition of metabolic health status with incident POAG. BMI was modelled as a time-varying coefficient. Multivariable analysis was adjusted for age, sex, ethnicity, intraocular pressure, spherical equivalent, polygenic risk score and stratified by the presence of primary care data.There were 647 events of incident POAG over 464 117 580 person-years and a mean follow-up of 12.6 years. At baseline (time = 0), each one unit increase in BMI was associated with a 9% lower hazard of incident glaucoma (HR 0.91, CI 0.86-0.97, p = 0.0066). Further, compared to a normal BMI range of 18.5-24 kg/m2, a BMI ≥30 kg/m2 was associated with a 65% relative hazard reduction (HR 0.35, CI 0.16-0.80, p = 0.012). There was no significant interaction between BMI and metabolic syndrome or metabolic health (all p > 0.05).The effect of BMI on the risk of incident POAG varied with time. Higher BMI was associated with a decreased risk of incident POAG in this large prospective cohort. There was no significant association with systemic metabolic health.
View details for DOI 10.1111/ceo.14467
View details for PubMedID 39557423
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Incidence of Uveitis Following Initiation of Prostaglandin Analogs Versus Other Glaucoma Medications: A Study from the SOURCE Repository.
Ophthalmology. Glaucoma
2024
Abstract
PURPOSE: To evaluate the risk of incidence rates of uveitis among patients starting topical glaucoma therapy.DESIGN: Retrospective database study utilizing the Sight Outcomes Research Collaborative (SOURCE) Ophthalmology Data Repository.PARTICIPANTS: Adult glaucoma patients who were recently started on topical glaucoma therapy.METHODS: Using data from 10 health systems contributing data to the SOURCE data repository, we identified all adult glaucoma patients who had been newly started on a topical glaucoma medication (prostaglandin analogues (PGAs), beta-blockers (BBs), alpha agonists (AAs), and carbonic anhydrase inhibitors (CAIs)). Patients with pre-existing documentation of uveitis were excluded.MAIN OUTCOME MEASURES: Incidence of uveitis within 3 months of initiating therapy with different topical glaucoma medications.RESULTS: We included 67,517 patients who were newly prescribed a topical glaucoma medication. The mean age of the patients was 67.3±13.2 years and 59% were females. A total of 567 patients (0.87%) developed uveitis within 3 months of initiating the therapy. The incidence of uveitis was 0.32%, 1.95%, 1.63%, and 1.68% for users of PGAs, BBs, AAs, and CAIs, respectively. After adjusting for sociodemographic factors, individuals using topical BBs, AAs, and CAIs had significantly higher odds of developing uveitis versus those using PGAs (P<0.001 for all comparisons).CONCLUSIONS: The use of PGAs was not associated with higher odds of developing uveitis compared to other classes of topical glaucoma medications.
View details for DOI 10.1016/j.ogla.2024.10.010
View details for PubMedID 39542214
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Big data and electronic health records for glaucoma research.
Taiwan journal of ophthalmology
2024; 14 (3): 352-359
Abstract
The digitization of health records through electronic health records (EHRs) has transformed the landscape of ophthalmic research, particularly in the study of glaucoma. EHRs offer a wealth of structured and unstructured data, allowing for comprehensive analyses of patient characteristics, treatment histories, and outcomes. This review comprehensively discusses different EHR data sources, their strengths, limitations, and applicability towards glaucoma research. Institutional EHR repositories provide detailed multimodal clinical data, enabling in-depth investigations into conditions such as glaucoma and facilitating the development of artificial intelligence applications. Multicenter initiatives such as the Sight Outcomes Research Collaborative and the Intelligent Research In Sight registry offer larger, more diverse datasets, enhancing the generalizability of findings and supporting large-scale studies on glaucoma epidemiology, treatment outcomes, and practice patterns. The All of Us Research Program, with a special emphasis on diversity and inclusivity, presents a unique opportunity for glaucoma research by including underrepresented populations and offering comprehensive health data even beyond the EHR. Challenges persist, such as data access restrictions and standardization issues, but may be addressed through continued collaborative efforts between researchers, institutions, and regulatory bodies. Standardized data formats and improved data linkage methods, especially for ophthalmic imaging and testing, would further enhance the utility of EHR datasets for ophthalmic research, ultimately advancing our understanding and treatment of glaucoma and other ocular diseases on a global scale.
View details for DOI 10.4103/tjo.TJO-D-24-00055
View details for PubMedID 39430348
View details for PubMedCentralID PMC11488813
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Beyond PhacoTrainer: Deep Learning for Enhanced Trabecular Meshwork Detection in MIGS Videos.
Translational vision science & technology
2024; 13 (9): 5
Abstract
The purpose of this study was to develop deep learning models for surgical video analysis, capable of identifying minimally invasive glaucoma surgery (MIGS) and locating the trabecular meshwork (TM).For classification of surgical steps, we had 313 video files (265 for cataract surgery and 48 for MIGS procedures), and for TM segmentation, we had 1743 frames (1110 for TM and 633 for no TM). We used transfer learning to update a classification model pretrained to recognize standard cataract surgical steps, enabling it to also identify MIGS procedures. For TM localization, we developed three different models: U-Net, Y-Net, and Cascaded. Segmentation accuracy for TM was measured by calculating the average pixel error between the predicted and ground truth TM locations.Using transfer learning, we developed a model which achieved 87% accuracy for MIGS frame classification, with area under the receiver operating characteristic curve (AUROC) of 0.99. This model maintained a 79% accuracy for identifying 14 standard cataract surgery steps. The overall micro-averaged AUROC was 0.98. The U-Net model excelled in TM segmentation with an Intersection over union (IoU) score of 0.9988 and an average pixel error of 1.47.Building on prior work developing computer vision models for cataract surgical video, we developed models that recognize MIGS procedures and precisely localize the TM with superior performance. Our work demonstrates the potential of transfer learning for extending our computer vision models to new surgeries without the need for extensive additional data collection.Computer vision models in surgical videos can underpin the development of systems offering automated feedback for trainees, improving surgical training and patient care.
View details for DOI 10.1167/tvst.13.9.5
View details for PubMedID 39226062
View details for PubMedCentralID PMC11373722
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Gap Analysis of Glaucoma Examination Concept Representations within Standard SNOMED Clinical Terms.
Ophthalmology. Glaucoma
2024
Abstract
Standardization of eye care data is important for clinical interoperability and research . We aimed to address gaps in the representations of glaucoma examination concepts within Systemized Nomenclature of Medicine - Clinical Terms (SNOMED-CT), the preferred terminology of the American Academy of Ophthalmology.Study of data elements.Structured eye exam data fields from two electronic health records (EHR) systems (Epic Systems and Medisoft) were compared against existing SNOMED-CT codes for concepts representing glaucoma examination findings3. Glaucoma specialists from multiple institutions were surveyed to identify high-priority gaps in representation, which were discussed among the SNOMED International Eye Care Clinical Reference Group. Proposals for new codes to address the gaps were formulated and submitted for inclusion in SNOMED-CT.Gaps in SNOMED-CT glaucoma examination concept representations RESULTS: We identified several gaps in SNOMED-CT regarding glaucoma examination concepts. A survey of glaucoma specialists identified high-priority data elements within the categories of tonometry and gonioscopy. For tonometry, there was consensus that we need to define new codes related to maximum intraocular pressure (IOP) and target IOP, and to delineate all methods of measuring IOP. These new codes were proposed and successfully added to SNOMED-CT for future use. Regarding gonioscopy, the current terminology did not include the ability to denote the gonioscopic grading system used (e.g., Shaffer or Spaeth), degree of angle pigmentation, iris configuration (except for plateau iris), and iris approach. There was also no ability to specify eye laterality or angle quadrant for gonioscopic findings. We proposed a framework for representing gonioscopic findings as observable entities in SNOMED-CT.There are existing gaps in the standardized representation of findings related to tonometry and gonioscopy within SNOMED-CT. These are important areas for evaluating clinical outcomes and enabling secondary use of EHR data for glaucoma research. This international, multi-institutional collaborative process enabled identification of gaps, prioritization, and development of data standards to address these gaps.Addressing these gaps and augmenting SNOMED-CT coverage of glaucoma examination findings could enhance clinical documentation and future research efforts related to glaucoma.
View details for DOI 10.1016/j.ogla.2024.08.001
View details for PubMedID 39147325
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Automated Recognition of Visual Acuity Measurements in Ophthalmology Clinical Notes Using Deep Learning.
Ophthalmology science
2024; 4 (2): 100371
Abstract
Visual acuity (VA) is a critical component of the eye examination but is often only documented in electronic health records (EHRs) as unstructured free-text notes, making it challenging to use in research. This study aimed to improve on existing rule-based algorithms by developing and evaluating deep learning models to perform named entity recognition of different types of VA measurements and their lateralities from free-text ophthalmology notes: VA for each of the right and left eyes, with and without glasses correction, and with and without pinhole.Cross-sectional study.A total of 319 756 clinical notes with documented VA measurements from approximately 90 000 patients were included.The notes were split into train, validation, and test sets. Bidirectional Encoder Representations from Transformers (BERT) models were fine-tuned to identify VA measurements from the progress notes and included BERT models pretrained on biomedical literature (BioBERT), critical care EHR notes (ClinicalBERT), both (BlueBERT), and a lighter version of BERT with 40% fewer parameters (DistilBERT). A baseline rule-based algorithm was created to recognize the same VA entities to compare against BERT models.Model performance was evaluated on a held-out test set using microaveraged precision, recall, and F1 score for all entities.On the human-annotated subset, BlueBERT achieved the best microaveraged F1 score (F1 = 0.92), followed by ClinicalBERT (F1 = 0.91), DistilBERT (F1 = 0.90), BioBERT (F1 = 0.84), and the baseline model (F1 = 0.83). Common errors included labeling VA in sections outside of the examination portion of the note, difficulties labeling current VA alongside a series of past VAs, and missing nonnumeric VAs.This study demonstrates that deep learning models are capable of identifying VA measurements from free-text ophthalmology notes with high precision and recall, achieving significant performance improvements over a rule-based algorithm. The ability to recognize VA from free-text notes would enable a more detailed characterization of ophthalmology patient cohorts and enhance the development of models to predict ophthalmology outcomes.Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
View details for DOI 10.1016/j.xops.2023.100371
View details for PubMedID 37868799
View details for PubMedCentralID PMC10587603
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Big data and electronic health records for glaucoma research
TAIWAN JOURNAL OF OPHTHALMOLOGY
2024; 14 (3): 352-359
View details for DOI 10.4103/tjo.TJO-D-24-00055
View details for Web of Science ID 001316677100007
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Multi-institutional analysis of barriers to extracting and harmonizing glaucoma testing and imaging data
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2024
View details for Web of Science ID 001312354900038
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Predicting Glaucoma Surgical Outcomes Using Neural Networks and Machine Learning on Electronic Health Records.
Translational vision science & technology
2024; 13 (6): 15
Abstract
To develop machine learning (ML) and deep learning (DL) models to predict glaucoma surgical outcomes, including postoperative intraocular pressure, use of ocular antihypertensive medications, and need for repeat surgery.We identified glaucoma surgeries performed at Stanford from 2013-2024, with two or more postoperative visits with intraocular pressure (IOP) measurement. Patient features were identified from the electronic health record (EHR), including demographics, prior diagnosis and procedure codes, medications and eye exam findings. Classical ML and DL models were developed to predict which glaucoma surgeries would result in surgical failure, defined as (1) IOP not reduced by more than 20% of preoperative baseline on two consecutive postoperative visits, (2) increased classes of glaucoma medications, and (3) need for additional glaucoma surgery or revision of original surgery.A total of 2398 glaucoma surgeries of 1571 patients were included, of which 1677 surgeries met failure criteria. Random forest performed best for prediction of overall surgical failure, with accuracy of 75.5% and area under the receiver operator curve (AUROC) of 76.7%, similar to the deep learning model (accuracy 75.5%, AUROC 76.6%). Across all models, prediction performance was better for IOP outcomes (AUROC 86%) than need for an additional surgery (AUROC 76%) or need for additional glaucoma medication (AUC 70%).ML and DL algorithms can predict glaucoma surgery outcomes using structured data inputs from EHRs.Models that predict outcomes of glaucoma surgery may one day provide the basis for clinical decision support tools supporting surgeons in personalizing glaucoma treatment plans.
View details for DOI 10.1167/tvst.13.6.15
View details for PubMedID 38904612
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Prediction Models for Glaucoma in a Multicenter Electronic Health Records Consortium: The Sight Outcomes Research Collaborative.
Ophthalmology science
2024; 4 (3): 100445
Abstract
Purpose: Advances in artificial intelligence have enabled the development of predictive models for glaucoma. However, most work is single-center and uncertainty exists regarding the generalizability of such models. The purpose of this study was to build and evaluate machine learning (ML) approaches to predict glaucoma progression requiring surgery using data from a large multicenter consortium of electronic health records (EHR).Design: Cohort study.Participants: Thirty-six thousand five hundred forty-eight patients with glaucoma, as identified by International Classification of Diseases (ICD) codes from 6 academic eye centers participating in the Sight OUtcomes Research Collaborative (SOURCE).Methods: We developed ML models to predict whether patients with glaucoma would progress to glaucoma surgery in the coming year (identified by Current Procedural Terminology codes) using the following modeling approaches: (1) penalized logistic regression (lasso, ridge, and elastic net); (2) tree-based models (random forest, gradient boosted machines, and XGBoost), and (3) deep learning models. Model input features included demographics, diagnosis codes, medications, and clinical information (intraocular pressure, visual acuity, refractive status, and central corneal thickness) available from structured EHR data. One site was reserved as an "external site" test set (N=1550); of the patients from the remaining sites, 10% each were randomly selected to be in development and test sets, with the remaining 27999 reserved for model training.Main Outcome Measures: Evaluation metrics included area under the receiver operating characteristic curve (AUROC) on the test set and the external site.Results: Six thousand nineteen (16.5%) of 36548 patients underwent glaucoma surgery. Overall, the AUROC ranged from 0.735 to 0.771 on the random test set and from 0.706 to 0.754 on the external test site, with the XGBoost and random forest model performing best, respectively. There was greatest performance decrease from the random test set to the external test site for the penalized regression models.Conclusions: Machine learning models developed using structured EHR data can reasonably predict whether glaucoma patients will need surgery, with reasonable generalizability to an external site. Additional research is needed to investigate the impact of protected class characteristics such as race or gender on model performance and fairness.Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
View details for DOI 10.1016/j.xops.2023.100445
View details for PubMedID 38317869
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Limitations of Assessing Barriers in Diabetic Retinopathy Screening-Reply.
JAMA ophthalmology
2024
View details for DOI 10.1001/jamaophthalmol.2024.0320
View details for PubMedID 38512268
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Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.
American journal of ophthalmology
2024
Abstract
Nearly all published ophthalmology-related Big Data studies rely exclusively upon International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or non-specific codes may be used. We assessed whether natural language processing (NLP), as an alternative approach, could more accurately identify lens pathology.Database study comparing the accuracy of NLP versus ICD billing codes to properly identify lens pathology.We developed an NLP algorithm capable of searching free-text lens exam data in the electronic health record (EHR) to identify type(s) of cataract present, cataract density, presence of intraocular lenses, and other lens pathology. We applied our algorithm to 17.5 million lens exam records in the Sight Outcomes Research Collaborative (SOURCE) repository. We selected 4314 unique lens-exam entries and asked 11 clinicians to assess whether all pathology present in the entries had been correctly identified in the NLP algorithm output. The algorithm's sensitivity at accurately identifying lens pathology was compared with that of the ICD codes.The NLP algorithm correctly identified all lens pathology present in 4104 of the 4314 lens-exam entries (95.1%). For less common lens pathology, algorithm findings were corroborated by reviewing clinicians for 100% of mentions of pseudoexfoliation material and 99.7% for phimosis, subluxation, and synechia. Sensitivity at identifying lens pathology was much better for NLP (0.98 (0.96-0.99) than for billing codes (0.49 (0.46-0.53)).Our NLP algorithm identifies and classifies lens abnormalities routinely documented by eye-care professionals with high accuracy. Such algorithms will help researchers to properly identify and classify ocular pathology, broadening the scope of feasible research using real-world data.
View details for DOI 10.1016/j.ajo.2024.01.030
View details for PubMedID 38296152
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Predicting Glaucoma Progression to Surgery with Artificial Intelligence Survival Models.
Ophthalmology science
2023; 3 (4): 100336
Abstract
Purpose: Prior artificial intelligence (AI) models for predicting glaucoma progression have used traditional classifiers that do not consider the longitudinal nature of patients' follow-up. In this study, we developed survival-based AI models for predicting glaucoma patients' progression to surgery, comparing performance of regression-, tree-, and deep learning-based approaches.Design: Retrospective observational study.Subjects: Patients with glaucoma seen at a single academic center from 2008 to 2020 identified from electronic health records (EHRs).Methods: From the EHRs, we identified 361 baseline features, including demographics, eye examinations, diagnoses, and medications. We trained AI survival models to predict patients' progression to glaucoma surgery using the following: (1) a penalized Cox proportional hazards (CPH) model with principal component analysis (PCA); (2) random survival forests (RSFs); (3) gradient-boosting survival (GBS); and (4) a deep learning model (DeepSurv). The concordance index (C-index) and mean cumulative/dynamic area under the curve (mean AUC) were used to evaluate model performance on a held-out test set. Explainability was investigated using Shapley values for feature importance and visualization of model-predicted cumulative hazard curves for patients with different treatment trajectories.Main Outcome Measures: Progression to glaucoma surgery.Results: Of the 4512 patients with glaucoma, 748 underwent glaucoma surgery, with a median follow-up of 1038 days. The DeepSurv model performed best overall (C-index, 0.775; mean AUC, 0.802) among the models studied in this article (CPH with PCA: C-index, 0.745; mean AUC, 0.780; RSF: C-index, 0.766; mean AUC, 0.804; GBS: C-index, 0.764; mean AUC, 0.791). Predicted cumulative hazard curves demonstrate how models could distinguish between patient who underwent early surgery and patients who underwent surgery after > 3000 days of follow-up or no surgery.Conclusions: Artificial intelligence survival models can predict progression to glaucoma surgery using structured data from EHRs. Tree-based and deep learning-based models performed better at predicting glaucoma progression to surgery than the CPH regression model, potentially because of their better suitability for high-dimensional data sets. Future work predicting ophthalmic outcomes should consider using tree-based and deep learning-based survival AI models. Additional research is needed to develop and evaluate more sophisticated deep learning survival models that can incorporate clinical notes or imaging.Financial Disclosures: Proprietary or commercial disclosure may be found after the references.
View details for DOI 10.1016/j.xops.2023.100336
View details for PubMedID 37415920
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Social Determinants of Health and Perceived Barriers to Care in Diabetic Retinopathy Screening.
JAMA ophthalmology
2023
Abstract
Regular screening for diabetic retinopathy often is crucial for the health of patients with diabetes. However, many factors may be barriers to regular screening and associated with disparities in screening rates.To evaluate the associations between visiting an eye care practitioner for diabetic retinopathy screening and factors related to overall health and social determinants of health, including socioeconomic status and health care access and utilization.This retrospective cross-sectional study included adults aged 18 years or older with type 2 diabetes who answered survey questions in the All of Us Research Program, a national multicenter cohort of patients contributing electronic health records and survey data, who were enrolled from May 1, 2018, to July 1, 2022.The associations between visiting an eye care practitioner and (1) demographic and socioeconomic factors and (2) responses to the Health Care Access and Utilization, Social Determinants of Health, and Overall Health surveys were investigated using univariable and multivariable logistic regressions.The primary outcome was whether patients self-reported visiting an eye care practitioner in the past 12 months. The associations between visiting an eye care practitioner and demographic and socioeconomic factors and responses to the Health Care Access and Utilization, Social Determinants of Health, and Overall Health surveys in All of Us were investigated using univariable and multivariable logistic regression.Of the 11 551 included participants (54.55% cisgender women; mean [SD] age, 64.71 [11.82] years), 7983 (69.11%) self-reported visiting an eye care practitioner in the past year. Individuals who thought practitioner concordance was somewhat or very important were less likely to have seen an eye care practitioner (somewhat important: adjusted odds ratio [AOR], 0.83 [95% CI, 0.74-0.93]; very important: AOR, 0.85 [95% CI, 0.76-0.95]). Compared with financially stable participants, individuals with food or housing insecurity were less likely to visit an eye care practitioner (food insecurity: AOR, 0.75 [95% CI, 0.61-0.91]; housing insecurity: AOR, 0.86 [95% CI, 0.75-0.98]). Individuals who reported fair mental health were less likely to visit an eye care practitioner than were those who reported good mental health (AOR, 0.84; 95% CI, 0.74-0.96).This study found that food insecurity, housing insecurity, mental health concerns, and the perceived importance of practitioner concordance were associated with a lower likelihood of receiving eye care. Such findings highlight the self-reported barriers to seeking care and the importance of taking steps to promote health equity.
View details for DOI 10.1001/jamaophthalmol.2023.5287
View details for PubMedID 37971726
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Impact of Type 2 diabetes mellitus and insulin use on progression to glaucoma surgery in primary open angle glaucoma.
Eye (London, England)
2023
Abstract
PURPOSE: To investigate outcomes of primary open-angle glaucoma (POAG) patients with and without type 2 diabetes mellitus (T2DM).METHODS: Retrospective observational study using U.S. nationwide healthcare insurance claims database. Patients ≥40 years old with at least one HbA1c within one year of POAG diagnosis were included. Diabetic factors associated with POAG progression requiring glaucoma surgery were evaluated using multivariable Cox proportional hazards regression models adjusted for demographic, diabetic and glaucoma factors. T2DM diagnosis and use of either oral hypoglycaemic agents or insulin therapy were assessed in association with POAG progression requiring glaucoma surgery.RESULTS: 104,515 POAG patients were included, of which 70,315 (67%) had T2DM. The mean age was 68.9 years (Standard deviation 9.2) and 55% were female. Of those with T2DM, 93% were taking medication (65,468); 95% (62,412) taking oral hypoglycaemic agents, and 34% (22,028) were on insulin. In multivariable analyses, patients with T2DM had a higher hazard of requiring glaucoma surgery (Hazard ratio, HR 1.15, 95% CI 1.09-1.21, p<0.001). Higher mean HbA1c was also a significant predictor of progression requiring glaucoma surgery (HR 1.02, 95% CI 1.01-1.03, p<0.001). When evaluating only patients who were taking antidiabetic medication, after adjusting for confounders, insulin use was associated with a 1.20 higher hazard of requiring glaucoma surgery compared to oral hypoglycaemic agents (95% CI 1.14-1.27, p<0.001), but when stratified by HbA1c, this effect was only significant for those with HbA1c>7.5%.CONCLUSIONS: Higher baseline HbA1c, particularly in patients taking insulin may be associated with higher rates of glaucoma surgery in POAG.
View details for DOI 10.1038/s41433-023-02734-2
View details for PubMedID 37740048
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The Association Between Frailty and Visual Field Loss in U.S. Adults.
American journal of ophthalmology
2023
Abstract
To describe the association between visual field loss and frailty in a nationally representative cohort of U.S. adults.Retrospective cross-sectional study.The cohort included adults 40 years or older with complete eye examination data from the 2005-2006 and 2007-2008 National Health and Nutrition Examination Surveys (NHANES). Visual field loss (VFL) was determined by frequency doubling technology and a 2-2-1 algorithm. A 36-item deficit accumulation-based frailty index was used to divide subjects into 4 categories of increasing frailty severity.Of the 4,897 participants, 4,402 (93.2%) participants had no VFL, 301 (4.1%) had unilateral VFL, and 194 (2.73%) had bilateral VFL. Within the sample, 2,197 (53.1%) subjects were categorized as non-frail, 1,659 (31.3%) as vulnerable, 732 (11.3%) as mildly frail, and 312 (4.3%) as most frail. In multivariable models adjusted for demographics, visual acuity, and history of cataract surgery, subjects with unilateral VFL had higher adjusted odds of being in a more frail category (adjusted odds ratio [aOR], 2.07; 95% CI, 1.42-3.02) than subjects without VFL. Subjects with bilateral VFL also had higher odds of a more frail category compared to subjects without VFL (aOR, 1.74; 95% CI, 1.20-2.52).In the 2005-2008 NHANES adult population, VFL is associated with higher odds of frailty, independent of central visual acuity loss. Frail individuals may be more susceptible to diseases which can cause VFL and/or VFL may predispose to frailty. Additional studies are needed to determine the directionality of this relationship and to assess potential interventions.
View details for DOI 10.1016/j.ajo.2023.09.008
View details for PubMedID 37714282
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Comparison of Ophthalmologist and Large Language Model Chatbot Responses to Online Patient Eye Care Questions.
JAMA network open
2023; 6 (8): e2330320
Abstract
Importance: Large language models (LLMs) like ChatGPT appear capable of performing a variety of tasks, including answering patient eye care questions, but have not yet been evaluated in direct comparison with ophthalmologists. It remains unclear whether LLM-generated advice is accurate, appropriate, and safe for eye patients.Objective: To evaluate the quality of ophthalmology advice generated by an LLM chatbot in comparison with ophthalmologist-written advice.Design, Setting, and Participants: This cross-sectional study used deidentified data from an online medical forum, in which patient questions received responses written by American Academy of Ophthalmology (AAO)-affiliated ophthalmologists. A masked panel of 8 board-certified ophthalmologists were asked to distinguish between answers generated by the ChatGPT chatbot and human answers. Posts were dated between 2007 and 2016; data were accessed January 2023 and analysis was performed between March and May 2023.Main Outcomes and Measures: Identification of chatbot and human answers on a 4-point scale (likely or definitely artificial intelligence [AI] vs likely or definitely human) and evaluation of responses for presence of incorrect information, alignment with perceived consensus in the medical community, likelihood to cause harm, and extent of harm.Results: A total of 200 pairs of user questions and answers by AAO-affiliated ophthalmologists were evaluated. The mean (SD) accuracy for distinguishing between AI and human responses was 61.3% (9.7%). Of 800 evaluations of chatbot-written answers, 168 answers (21.0%) were marked as human-written, while 517 of 800 human-written answers (64.6%) were marked as AI-written. Compared with human answers, chatbot answers were more frequently rated as probably or definitely written by AI (prevalence ratio [PR], 1.72; 95% CI, 1.52-1.93). The likelihood of chatbot answers containing incorrect or inappropriate material was comparable with human answers (PR, 0.92; 95% CI, 0.77-1.10), and did not differ from human answers in terms of likelihood of harm (PR, 0.84; 95% CI, 0.67-1.07) nor extent of harm (PR, 0.99; 95% CI, 0.80-1.22).Conclusions and Relevance: In this cross-sectional study of human-written and AI-generated responses to 200 eye care questions from an online advice forum, a chatbot appeared capable of responding to long user-written eye health posts and largely generated appropriate responses that did not differ significantly from ophthalmologist-written responses in terms of incorrect information, likelihood of harm, extent of harm, or deviation from ophthalmologist community standards. Additional research is needed to assess patient attitudes toward LLM-augmented ophthalmologists vs fully autonomous AI content generation, to evaluate clarity and acceptability of LLM-generated answers from the patient perspective, to test the performance of LLMs in a greater variety of clinical contexts, and to determine an optimal manner of utilizing LLMs that is ethical and minimizes harm.
View details for DOI 10.1001/jamanetworkopen.2023.30320
View details for PubMedID 37606922
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Real-world agreement of same-visit Tono-Pen vs Goldmann applanation intraocular pressure measurements using electronic health records.
Heliyon
2023; 9 (8): e18703
Abstract
Purpose: To compare intraocular pressure (IOP) obtained with Tono-Pen (TP) and Goldmann applanation (GAT) using large-scale electronic health records (EHR).Design: Retrospective cohort study.Methods: A single pair of eligible TP/GAT IOP readings was randomly selected from the EHR for each ophthalmology patient at an academic ophthalmology center (2013-2022), yielding 4550 eligible measurements. We used Bland-Altman analysis to describe agreement between TP/GAT IOP differences and mean IOP measurements. We also used multivariable logistic regression to identify factors associated with different IOP readings in the same eye, including demographics, glaucoma diagnosis, and central corneal thickness (CCT). Primary outcome metrics were discrepant measurements between TP and GAT as defined by two methods: Outcome A (normal TP despite elevated GAT measurements), and Outcome B (TP and GAT IOP differences ≥6mmHg).Result: The mean TP/GAT IOP difference was 0.15mmHg (±5.49mmHg 95% CI). There was high correlation between the measurements (r=0.790, p<0.001). We found that TP overestimated pressures at IOP <16.5mmHg and underestimated at IOP >16.5mmHg (Fig. 4). Discrepant measurements accounted for 2.6% (N=116) and 5.2% (N=238) for outcomes A and B respectively. Patients with thinner CCT had higher odds of discrepant IOP (OR 0.88 per 25mum increase, CI [0.84-0.92], p<0.0001; OR 0.88 per 25mum increase, CI [0.84-0.92], p<0.0001 for outcomes A and B respectively).Conclusion: In a real-world academic practice setting, TP and GAT IOP measurements demonstrated close agreement, although 2.6% of measurements showed elevated GAT IOP despite normal TP measurements, and 5.2% of measurements were ≥6mmHg apart.
View details for DOI 10.1016/j.heliyon.2023.e18703
View details for PubMedID 37576221
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Ischemic optic neuropathy with and without optic disc drusen
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053795604032
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Impact of Metabolic Syndrome on Risk of Incident Primary Open Angle Glaucoma
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053758300007
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Use of Natural Language Processing to Accurately Identify Cataracts and Other Lens Pathology in Electronic Health Record Data - A Study Using the Sight Outcomes Research Collaborative (SOURCE) Repository
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053758303134
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Machine learning approaches for predicting glaucoma progression in a large multicenter electronic health records consortium: the Sight Outcomes Research Collaborative (SOURCE)
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053758301046
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Real-World Agreement of Same-Visit Tono-Pen Versus Goldmann Applanation Intraocular Pressure Measurements Using Electronic Health Records at an Academic Medical Center
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053758301079
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Clinical and Ophthalmic Biomarkers of Diabetes Mellitus: A Longitudinal Study of Visual Outcome
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053758307308
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Seeing What Patients See: Identifying Visual Acuity from Ophthalmology Clinical Notes Using Deep Learning and Natural Language Processing
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053795606125
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Predicting near-term glaucoma progression: An artificial intelligence approach using clinical free-text notes and data from electronic health records.
Frontiers in medicine
2023; 10: 1157016
Abstract
The purpose of this study was to develop a model to predict whether or not glaucoma will progress to the point of requiring surgery within the following year, using data from electronic health records (EHRs), including both structured data and free-text progress notes.A cohort of adult glaucoma patients was identified from the EHR at Stanford University between 2008 and 2020, with data including free-text clinical notes, demographics, diagnosis codes, prior surgeries, and clinical information, including intraocular pressure, visual acuity, and central corneal thickness. Words from patients' notes were mapped to ophthalmology domain-specific neural word embeddings. Word embeddings and structured clinical data were combined as inputs to deep learning models to predict whether a patient would undergo glaucoma surgery in the following 12 months using the previous 4-12 months of clinical data. We also evaluated models using only structured data inputs (regression-, tree-, and deep-learning-based models) and models using only text inputs.Of the 3,469 glaucoma patients included in our cohort, 26% underwent surgery. The baseline penalized logistic regression model achieved an area under the receiver operating curve (AUC) of 0.873 and F1 score of 0.750, compared with the best tree-based model (random forest, AUC 0.876; F1 0.746), the deep learning structured features model (AUC 0.885; F1 0.757), the deep learning clinical free-text features model (AUC 0.767; F1 0.536), and the deep learning model with both the structured clinical features and free-text features (AUC 0.899; F1 0.745).Fusion models combining text and EHR structured data successfully and accurately predicted glaucoma progression to surgery. Future research incorporating imaging data could further optimize this predictive approach and be translated into clinical decision support tools.
View details for DOI 10.3389/fmed.2023.1157016
View details for PubMedID 37122330
View details for PubMedCentralID PMC10133544
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PhacoTrainer: Deep Learning for Cataract Surgical Videos to Track Surgical Tools.
Translational vision science & technology
2023; 12 (3): 23
Abstract
Purpose: The purpose of this study was to build a deep-learning model that automatically analyzes cataract surgical videos for the locations of surgical landmarks, and to derive skill-related motion metrics.Methods: The locations of the pupil, limbus, and 8 classes of surgical instruments were identified by a 2-step algorithm: (1) mask segmentation and (2) landmark identification from the masks. To perform mask segmentation, we trained the YOLACT model on 1156 frames sampled from 268 videos and the public Cataract Dataset for Image Segmentation (CaDIS) dataset. Landmark identification was performed by fitting ellipses or lines to the contours of the masks and deriving locations of interest, including surgical tooltips and the pupil center. Landmark identification was evaluated by the distance between the predicted and true positions in 5853 frames of 10 phacoemulsification video clips. We derived the total path length, maximal speed, and covered area using the tip positions and examined the correlation with human-rated surgical performance.Results: The mean average precision score and intersection-over-union for mask detection were 0.78 and 0.82. The average distance between the predicted and true positions of the pupil center, phaco tip, and second instrument tip was 5.8, 9.1, and 17.1 pixels. The total path length and covered areas of these landmarks were negatively correlated with surgical performance.Conclusions: We developed a deep-learning method to localize key anatomical portions of the eye and cataract surgical tools, which can be used to automatically derive metrics correlated with surgical skill.Translational Relevance: Our system could form the basis of an automated feedback system that helps cataract surgeons evaluate their performance.
View details for DOI 10.1167/tvst.12.3.23
View details for PubMedID 36947046
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Re: Lee et al.: The association among blood pressure, blood pressure medications, and glaucoma in a nationwide electronic health records database (Ophthalmology. 2022;129:276-284.) REPLY
OPHTHALMOLOGY
2023; 130 (2): E5-E6
View details for Web of Science ID 000925117000001
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Reply.
Ophthalmology
2022
View details for DOI 10.1016/j.ophtha.2022.10.010
View details for PubMedID 36481104
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Blood Pressure Measures and Incident Primary Open-Angle Glaucoma.
Investigative ophthalmology & visual science
2022; 63 (13): 3
Abstract
To investigate the association of systemic blood pressure and incident primary open-angle glaucoma (POAG) using a large open-access database.Prospective cohort study included 484,268 participants from the UK Biobank without glaucoma at enrollment. Incident POAG events were recorded through assessment visits, hospital inpatient admissions, and primary care data. Blood pressure measures included systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), and mean arterial pressure (MAP). Repeated measurements throughout the study period were analyzed as time-varying covariables. The parameters were modeled as both categorical and continuous nonlinear variables. The primary outcome measure was the relative hazard of incident POAG.There were 2390 incident POAG events over 5,715,480 person-years of follow-up. Median follow-up was 12.08 years. In multivariable analyses, compared to SBP and PP in the normal range (SBP, 120-130 mmHg; PP, 40-50 mmHg), higher SBP and PP were associated with an increased risk of incident POAG (linear trend P = 0.038 for SBP, P < 0.001 for PP). Specifically, SBP of 130 to 140 mmHg or 140 to 150 mmHg was associated with a 1.16 higher hazard of incident POAG (95% CI, 1.01-1.32 and 1.01-1.33, respectively), whereas a PP of greater than 70 mmHg was associated with a 1.13 higher hazard of incident glaucoma (95% CI, 1.00-1.29). In multivariable models, no statistically significant associations were found for DBP or MAP with incident glaucoma. These findings were similar when blood pressure measures were modeled as continuous variables.Higher SBP and PP were associated with an increased risk of incident POAG. Further studies are required to characterize these relationships better.
View details for DOI 10.1167/iovs.63.13.3
View details for PubMedID 36469027
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Leveraging weak supervision to perform named entity recognition in electronic health records progress notes to identify the ophthalmology exam.
International journal of medical informatics
2022; 167: 104864
Abstract
To develop deep learning models to recognize ophthalmic examination components from clinical notes in electronic health records (EHR) using a weak supervision approach.A corpus of 39,099 ophthalmology notes weakly labeled for 24 examination entities was assembled from the EHR of one academic center. Four pre-trained transformer-based language models (DistilBert, BioBert, BlueBert, and ClinicalBert) were fine-tuned to this named entity recognition task and compared to a baseline regular expression model. Models were evaluated on the weakly labeled test dataset, a human-labeled sample of that set, and a human-labeled independent dataset.On the weakly labeled test set, all transformer-based models had recall > 0.93, with precision varying from 0.815 to 0.843. The baseline model had lower recall (0.769) and precision (0.682). On the human-annotated sample, the baseline model had high recall (0.962, 95 % CI 0.955-0.067) with variable precision across entities (0.081-0.999). Bert models had recall ranging from 0.771 to 0.831, and precision >=0.973. On the independent dataset, precision was 0.926 and recall 0.458 for BlueBert. The baseline model had better recall (0.708, 95 % CI 0.674-0.738) but worse precision (0.399, 95 % CI -0.352-0.451).We developed the first deep learning system to recognize eye examination components from clinical notes, leveraging a novel opportunity for weak supervision. Transformer-based models had high precision on human-annotated labels, whereas the baseline model had poor precision but higher recall. This system may be used to improve cohort and feature identification using free-text notes.Our weakly supervised approach may help amass large datasets of domain-specific entities from EHRs in many fields.
View details for DOI 10.1016/j.ijmedinf.2022.104864
View details for PubMedID 36179600
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Real-World Outcomes of Glaucoma Filtration Surgery using Electronic Health Records: An Informatics Study.
Journal of glaucoma
2022
Abstract
PRECIS: Utilising an automated pipeline for data extraction from electronic health records provides real-world information on the success of various glaucoma procedures, with tube shunt implantation associated with increased failure rates compared with trabeculectomy.BACKGROUND: We aimed to evaluate long-term survival of glaucoma surgeries using an automated pipeline for extraction of outcomes from electronic health records.METHODS: Retrospective observational study from a single academic center. Patients undergoing trabeculectomy, Ex-PRESS shunt, Baerveldt and Ahmed tube shunt insertion from 2009-2018 were identified from electronic health record procedure codes. Patient characteristics were identified from structured and unstructured fields using a previously validated natural language processing pipeline.RESULTS: 512 patients underwent 711 glaucoma surgeries: 287 trabeculectomies, 47 Ex-PRESS shunts, 274 Baerveldt and 103 Ahmed tube implantations. Median follow-up was 359 days. Mean baseline IOP was 24.4mmHg (SD 10.9) and 73.1% were on ≥3 medications. Compared to trabeculectomy, tube shunt surgery had higher risk of failure (Baerveldt: Hazard Ratio (HR) 1.44, 95% CI 1.02-2.02; Ahmed: HR 2.01, 95% CI 1.28-3.17). Previous glaucoma surgery was associated with increased failure (≥2 previous surgeries: HR 2.74, 95% CI 1.62-4.64), as was fewer baseline medications (<3 medications: HR 2.96, 95% CI 2.12-4.13) and male sex (HR 1.40, 95% CI 1.03-1.90). At 1-year, tube shunt patients had a 2.53mmHg (P=0.002) higher IOP compared to trabeculectomy patients.CONCLUSIONS: Baerveldt and Ahmed tube shunt implantation was associated with increased failure compared with trabeculectomy. Fewer baseline medications, previous glaucoma surgeries, and male sex were also risk factors for failure. These results demonstrate the utility of applying an informatics pipeline to electronic health records to investigate key clinical questions using real-world evidence.
View details for DOI 10.1097/IJG.0000000000002122
View details for PubMedID 36223316
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Corrigendum to Phase 1b Randomized Controlled Study of Short Course Topical Recombinant Human Nerve Growth Factor (rhNGF) for Neuroenhancement in Glaucoma: Safety, Tolerability, and Efficacy Measure Outcomes. Am J Ophthalmol 2022;234:223-234.
American journal of ophthalmology
2022
View details for DOI 10.1016/j.ajo.2022.07.018
View details for PubMedID 35977854
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Deep Learning Approaches for Predicting Glaucoma Progression Using Electronic Health Records and Natural Language Processing.
Ophthalmology science
2022; 2 (2): 100127
Abstract
Purpose: Advances in artificial intelligence have produced a few predictive models in glaucoma, including a logistic regression model predicting glaucoma progression to surgery. However, uncertainty exists regarding how to integrate the wealth of information in free-text clinical notes. The purpose of this study was to predict glaucoma progression requiring surgery using deep learning (DL) approaches on data from electronic health records (EHRs), including features from structured clinical data and from natural language processing of clinical free-text notes.Design: Development of DL predictive model in an observational cohort.Participants: Adult patients with glaucoma at a single center treated from 2008 through2020.Methods: Ophthalmology clinical notes of patients with glaucoma were identified from EHRs. Available structured data included patient demographic information, diagnosis codes, prior surgeries, and clinical information including intraocular pressure, visual acuity, and central corneal thickness. In addition, words from patients' first 120 days of notes were mapped to ophthalmology domain-specific neural word embeddings trained on PubMed ophthalmology abstracts. Word embeddings and structured clinical data were used as inputs to DL models to predict subsequent glaucoma surgery.Main Outcome Measures: Evaluation metrics included area under the receiver operating characteristic curve (AUC) and F1 score, the harmonic mean of positive predictive value, and sensitivity on a held-out test set.Results: Seven hundred forty-eight of 4512 patients with glaucoma underwent surgery. The model that incorporated both structured clinical features as well as input features from clinical notes achieved an AUC of 73% and F1 of 40%, compared with only structured clinical features, (AUC, 66%; F1, 34%) and only clinical free-text features (AUC, 70%; F1, 42%). All models outperformed predictions from a glaucoma specialist's review of clinical notes (F1, 29.5%).Conclusions: We can successfully predict which patients with glaucoma will need surgery using DL models on EHRs unstructured text. Models incorporating free-text data outperformed those using only structured inputs. Future predictive models using EHRs should make use of information from within clinical free-text notes to improve predictive performance. Additional research is needed to investigate optimal methods of incorporating imaging data into future predictive models as well.
View details for DOI 10.1016/j.xops.2022.100127
View details for PubMedID 36249690
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Explaining Deep Learning Models for Low Vision Prognosis
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2022
View details for Web of Science ID 000844437005157
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PhacoTrainer: Deep Learning for Cataract Surgical Videos to Track Surgical Tools
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2022
View details for Web of Science ID 000844401300225
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Named entity recognition in ophthalmology clinical progress notes: What's in the eye exam?
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2022
View details for Web of Science ID 000844401302060
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Impact of Type 2 Diabetes Mellitus and Insulin Use on Progression to Glaucoma Surgery in Primary Open Angle Glaucoma
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2022
View details for Web of Science ID 000844401305018
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Representation of Women in Ophthalmology Subspecialty Societies over 20
OPHTHALMOLOGY
2022; 129 (5): 587-590
View details for Web of Science ID 000791327000022
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Changes in glaucoma management following visual field testing and optical coherence tomography.
The British journal of ophthalmology
2022
Abstract
BACKGROUND: Optimal utilisation of investigations in glaucoma management remains unclear. We aimed to assess whether a temporal association exists between such testing and management changes.METHODS: Retrospective observational study using nationwide healthcare insurance claims database. Glaucoma outpatient encounters from patients aged ≥40 years with/without Humphrey visual field (HVF) and/or optical coherence tomography (OCT) were identified. An encounter was considered associated with an intervention if surgery occurred within 90 days, or if medication change or laser trabeculoplasty (LT) occurred within 30 days.RESULTS: 12 669 324 outpatient encounters of 1 863 748 individuals from 2003 to 2020 were included. HVF and OCT was performed during 32.8% and 22.2% of encounters respectively. Of the 36 763 (0.3%) encounters preceding surgery, 28.1% included HVF, 11.9% had OCT and 8.5% both. 79 181 (0.6%) visits preceded LT, of which 28.2% had HVF, 13.2% OCT and 9.3% both. Of the 515 899 (4.5%) encounters preceding medication changes, 29.1% had HVF, 16.7% OCT and 12.2% both. Compared with encounters with no investigations, those with HVF and/or OCT were associated with a 49% increased odds of a management change (p<0.001). In multivariate analyses, compared with encounters without investigations, visits with HVF alone had higher odds of subsequent surgery and LT, while HVF and/or OCT were associated with higher odds of medication change (p<0.001 for all).CONCLUSION: Glaucoma therapeutic changes occurred following approximately 5% of outpatient encounters. Surgery and LT were more likely to occur following a visit with a HVF rather than an OCT, while either investigation was associated with a higher odds of medication change.
View details for DOI 10.1136/bjophthalmol-2021-321010
View details for PubMedID 35450937
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Outcomes of Primary Trabeculectomy versus Combined Phacoemulsification-Trabeculectomy Using Automated Electronic Health Record Data Extraction.
Current eye research
2022: 1-7
Abstract
PURPOSE: Cataract is a known effect of trabeculectomy (TE), but some surgeons are hesitant to perform combined phacoemulsification-TE (PTE) due to a risk of increased TE failure. Herein, we compare intraocular pressure (IOP) lowering between trabeculectomy (TE) and phacoemulsification-TE (PTE) and investigate factors that impact patient outcomes.METHODS: We performed a retrospective study of adults undergoing primary TE or PTE at our institution from 2010 to 2017. We used Kaplan-Meier survival analysis to investigate time to TE failure, and Cox proportional hazards modeling to investigate predictors of TE failure, defined as undergoing a second glaucoma surgery or using more IOP-lowering medications than pre-operatively.RESULTS: 318 surgeries (218 TE; 100 PTE) from 268 patients were included. Median follow-up time was 753days. Mean baseline IOP was 21.1mmHg. There were no significant differences in IOP between TE and PTE groups beyond postoperative year 1, with 28.9-46.5% of TE and 35.5-44.4% of PTE groups achieving IOP ≤10. Final IOP was similar in both groups (p=0.22): 12.41 (SD 4.18) mmHg in the TE group and 14.05 (SD 5.45) in the PTE group. 84 (26.4%) surgeries met failure criteria. After adjusting for surgery type, sex, age, race, surgeon, and glaucoma diagnosis there were no significant differences in TE failure.CONCLUSION: This study suggests there is no significant difference in the risk of TE failure in patients receiving TE versus those receiving PTE.
View details for DOI 10.1080/02713683.2022.2045611
View details for PubMedID 35317681
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Predicting Glaucoma Progression Requiring Surgery Using Clinical Free-Text Notes and Transfer Learning With Transformers.
Translational vision science & technology
2022; 11 (3): 37
Abstract
Purpose: We evaluated the use of massive transformer-based language models to predict glaucoma progression requiring surgery using ophthalmology clinical notes from electronic health records (EHRs).Methods: Ophthalmology clinical notes for 4512 glaucoma patients at a single center from 2008 to 2020 were identified from the EHRs. Four different pre-trained Bidirectional Encoder Representations from Transformers (BERT)-based models were fine-tuned on ophthalmology clinical notes from the patients' first 120 days of follow-up for the task of predicting which patients would require glaucoma surgery. Models were evaluated with standard metrics, including area under the receiver operating characteristic curve (AUROC) and F1 score.Results: Of the patients, 748 progressed to require glaucoma surgery (16.6%). The original BERT model had the highest AUROC (73.4%; F1 = 45.0%) for identifying these patients, followed by RoBERTa, with an AUROC of 72.4% (F1 = 44.7%); DistilBERT, with an AUROC of 70.2% (F1 = 42.5%); and BioBERT, with an AUROC of 70.1% (F1 = 41.7%). All models had higher F1 scores than an ophthalmologist's review of clinical notes (F1 = 29.9%).Conclusions: Using transfer learning with massively pre-trained BERT-based models is a natural language processing approach that can access the wealth of clinical information stored within ophthalmology clinical notes to predict the progression of glaucoma. Future work to improve model performance can focus on integrating structured or imaging data or further tailoring the BERT models to ophthalmology domain-specific text.Translational Relevance: Predictive models can provide the basis for clinical decision support tools to aid clinicians in identifying high- or low-risk patients to maximally tailor glaucoma treatments.
View details for DOI 10.1167/tvst.11.3.37
View details for PubMedID 35353148
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Looking for low vision: Predicting visual prognosis by fusing structured and free-text data from electronic health records.
International journal of medical informatics
1800; 159: 104678
Abstract
INTRODUCTION: Low vision rehabilitation improves quality-of-life for visually impaired patients, but referral rates fall short of national guidelines. Automatically identifying, from electronic health records (EHR), patients with poor visual prognosis could allow targeted referrals to low vision services. The purpose of this study was to build and evaluate deep learning models that integrate EHR data that is both structured and free-text to predict visual prognosis.METHODS: We identified 5547 patients with low vision (defined as best documented visual acuity (VA)less than20/40) on≥1 encounter from EHR from 2009 to 2018, with≥1year of follow-up from the earliest date of low vision, who did not improve togreater than20/40 over 1year. Ophthalmology notes on or prior to the index date were extracted. Structured data available from the EHR included demographics, billing and procedure codes, medications, and exam findings including VA, intraocular pressure, corneal thickness, and refraction. To predict whether low vision patients would still have low vision a year later, we developed and compared deep learning models that used structured inputs and free-text progress notes. We compared three different representations of progress notes, including 1) using previously developed ophthalmology domain-specific word embeddings, and representing medical concepts from notes as 2) named entities represented by one-hot vectors and 3) named entities represented as embeddings. Standard performance metrics including area under the receiver operating curve (AUROC) and F1 score were evaluated on a held-out test set.RESULTS: Among the 5547 low vision patients in our cohort, 40.7% (N=2258) never improved to better than 20/40 over one year of follow-up. Our single-modality deep learning model based on structured inputs was able to predict low vision prognosis with AUROC of 80% and F1 score of 70%. Deep learning models utilizing named entity recognition achieved an AUROC of 79% and F1 score of 63%. Deep learning models further augmented with free-text inputs using domain-specific word embeddings, were able to achieve AUROC of 82% and F1 score of 69%, outperforming all single- and multiple-modality models representing text with biomedical concepts extracted through named entity recognition pipelines.DISCUSSION: Free text progress notes within the EHR provide valuable information relevant to predicting patients' visual prognosis. We observed that representing free-text using domain-specific word embeddings led to better performance than representing free-text using extracted named entities. The incorporation of domain-specific embeddings improved the performance over structured models, suggesting that domain-specific text representations may be especially important to the performance of predictive models in highly subspecialized fields such as ophthalmology.
View details for DOI 10.1016/j.ijmedinf.2021.104678
View details for PubMedID 34999410
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Representation of Women in Ophthalmology Subspecialty Societies over 20 Years.
Ophthalmology
1800
Abstract
The representation of women has increased over the last 20 years among ophthalmology subspecialty society new membership, award winners, and executive committee membership; however, proportional representation is still lacking at most benchmarks.
View details for DOI 10.1016/j.ophtha.2021.12.011
View details for PubMedID 34958831
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The association between blood pressure, blood pressure medications, and glaucoma in a nationwide electronic health records database.
Ophthalmology
2021
Abstract
PURPOSE: To measure the association between blood pressure, blood pressure medications, and glaucoma using the All of Us Research Program database.DESIGN: A retrospective, longitudinal cohort study leveraging a national electronic health records database administered by the National Institute of Health.SUBJECTS, PARTICIPANTS AND/OR CONTROLS: Eye patients in the All of Us Research Program database with at least fifteen months of follow up and one blood pressure (BP) measurement.METHODS, INTERVENTION, OR TESTING: Univariable and multivariable Cox regression models predicted the risk of developing incident open angle glaucoma (OAG). Mean arterial pressure (MAP) and the number of BP medication classes were entered as time-varying predictors to account for changes over time.MAIN OUTCOME MEASURES: The risk of developing incident OAG, as defined by billing diagnosis codes.RESULTS: Of 20815 eligible eye patients who qualified for this study, 462 developed OAG. Low blood pressure (MAP < 83.0 mmHg) was associated with increased risk of developing OAG (hazard ratio [HR] 1.32, 95% confidence interval [CI] 1.04 - 1.67). High blood pressure (MAP > 101.3 mmHg) and the number of BP medication classes were not associated with OAG after adjustment for covariates. Other risk factors associated with OAG included being Black (HR 3.31, 95% CI 2.63 - 4.17), Hispanic or Latino (HR 2.53, 95% CI 1.94 - 3.28), Asian (HR 2.22, 95% CI 1.24 - 3.97), older in age (80+ years, HR 20.1, 95% CI 9.10 - 44.5), and diabetic (HR 1.32, 95% CI 1.04 - 1.67). Female gender was associated with decreased hazard of developing OAG (HR 0.66, 95% CI 0.55 - 0.80). No significant interaction was observed between MAP and the number of BP medications on the risk of developing OAG.CONCLUSIONS: We found that low blood pressure is associated with increased risk of developing OAG in a national longitudinal electronic health records database. We did not find evidence supporting a differential effect of medically treated and untreated low BP. This study adds to the body of literature implicating vascular dysregulation as a potential etiology for the development of OAG, particularly emphasizing the lack of influence of blood pressure medications on this relationship.
View details for DOI 10.1016/j.ophtha.2021.10.018
View details for PubMedID 34688700
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Looking for Low Vision: Deep Learning and Natural Language Processing to Predict Visual Prognosis
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2021
View details for Web of Science ID 000690761600741
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PhacoTrainer: Deep Learning for Activity Recognition in Cataract Surgical Videos
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2021
View details for Web of Science ID 000690760500583
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y Predicting High Impact Ophthalmology Articles Using Machine Learning and Natural Language Processing
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2021
View details for Web of Science ID 000690761100077
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Rare Complications of Selective Laser Trabeculoplasty - Corneal Edema, Thinning and Hyperopic Shift: Incidences in the Optum Data Set
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2021
View details for Web of Science ID 000690761400742
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Determination of Patient Sentiment and Emotion in Ophthalmology: Infoveillance Tutorial on Web-Based Health Forum Discussions.
Journal of medical Internet research
2021; 23 (5): e20803
Abstract
BACKGROUND: Clinical data in social media are an underused source of information with great potential to allow for a deeper understanding of patient values, attitudes, and preferences.OBJECTIVE: This tutorial aims to describe a novel, robust, and modular method for the sentiment analysis and emotion detection of free text from web-based forums and the factors to consider during its application.METHODS: We mined the discussion and user information of all posts containing search terms related to a medical subspecialty (oculoplastics) from MedHelp, the largest web-based platform for patient health forums. We used data cleaning and processing tools to define the relevant subset of results and prepare them for sentiment analysis. We executed sentiment and emotion analyses by using IBM Watson Natural Language Understanding to generate sentiment and emotion scores for the posts and their associated keywords. The keywords were aggregated using natural language processing tools.RESULTS: Overall, 39 oculoplastic-related search terms resulted in 46,381 eligible posts within 14,329 threads. Posts were written by 18,319 users (117 doctors; 18,202 patients) and included 201,611 associated keywords. Keywords that occurred ≥500 times in the corpus were used to identify the most prominent topics, including specific symptoms, medication, and complications. The sentiment and emotion scores of these keywords and eligible posts were analyzed to provide concrete examples of the potential of this methodology to allow for a better understanding of patients' attitudes. The overall sentiment score reflects a positive, neutral, or negative sentiment, whereas the emotion scores (anger, disgust, fear, joy, and sadness) represent the likelihood of the presence of the emotion. In keyword grouping analyses, medical signs, symptoms, and diseases had the lowest overall sentiment scores (-0.598). Complications were highly associated with sadness (0.485). Forum posts mentioning body parts were related to sadness (0.416) and fear (0.321). Administration was the category with the highest anger score (0.146). The top 6 forum subgroups had an overall negative sentiment score; the most negative one was the Neurology forum, with a score of -0.438. The Undiagnosed Symptoms forum had the highest sadness score (0.448). The least likely fearful posts were those from the Eye Care forum, with a score of 0.260. The overall sentiment score was much more negative before the doctor replied. The anger, disgust, fear, and sadness emotion scores decreased in likelihood, whereas joy was slightly more likely to be expressed after doctors replied.CONCLUSIONS: This report allows physicians and researchers to efficiently mine and perform sentiment analysis on social media to better understand patients' perspectives and promote patient-centric care. Important factors to be considered during its application include evaluating the scope of the search; selecting search terms and understanding their linguistic usages; and establishing selection, filtering, and processing criteria for posts and keywords tailored to the desired results.
View details for DOI 10.2196/20803
View details for PubMedID 33999001
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Development and evaluation of novel ophthalmology domain-specific neural word embeddings to predict visual prognosis.
International journal of medical informatics
2021; 150: 104464
Abstract
OBJECTIVE: To develop and evaluate novel word embeddings (WEs) specific to ophthalmology, using text corpora from published literature and electronic health records (EHR).MATERIALS AND METHODS: We trained ophthalmology-specific WEs using 121,740 PubMed abstracts and 89,282 EHR notes using word2vec continuous bag-of-words architecture. PubMed and EHR WEs were compared to general domain GloVe WEs and general biomedical domain BioWordVec embeddings using a novel ophthalmology-domain-specific 200-question analogy test and prediction of prognosis in 5547 low vision patients using EHR notes as inputs to a deep learning model.RESULTS: We found that many words representing important ophthalmic concepts in the EHR were missing from the general domain GloVe vocabulary, but covered in the ophthalmology abstract corpus. On ophthalmology analogy testing, PubMed WEs scored 95.0 %, outperforming EHR (86.0 %) and GloVe (91.0 %) but less than BioWordVec (99.5 %). On predicting low vision prognosis, PubMed and EHR WEs resulted in similar AUROC (0.830; 0.826), outperforming GloVe (0.778) and BioWordVec (0.784).CONCLUSION: We found that using ophthalmology domain-specific WEs improved performance in ophthalmology-related clinical prediction compared to general WEs. Deep learning models using clinical notes as inputs can predict the prognosis of visually impaired patients. This work provides a framework to improve predictive models using domain-specific WEs.
View details for DOI 10.1016/j.ijmedinf.2021.104464
View details for PubMedID 33892445
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Phase 1b randomized controlled study of short course topical recombinant human nerve growth factor (rhNGF) for neuroenhancement in glaucoma: safety, tolerability and efficacy measure outcomes.
American journal of ophthalmology
2021
Abstract
No approved therapies directly target retinal ganglion cells (RGCs) for neuroprotection or neuroenhancement in glaucoma. Recombinant human nerve growth factor (rhNGF) has been shown to promote RGC survival and function in animal models of optic neuropathy. Here we evaluate safety, tolerability, and efficacy of short-term, high-dose rhNGF eye drops versus placebo in a cohort of glaucoma patients.This study is a single-center, randomized, double-masked, vehicle-controlled, parallel group study designed to assess safety and tolerability as well as short-term neuroenhancement of structure and function (Clinicaltrials.gov NCT02855450). Sixty open-angle glaucoma patients were randomized 40:20 to receive either 180 μg/ml rhNGF or vehicle control eye drops in both eyes, three times daily for 8 weeks, with a 24-week post-treatment follow-up. One eye was officially selected as the study eye, although both eyes were studied and dosed. Primary endpoints were safety, as assessed through adverse events, and tolerability, as assessed through patient reported outcomes. Secondary outcome measures included best corrected visual acuity (BCVA), Humphrey visual field (HVF), electroretinogram (ERG), and optical coherence tomography (OCT) of retinal nerve fiber layer (RNFL) thickness at baseline, after 8 weeks of treatment, and at 4 and 24 weeks after treatment (12- and 32-weeks total).Of the 60 randomized subjects, 23 were female (38%) and the average age was 66.1 years. Through week 32, there were no treatment-related serious adverse events, including no unexpectedly severe progression of optic neuropathy, no adverse events affecting ocular function or pressure, and no drug-related systemic toxicity. Topical high-dose rhNGF was tolerated well, with low level of symptom burden mainly eliciting periocular ache (in 52% of treated, 5% of placebo) and only 3 patients (7.5%) discontinuing treatment due to discomfort, out of whom 1 patient (2.5%) prematurely withdrawing from the study. There were no statistically significant differences in global indices of HVF, and no meaningful differences in total, quadrant, or clock-hour mean RNFL thickness between the groups, although both of these function and structure measures showed non-significant trends towards significance in favor of rhNGF. Real-world participant data was used to generate an estimate of cohort size needed to power subsequent studies.rhNGF is safe and tolerable in a topical 180 μg/ml formulation. Although no statistically significant short-term neuroenhancement was detected in this trial, given the strong effects of NGF in preclinical models and trends detected in this study, analysis for efficacy in a neuroprotection trial is warranted.
View details for DOI 10.1016/j.ajo.2021.11.002
View details for PubMedID 34780798
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PhacoTrainer: A Multicenter Study of Deep Learning for Activity Recognition in Cataract Surgical Videos.
Translational vision science & technology
2021; 10 (13): 23
Abstract
To build and evaluate deep learning models for recognizing cataract surgical steps from whole-length surgical videos with minimal preprocessing, including identification of routine and complex steps.We collected 298 cataract surgical videos from 12 resident surgeons across 6 sites and excluded 30 incomplete, duplicated, and combination surgery videos. Videos were downsampled at 1 frame/second. Trained annotators labeled 13 steps of surgery: create wound, injection into the eye, capsulorrhexis, hydrodissection, phacoemulsification, irrigation/aspiration, place lens, remove viscoelastic, close wound, advanced technique/other, stain with trypan blue, manipulating iris, and subconjunctival injection. We trained two deep learning models, one based on the VGG16 architecture (VGG model) and the second using VGG16 followed by a long short-term memory network (convolutional neural network [CNN]- recurrent neural network [RNN] model). Class activation maps were visualized using Grad-CAM.Overall top 1 prediction accuracy was 76% for VGG model (93% for top 3 accuracy) and 84% for the CNN-RNN model (97% for top 3 accuracy). The microaveraged area under receiver-operating characteristic curves was 0.97 for the VGG model and 0.99 for the CNN-RNN model. The microaveraged average precision score was 0.83 for the VGG model and 0.92 for the CNN-RNN model. Class activation maps revealed the model was appropriately focused on the instrumentation used in each step to identify which step was being performed.Deep learning models can classify cataract surgical activities on a frame-by-frame basis with remarkably high accuracy, especially routine surgical steps.An automated system for recognition of cataract surgical steps could provide to residents automated feedback metrics, such as the length of time spent on each step.
View details for DOI 10.1167/tvst.10.13.23
View details for PubMedID 34784415
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Interpreting Deep Learning Studies in Glaucoma: Unresolved Challenges.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
2021; 10 (3): 261-267
Abstract
Deep learning algorithms as tools for automated image classification have recently experienced rapid growth in imaging-dependent medical specialties, including ophthalmology. However, only a few algorithms tailored to specific health conditions have been able to achieve regulatory approval for autonomous diagnosis. There is now an international effort to establish optimized thresholds for algorithm performance benchmarking in a rapidly evolving artificial intelligence field. This review examines the largest deep learning studies in glaucoma, with special focus on identifying recurrent challenges and limitations within these studies which preclude widespread clinical deployment. We focus on the 3 most common input modalities when diagnosing glaucoma, namely, fundus photographs, spectral domain optical coherence tomography scans, and standard automated perimetry data. We then analyze 3 major challenges present in all studies: defining the algorithm output of glaucoma, determining reliable ground truth datasets, and compiling representative training datasets.
View details for DOI 10.1097/APO.0000000000000395
View details for PubMedID 34383718
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The Impact of COVID-19 on Missed Ophthalmology Clinic Visits
CLINICAL OPHTHALMOLOGY
2021; 15: 4645-4657
Abstract
To measure the COVID-19 pandemic impact on missed ophthalmology clinic visits and the influence of patient and eye disease characteristics on likelihood of missing clinic visits before and during the pandemic.A retrospective observational study analyzing eye clinic patients at a large tertiary care academic institution. We identified patients scheduled for eye care during pre-COVID-19 (January 1-February 29, 2020) and early COVID-19 (March 16-May 31, 2020) time periods. Missed appointment frequency and characteristics were evaluated during each time period. Multivariable logistic regression models were developed to examine adjusted odds of having at least one missed appointment during a given time period. Covariates included age, sex, race/ethnicity, marital status, preferred language (non-English vs English), insurance, distance from clinic, and diagnosis.Overall, 82.0% (n = 11,998) of pre-COVID-19 patients completed all scheduled visits, compared to only 59.3% (n = 9020) during COVID-19. Missed visits increased dramatically in late March 2020, then improved week by week through the end of May 2020. General ophthalmology/cataract and strabismus clinics had the highest rates of missed clinic visits during the COVID-19 period; neuro-ophthalmology, retina, cornea, oculoplastics and glaucoma had the lowest. Females, Blacks, Hispanics, Asians, ages 50+, and married patients had higher adjusted odds of missing clinic visits, both pre-COVID-19 and during COVID-19. Asian, elderly, and cataract patients had the highest adjusted odds of missing clinic visits during COVID-19 and had significant increases in odds compared to pre-COVID-19. Non-married, diabetic macular edema, and wet age-related macular degeneration patients had the lowest adjusted odds of missed visits during COVID-19.Missed clinic visits increased dramatically during the COVID-19 pandemic, particularly among elderly and nonwhite patients. These findings reflect differences in eye care delivery during the pandemic, and they indicate opportunities to target barriers to care, even during non-pandemic eras.
View details for DOI 10.2147/OPTH.S341739
View details for Web of Science ID 000730419000002
View details for PubMedID 34916776
View details for PubMedCentralID PMC8667753
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Association of ocular antihypertensive medications and the development and progression of age-related macular degeneration in a U.S. insurance claims database.
Current eye research
2020
Abstract
Purpose/Aim : To assess whether ocular antihypertensives are associated with development and progression of age-related macular degeneration (AMD). Materials and Methods : This retrospective, observational cohort study using healthcare claims data from a U.S. nationwide managed-care network between January 1, 2006 and December 31, 2016 included enrollees ≥40 years old with primary open angle glaucoma with or without a diagnosis of nonexudative AMD at the index date. Hazard ratios (HR) for developing AMD or progressing from nonexudative to exudative AMD with exposure to ocular antihypertensive medications were analyzed. Results : Of 132 963 eligible enrollees, 118 174 (87.5%) had no diagnosis of AMD at baseline while 14 789 (12.5%) had a diagnosis of nonexudative AMD. Prostaglandin analog exposure had a decreased hazard of developing AMD among individuals without baseline disease (HR, 0.90; 95% CI, 0.87-0.94; p<0.0001), while topical alpha2-agonist exposure demonstrated an increased hazard of AMD development (HR, 1.08; 95% CI, 1.03-1.14; p=0.004). Among patients with baseline nonexudative AMD, topical carbonic anhydrase inhibitor exposure was associated with a decreased hazard of progressing to exudative disease (HR, 0.84; 95% CI, 0.71-0.99; p=0.04) while topical alpha2-agonists had increased hazard (HR, 1.17; 95% CI, 1.01-1.36; p=0.04). Conclusions : Certain ocular antihypertensive medications may be associated with development or progression of AMD. Their role in AMD pathogenesis should be better understood as they are considered for therapeutics in this disease.
View details for DOI 10.1080/02713683.2020.1849731
View details for PubMedID 33174463
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Sustaining Independent Careers in Vision Research: Demographics and Success in Second R01 Attainment Among Clinician-Scientists from 1985 to 2019
TRANSLATIONAL VISION SCIENCE & TECHNOLOGY
2020; 9 (12)
View details for Web of Science ID 000604304000006
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Sustaining Independent Careers in Vision Research: Demographics and Success in Second R01 Attainment Among Clinician-Scientists from 1985 to 2019.
Translational vision science & technology
2020; 9 (12): 32
Abstract
Purpose: To evaluate the success of ophthalmology and optometry clinician-scientists in obtaining a second R01 (renewal or new) and factors associated with this success, including gender, clinical specialty, degree, institution, and bench versus non-bench research.Methods: First-time National Eye Institute (NEI) R01 awardee data from 1985 to 2014 (N = 234) were analyzed to calculate second R01 success rates. Only R01 awards to ophthalmology or optometry clinician-scientists were included. Demographic data were obtained from clinicians with first-time NEI R01 funding spanning from 1962 to 2019 (N = 386). We obtained information regarding time span of the first R01, year of second R01, institution, and project title on the National Institutes of Health (NIH) Research Portfolio Online Reporting Tool, Expenditures and Results (RePORTER) database, and additional measures of gender, clinical specialty, and degree by performing Internet searches.Results: Overall, from 1985 to 2014, 62.8% of ophthalmology or optometry clinician-scientists were awarded a second R01; at 5 years after receipt of the first R01 (the typical length of an R01), only 3.9% received their second R01. None of the factors examined (temporal cohort, gender, clinical specialty, degree, institution, or bench vs. non-bench research) was significantly associated with successful attainment of a second R01.Conclusions: We found an overall success rate of 62.8% for receiving a second R01, but 5 years after the first R01 an attainment rate for a second R01 of only 4%.Translational Relevance: Our study provides insight on significant leaks in the clinician-scientist pipeline and raises questions of how stakeholders should support this important group of individuals at the intersection of clinical medicine and biomedical research.
View details for DOI 10.1167/tvst.9.12.32
View details for PubMedID 33262906
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Big data requirements for artificial intelligence.
Current opinion in ophthalmology
2020
Abstract
PURPOSE OF REVIEW: To summarize how big data and artificial intelligence technologies have evolved, their current state, and next steps to enable future generations of artificial intelligence for ophthalmology.RECENT FINDINGS: Big data in health care is ever increasing in volume and variety, enabled by the widespread adoption of electronic health records (EHRs) and standards for health data information exchange, such as Digital Imaging and Communications in Medicine and Fast Healthcare Interoperability Resources. Simultaneously, the development of powerful cloud-based storage and computing architectures supports a fertile environment for big data and artificial intelligence in health care. The high volume and velocity of imaging and structured data in ophthalmology and is one of the reasons why ophthalmology is at the forefront of artificial intelligence research. Still needed are consensus labeling conventions for performing supervised learning on big data, promotion of data sharing and reuse, standards for sharing artificial intelligence model architectures, and access to artificial intelligence models through open application program interfaces (APIs).SUMMARY: Future requirements for big data and artificial intelligence include fostering reproducible science, continuing open innovation, and supporting the clinical use of artificial intelligence by promoting standards for data labels, data sharing, artificial intelligence model architecture sharing, and accessible code and APIs.
View details for DOI 10.1097/ICU.0000000000000676
View details for PubMedID 32657996
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Intraocular Pressure Changes after Cataract Surgery in Patients with and without Glaucoma: An Informatics-Based Approach.
Ophthalmology. Glaucoma
2020
Abstract
PURPOSE: To evaluate changes in intraocular pressure (IOP) after cataract surgery among patients with or without glaucoma using automated extraction of data from electronic health records (EHRs).DESIGN: Retrospective cohort study.PARTICIPANTS: Adults who underwent standalone cataract surgery at a single academic center from 2009-2018.METHODS: Patient information was identified from procedure and billing codes, demographic tables, medication orders, clinical notes, and eye examination fields in the EHR. A previously validated natural language processing pipeline was used to identify laterality of cataract surgery from operative notes and laterality of eye medications from medication orders. Cox proportional hazards modeling evaluated factors associated with the main outcome of sustained postoperative IOP reduction.MAIN OUTCOME MEASURES: Sustained post-cataract surgery IOP reduction, measured at 14 months or the last follow-up while using equal or fewer glaucoma medications compared with baseline and without additional glaucoma laser or surgery on the operative eye.RESULTS: The median follow-up for 7574 eyes of 4883 patients who underwent cataract surgery was 244 days. The mean preoperative IOP for all patients was 15.2 mmHg (standard deviation [SD], 3.4 mmHg), which decreased to 14.2 mmHg (SD, 3.0 mmHg) at 12 months after surgery. Patients with IOP of 21.0 mmHg or more showed mean postoperative IOP reduction ranging from -6.2 to -6.9 mmHg. Cataract surgery was more likely to yield sustained IOP reduction for patients with primary open-angle glaucoma (hazard ratio [HR], 1.19; 95% confidence interval, 1.05-1.36) or narrow angles or angle closure (HR, 1.21; 95% confidence interval, 1.08-1.34) compared with patients without glaucoma. Those with a higher baseline IOP were more likely to achieve postoperative IOP reduction (HR, 1.06 per 1-mmHg increase in baseline IOP; 95% confidence interval, 1.05-1.07).CONCLUSIONS: Our results suggest that patients with primary open-angle glaucoma or with narrow angles or chronic angle closure were more likely to achieve sustained IOP reduction after cataract surgery. Patients with higher baseline IOP had increasingly higher odds of achieving reduction in IOP. This evidence demonstrates the potential usefulness of a pipeline for automated extraction of ophthalmic surgical outcomes from EHR to answer key clinical questions on a large scale.
View details for DOI 10.1016/j.ogla.2020.06.002
View details for PubMedID 32703703
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Informatics for Investigation of Glaucoma Filtration Surgery Outcomes Using Electronic Health Records
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2020
View details for Web of Science ID 000554495702337
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Characterization of 'Early Established' Clinician-Scientist Cohorts in Ophthalmology: Success Rates for 2nd R01 Grant Awards
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2020
View details for Web of Science ID 000554528304332
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Management of the glaucoma patient progressing at low normal intraocular pressure.
Current opinion in ophthalmology
2019
Abstract
PURPOSE OF REVIEW: Patients with glaucoma with disease progression despite low or normal intraocular pressure (IOP) present special challenges to the treating clinician. Treatment goals may depend on whether patients have apparent low IOP with concurrent treatment or have low IOP at baseline without treatment. We review the diagnostic and therapeutic approaches to these patients.RECENT FINDINGS: Apparent progression at low IOP should start with confirmation of IOP, made easier by devices enabling patient home self-tonometry. Suspected visual field progression should be confirmed by repeat testing prior to advancement of therapy. Trabeculectomy remains the most effective surgical method of achieving long-term success, particularly when there is a low starting IOP. Drainage tube implantation or the use of novel micro-incisional non-bleb-forming procedures are less likely to be successful in achieving low IOP goals.SUMMARY: Diagnostic testing is important in confirming progressive glaucomatous disease at low IOP levels. The most effective way of slowing the progression of glaucoma in a patient with low IOP is to lower the IOP further, sometimes to single digit levels, which is most often achievable with trabeculectomy.
View details for DOI 10.1097/ICU.0000000000000640
View details for PubMedID 31895152
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Automated extraction of ophthalmic surgery outcomes from the electronic health record.
International journal of medical informatics
2019; 133: 104007
Abstract
OBJECTIVE: Comprehensive analysis of ophthalmic surgical outcomes is often restricted by limited methodologies for efficiently and accurately extracting clinical information from electronic health record (EHR) systems because much is in free-text form. This study aims to utilize advanced methods to automate extraction of clinical concepts from the EHR free text to study visual acuity (VA), intraocular pressure (IOP), and medication outcomes of cataract and glaucoma surgeries.METHODS: Patients who underwent cataract or glaucoma surgery at an academic medical center between 2009 and 2018 were identified by Current Procedural Terminology codes. Rule-based algorithms were developed and used on EHR clinical narrative text to extract intraocular lens (IOL) power and implant type, as well as to create a surgery laterality classifier. MedEx (version 1.3.7) was used on free-text clinical notes to extract information on eye medications and compared to information from medication orders. Random samples of free-text notes were reviewed by two independent masked annotators to assess inter-annotator agreement on outcome variable classification and accuracy of classifiers. VA and IOP were available from semi-structured fields.RESULTS: This study cohort included 6347 unique patients, with 8550 stand-alone cataract surgeries, 451 combined cataract/glaucoma surgeries, and 961 glaucoma surgeries without concurrent cataract surgery. The rule-based laterality classifier achieved 100% accuracy compared to manual review of a sample of operative notes by independent masked annotators. For cataract surgery alone, glaucoma surgery alone, or combined cataract/glaucoma surgeries, our automated extraction algorithm achieved 99-100% accuracy compared to manual annotation of samples of notes from each group, including IOL model and IOL power for cataract surgeries, and glaucoma implant for glaucoma surgeries. For glaucoma medications, there was 90.7% inter-annotator agreement. After adjudication, 85.0% of medications identified by MedEx determined to be correct. Determination of surgical laterality enabled evaluation of pre- and postoperative VA and IOP for operative eyes.CONCLUSION: This text-processing pipeline can accurately capture surgical laterality and implant model usage from free-text operative notes of cataract and glaucoma surgeries, enabling extraction of clinical outcomes including visual acuities, intraocular pressure, and medications from the EHR system. Use of this approach with EHRs to assess ophthalmic surgical outcomes can benefit research groups interested in studying the safety and clinical efficacies of different surgical approaches.
View details for DOI 10.1016/j.ijmedinf.2019.104007
View details for PubMedID 31706228
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Understanding Patient Attitudes Toward Multifocal Intraocular Lenses in Online Medical Forums Through Sentiment Analysis.
Studies in health technology and informatics
2019; 264: 1378–82
Abstract
Multifocal intraocular lens implants (IOLs) are a premium option for cataract surgery which patients may purchase to achieve improved spectacle-independence for near vision but may have trade-offs with visual quality. We demonstrate the use of sentiment analysis to evaluate multifocal lenses discussed on MedHelp, a leading online health forum. A search for "multifocal IOL" was performed on MedHelp.org on November 1, 2016, yielding relevant patient posts. Sentiment analysis was performed using IBM's Watson, which extracted 30,066 unique keywords and their associated sentiment scores from 7495 posts written by 1474 unique patient users. Keywords associated with monovision, monofocal, and toric lenses had positive mean sentiment, significantly higher than for keywords associated with multifocals, which had negative mean sentiment (p < 0.001, ANOVA). Many keywords represented complaints and were associated with negative sentiment, including glare, halo, and ghosting. Sentiment analysis can provide insights into patient perspectives towards multifocal lenses by interpreting online patient posts.
View details for DOI 10.3233/SHTI190453
View details for PubMedID 31438152
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Understanding Patient Attitudes Toward Multifocal Intraocular Lenses in Online Medical Forums Through Sentiment Analysis
IOS PRESS. 2019: 1378–82
View details for DOI 10.3233/SHT1190453
View details for Web of Science ID 000569653400278
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Ocular Antihypertensive Medication Use After iStent Implantation Concurrent With Cataract Surgery vs Cataract Surgery Alone in a Large US Health Care Claims Database.
JAMA ophthalmology
2018
Abstract
Importance: The iStent Trabecular Micro-Bypass (Glaukos Corporation) is a minimally invasive glaucoma implant used in conjunction with cataract surgery to lower intraocular pressure.Objective: To determine whether implantation of the iStent concurrent with cataract surgery is associated with reduced use of ocular antihypertensive medications in a US health care claims database.Design, Setting, and Participants: Retrospective, observational longitudinal cohort study of individuals enrolled in a US managed care network who underwent iStent implantation with cataract surgery (iStent/CEIOL) from 2012 to 2016 (n=1509 bilateral and n=1462 unilateral surgery). A control group of individuals who underwent bilateral cataract surgery only (CEIOL) were matched 1:1 to patients undergoing bilateral iStent/CEIOL on baseline demographic and clinical factors. Data were analyzed between November 1, 2017, and January 31, 2018.Main Outcomes and Measures: The number of topical ocular antihypertensive agents used postoperatively by patients undergoing iStent/CEIOL compared with baseline and with matched CEIOL control individuals, and hazard ratios with 95% confidence intervals for sustained reduced use of at least 1 topical ocular antihypertensive agent postoperatively.Results: Of the 2971 eligible enrollees, mean age at first surgery was 74.3 years, and 1659 (55.8%) were women. Patients undergoing iStent/CEIOL had diagnoses that included primary open-angle glaucoma (n=2329; 78.4%), narrow angles (n=381; 12.8%), and secondary glaucomas (n=261; 8.8%). At baseline, 1223 (41.2%) were receiving no topical glaucoma agents; 876 (29.5%), 437 (14.7%), and 435 (14.6%) were receiving 1, 2, or at least 3 agents, respectively. Although only 678 persons (22.8%) completed at least 2 years of postoperative follow-up, the proportion of patients receiving no drops increased postoperatively (64.7%, 20-24 months, P<.001, chi2). Patients receiving at least 1 topical agent at baseline had mean reduction of 1.01 and 0.61 medications used at 20 to 24 months with bilateral or unilateral surgery, respectively (both P<.001, paired t). Sustained reduction in glaucoma medication use was more likely in patients receiving at least 3 vs 1 medication at baseline (hazard ratio, 1.68; 95% CI, 1.36-2.09). Compared with matched control individuals undergoing CEIOL, patients undergoing bilateral iStent/CEIOL had a greater mean reduction in drops used (0.99 vs 0.49; postoperative month 20-24; P<.001; paired t) and a higher proportion receiving no drops postoperatively (73.5% vs 55.3%, postoperative month 20-24; P<.001; chi2).Conclusions and Relevance: Implantation of the iStent trabecular micro-bypass stent concurrent with cataract surgery was associated with moderately reduced use of topical ocular antihypertensive medication. Reduction in the use of glaucoma medications may lessen the burden of medication adverse effects and promote better adherence.
View details for PubMedID 30267072
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Reduction of Ocular Antihypertensive Medication Use After IStent Implantation in a Large US Managed Care Network
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2018
View details for Web of Science ID 000442912506049
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Utilization of Ophthalmologist Consultation for Emergency Care at a University Hospital
JAMA OPHTHALMOLOGY
2018; 136 (4): 428–31
Abstract
Nearly 2 million patients visit emergency departments (EDs) because of eye concerns annually in the United States. How hospitals currently assign these patients to treatment is important for designing systems that equitably allocate resources for eye care in urgent settings.To investigate factors associated with ophthalmology consultation for eye-related adult ED encounters to assess possible disparities by sex, race/ethnicity, language preference, or residential distance from the medical center.Retrospective observational study of 13 361 adult ED encounters associated with an eye-related billing diagnosis between January 1, 2010, and September 30, 2015, at the University of Michigan Medical Center in Ann Arbor.Measures available from the University of Michigan clinical data warehouse included age, sex, race/ethnicity, preferred language, home distance from the ED, calendar year of encounter, and Charlson-Deyo Comorbidity Index score.Association of the ED encounter with ophthalmology consultation. An ophthalmology consultation was identified by cross-referencing ophthalmology faculty and clinical instructors from 2010 to 2015 against billing providers for consultations using the Charlson-Deyo Comorbidity Index score and billing codes. Measures included patient age, sex, race/ethnicity, home address, preferred language (English vs non-English), and calendar year of encounter.Among the 13 361 encounters, 6840 (51.2%) involved a female patient. Mean (SD) age at encounter was 50.7 (19.3) years; 10 033 patients (75.1%) were of white and 1969 (14.7%) of black race/ethnicity. English was the preferred language for 13 022 patients (97.5%). The ophthalmology service was consulted in 5289 encounters (39.6%). Black patients had significantly lower odds of an ophthalmology consultation than white patients (odds ratio [OR], 0.85; 95% CI, 0.75-0.96). Patients who preferred a non-English language had significantly lower odds of receiving an ophthalmology consultation (OR, 0.73; 95% CI, 0.55-0.98).Many of the 13 361 eye-related ED encounters were managed by ED clinicians with no ophthalmology consultation. Patients who were black or who preferred a language other than English were less likely to have an ophthalmologist involved in their care. The associations found in this observational study do not imply causation but suggest disparities in care that should be further investigated.
View details for PubMedID 29543941
View details for PubMedCentralID PMC5876882
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Ophthalmic Screening Patterns Among Youths With Diabetes Enrolled in a Large US Managed Care Network
JAMA OPHTHALMOLOGY
2017; 135 (5): 432-438
Abstract
Ophthalmic screening to check for diabetic retinopathy (DR) is important to prevent vision loss in persons with diabetes. The American Academy of Ophthalmology recommends that ophthalmic screening for DR occur beginning at 5 years after initial diabetes diagnosis for youths with type 1 diabetes; the American Diabetes Association recommends screening of youths with type 2 diabetes at the time of initial diagnosis. To our knowledge, it is unknown to what extent youths with diabetes obtain eye examinations in accordance with these guidelines.To assess the rate of obtaining ophthalmic examinations and factors associated with receipt of eye examinations for youths with diabetes.This retrospective, longitudinal cohort study examined youths 21 years or younger with newly diagnosed diabetes enrolled in a US managed care network from January 1, 2001, through December 31, 2014.Kaplan-Meier survival curves estimated the time from initial diabetes diagnosis to first eye examination by an ophthalmologist or optometrist. Multivariable Cox proportional hazards regression models identified factors associated with receiving an ophthalmic examination after initial diabetes diagnosis.Among 5453 youths with type 1 diabetes (median age at initial diagnosis, 11 years; interquartile range, 8-15 years; 2972 male [54.5%]; 4505 white [82.6%]) and 7233 youths with type 2 diabetes (median age at initial diagnosis, 19 years; interquartile range, 16-22 years; 1196 male [16.5%]; 5052 white [69.9%]), 64.9% of patients with type 1 diabetes and 42.2% of patients with type 2 diabetes had undergone an eye examination by 6 years after initial diabetes diagnosis. Black youths (1367 [10.8%] of the sample) had an 11% and Latino youths (1450 [11.4%] of the sample) had an 18% decreased hazard of undergoing an eye examination by 6 years compared with white youths (black youths: adjusted hazard ratio [HR], 0.89; 95% CI, 0.79-0.99; Latino youths: HR, 0.82; 95% CI, 0.73-0.92). As household net worth increased, youths were increasingly more likely to undergo an eye examination by 6 years after initial diabetes diagnosis (net worth of ≥$500 000 vs <$25 000: HR, 1.50; 95% CI, 1.34-1.68).Despite possessing health insurance, many youths with diabetes are not receiving eye examinations by 6 years after initial diagnosis to monitor for DR. These data suggest that adherence to clinical practice guidelines is particularly challenging for racial minorities and youths from less affluent families.
View details for DOI 10.1001/jamaophthalmol.2017.0089
View details for Web of Science ID 000401113400009
View details for PubMedID 28334336
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Patient-centered and visual quality outcomes of premium cataract surgery: a systematic review.
European journal of ophthalmology
2017: 0-?
Abstract
Over 8 million cataract surgeries are performed in the United States and the European Union annually, with many patients choosing to pay out of pocket for premium options including premium intraocular lens implants (IOLs) or laser-assisted cataract surgery (LACS). This report provides a systematic review evaluating patient-centered and visual quality outcomes comparing standard monofocal IOLs to premium cataract surgery options.PubMed and EMBASE were searched for publications published between January 1, 1980, and September 18, 2016, on multifocal, accommodative, and toric IOLs, monovision, and LACS, which reported on 1) dysphotopsias, 2) contrast sensitivity, 3) spectacle independence, 4) vision-related quality of life or patient satisfaction, and 5) IOL exchange.Multifocal lenses achieved higher rates of spectacle independence compared to monofocal lenses but also had higher reported frequency of dysphotopsia and worse contrast sensitivity, especially with low light or glare. Accommodative lenses were not associated with reduced contrast sensitivity or more dysphotopsia but had only modest improvements in spectacle independence compared to monofocal lenses. Studies of monovision did not target a sufficiently myopic outcome in the near-vision eye to achieve the full potential for spectacle independence. Patients reported high levels of overall satisfaction regardless of implanted IOL. No studies correlated patient-reported outcomes with patient expectations.Studies are needed to thoroughly compare patient-reported outcomes with concomitant patient expectations. In light of the substantial patient costs for premium options, patients and their surgeons will benefit from a better understanding of which surgical options best meet patients' expectations and how those expectations can be impacted by premium versus monofocal-including monovision-options.
View details for DOI 10.5301/ejo.5000978
View details for PubMedID 28574135
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Incidence and Risk Factors for Developing Diabetic Retinopathy among Youths with Type 1 or Type 2 Diabetes throughout the United States.
Ophthalmology
2017; 124 (4): 424-430
Abstract
Despite the increasing prevalence of type 2 diabetes mellitus (T2DM) among children and adolescents, little is known about their risk of developing diabetic retinopathy (DR). We sought to identify risk factors for DR in youths with diabetes mellitus, to compare DR rates for youths with type 1 diabetes mellitus (T1DM) and those with T2DM, and to assess whether adherence to DR screening guidelines promoted by the American Academy of Ophthalmology, American Academy of Pediatrics, and American Diabetes Association adequately capture youths with DR.Retrospective observational longitudinal cohort study.Youths aged ≤21 years with newly diagnosed T1DM or T2DM who were enrolled in a large US managed-care network.In this study of youths aged ≤21 years with newly diagnosed T1DM or T2DM who were under ophthalmic surveillance, we identified the incidence and timing of DR onset. Kaplan-Meier survival curves assessed the timing of initial diagnosis of DR for participants. Multivariable Cox proportional hazard regression modeling identified factors associated with the hazard of developing DR. Model predictors were age and calendar year at initial diabetes mellitus diagnosis, sex, race/ethnicity, net worth, and glycated hemoglobin A1c fraction (HbA1c).Hazard ratios (HRs) with 95% confidence intervals (CIs) for developing DR.Among the 2240 youths with T1DM and 1768 youths with T2DM, 20.1% and 7.2% developed DR over a median follow-up time of 3.2 and 3.1 years, respectively. Survival curves demonstrated that youths with T1DM developed DR faster than youths with T2DM (P < 0.0001). For every 1-point increase in HbA1c, the hazard for DR increased by 20% (HR = 1.20; 95% CI 1.06-1.35) and 30% (HR = 1.30; 95% CI 1.08-1.56) among youths with T1DM and T2DM, respectively. Current guidelines suggest that ophthalmic screening begin 3 to 5 years after initial diabetes mellitus diagnosis, at which point in our study, >18% of youths with T1DM had already received ≥1 DR diagnosis.Youths with T1DM or T2DM exhibit a considerable risk for DR and should undergo regular screenings by eye-care professionals to ensure timely DR diagnosis and limit progression to vision-threatening disease.
View details for DOI 10.1016/j.ophtha.2016.10.031
View details for PubMedID 27914837
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Patient Attitudes Toward Telemedicine for Diabetic Retinopathy.
Telemedicine journal and e-health
2017; 23 (3): 205-212
Abstract
Diabetic retinopathy (DR) is the leading cause of new-onset blindness in adults. Telemedicine is a validated, cost-effective method to improve monitoring. However, little is known of patients' attitudes toward telemedicine for DR. Our study explores factors that influence patients' attitudes toward participating in telemedicine.Ninety seven participants in a university and the Veterans Administration setting completed a survey. Only people with diabetes mellitus (DM) were included. The main outcome was willingness to participate in telemedicine. The other outcomes were perceived convenience and impact on the patient-physician relationship. Participants reported demographic information, comorbidities, and access to healthcare. Analysis was performed with t-tests and multivariable logistic regression.Demographic factors were not associated with the outcomes (all p > 0.05). Patients had decreased odds of willingness if they valued the patient-physician relationship (adjusted odds ratio [OR] = 0.08, confidence interval [CI] = 0.02-0.35, p = 0.001) or had a longer duration of diabetes (adjusted OR = 0.93, CI = 0.88-0.99, p = 0.02). Patients had increased odds of willingness if they perceived increased convenience (adjusted OR = 8.10, CI = 1.77-36.97, p = 0.01) or had more systemic comorbidities (adjusted OR = 1.85, CI = 1.10-3.11, p = 0.02).It is critical to understand the attitudes of people with DM where telemedicine shows promise for disease management and end-organ damage prevention. Patients' attitudes are influenced by their health and perceptions, but not by their demographics. Receptive patients focus on convenience, whereas unreceptive patients strongly value their patient-physician relationships or have long-standing DM. Telemedicine monitoring should be designed for people who are in need and receptive to telemedicine.
View details for DOI 10.1089/tmj.2016.0108
View details for PubMedID 27336678
View details for PubMedCentralID PMC5359684
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The relation between exercise and glaucoma in a South Korean population-based sample
PLOS ONE
2017; 12 (2)
Abstract
To investigate the association between exercise and glaucoma in a South Korean population-based sample.Population-based, cross-sectional study.A total of 11,246 subjects, 40 years and older who underwent health care assessment as part of the 2008-2011 Korean National Health and Nutrition Examination Survey.Variables regarding the duration (total minutes per week), frequency (days per week), and intensity of exercise (vigorous, moderate exercise and walking) as well as glaucoma prevalence were ascertained for 11,246 survey participants. Demographic, comorbidity, and health-related behavior information was obtained via interview. Multivariable logistic regression analyses were performed to determine the association between the exercise-related parameters and odds of a glaucoma diagnosis.Glaucoma defined by International Society for Geographical and Epidemiological Ophthalmology criteria.Overall, 336 (2.7%) subjects met diagnostic criteria for glaucomatous disease. After adjustment for potential confounding variables, subjects engaged in vigorous exercise 7 days per week had higher odds of having glaucoma compared with those exercising 3 days per week (Odds Ratio [OR] 3.33, 95% confidence interval [CI] 1.16-9.54). High intensity of exercise, as categorized by the guidelines of the American College of Sports Medicine (ACSM), was also associated with greater glaucoma prevalence compared with moderate intensity of exercise (OR 1.55, 95% CI 1.03-2.33). There was no association between other exercise parameters including frequency of moderate exercise, walking, muscle strength exercise, flexibility training, or total minutes of exercise per week, and the prevalence of glaucoma. In sub-analyses stratifying by gender, the association between frequency of vigorous exercise 7 days per week and glaucoma diagnosis remained significant in men (OR 6.05, 95% CI 1.67-21.94) but not in women (OR 0.96 95% CI: 0.23-3.97). A U-shaped association between exercise intensity and glaucoma prevalence was noted in men (OR 1.71, 95% CI 1.09-2.69 for low intensity versus moderate intensity; OR 2.19, 95% CI 1.25-3.85 for high intensity versus moderate intensity).In a South Korean population sample, daily vigorous exercise was associated with higher glaucoma prevalence. In addition, the intensity of exercise was positively associated with glaucoma diagnosis in men but not women.
View details for DOI 10.1371/journal.pone.0171441
View details for PubMedID 28187143
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Fungal Endophthalmitis Associated With DSAEK and Thermal Sclerostomy
OPHTHALMIC SURGERY LASERS & IMAGING RETINA
2016; 47 (7): 691-693
Abstract
An 85-year-old man with remote thermal sclerostomy and Descemet's stripping automated endothelial keratoplasty (DSAEK) in the right eye presented urgently for pain and blurred vision in that eye. Examination revealed bleb purulence and vitreous cellular aggregates concerning for endophthalmitis. Microscopy of a vitreous sample revealed yeast and pseudohyphae. He developed corneal infiltrates consistent with fungal infection. Therapy included topical, intravitreal, and systemic antifungals voriconazole and amphotericin. Fungal pathogens have very rarely been reported to cause bleb-associated endophthalmitis and should be considered in addition to bacterial pathogens. Vitreous aspiration should be performed in all cases of bleb-related endophthalmitis and include fungal studies. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:691-693.].
View details for DOI 10.3928/23258160-20160707-15
View details for Web of Science ID 000393098300015
View details for PubMedID 27434905
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Oral Contraceptive Use and Prevalence of Self-Reported Glaucoma or Ocular Hypertension in the United States
OPHTHALMOLOGY
2016; 123 (4): 729-736
Abstract
To investigate the association between oral contraceptive (OC) use and glaucoma prevalence in the United States.Cross-sectional study.A total of 3406 female participants, aged 40 years or older, from the 2005 to 2008 National Health and Nutrition Examination Survey, who reported a presence or absence of glaucoma or ocular hypertension completed both the vision and the reproductive health questionnaires and underwent eye examinations.Multivariate regression analysis was used to assess the correlation between OC use and self-reported glaucoma or ocular hypertension (n = 231 cases), controlling for potential confounders, including age, ethnicity, systemic comorbidities such as hypertension and stroke, ocular diseases such as cataract and diabetic retinopathy, and reproductive health factors, including age at menopause, age at menarche, history of hormone replacement therapy, and gynecological surgical history.The outcome variable was self-reported glaucoma or ocular hypertension.After adjusting for confounders, those with ≥3 years of OC use had greater odds (odds ratio, 1.94; 95% confidence interval, 1.22-3.07) of self-reported glaucoma or ocular hypertension. Other factors associated with higher glaucoma or ocular hypertension prevalence included older age, African American race, and later age at menarche.Oral contraceptive use may be associated with increased risk of self-reported glaucoma or ocular hypertension.
View details for DOI 10.1016/j.ophtha.2015.11.029
View details for Web of Science ID 000372718300016
View details for PubMedCentralID PMC4857187
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Oral Contraceptive Use and Prevalence of Self-Reported Glaucoma or Ocular Hypertension in the United States.
Ophthalmology
2016; 123 (4): 729-36
Abstract
To investigate the association between oral contraceptive (OC) use and glaucoma prevalence in the United States.Cross-sectional study.A total of 3406 female participants, aged 40 years or older, from the 2005 to 2008 National Health and Nutrition Examination Survey, who reported a presence or absence of glaucoma or ocular hypertension completed both the vision and the reproductive health questionnaires and underwent eye examinations.Multivariate regression analysis was used to assess the correlation between OC use and self-reported glaucoma or ocular hypertension (n = 231 cases), controlling for potential confounders, including age, ethnicity, systemic comorbidities such as hypertension and stroke, ocular diseases such as cataract and diabetic retinopathy, and reproductive health factors, including age at menopause, age at menarche, history of hormone replacement therapy, and gynecological surgical history.The outcome variable was self-reported glaucoma or ocular hypertension.After adjusting for confounders, those with ≥3 years of OC use had greater odds (odds ratio, 1.94; 95% confidence interval, 1.22-3.07) of self-reported glaucoma or ocular hypertension. Other factors associated with higher glaucoma or ocular hypertension prevalence included older age, African American race, and later age at menarche.Oral contraceptive use may be associated with increased risk of self-reported glaucoma or ocular hypertension.
View details for DOI 10.1016/j.ophtha.2015.11.029
View details for PubMedID 26948305
View details for PubMedCentralID PMC4857187
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Hospitalization after Cataract Surgery in a Nationwide Managed-Care Population
PLOS ONE
2016; 11 (2)
Abstract
Little is known regarding the extent by which patients undergoing outpatient cataract surgery are at risk for postoperative hospitalization. We sought to determine the percentage of patients undergoing cataract surgery who were subsequently hospitalized, the patient characteristics associated with postoperative hospitalization, and the reasons for hospitalization.We identified all beneficiaries of a large U.S. managed care network age ≥40 years old who underwent ≥1 cataract surgery from 2001-2011. All enrollees who required inpatient hospitalization within 7, 14, 30, and 90 days following initial cataract surgery and the reasons for hospitalization were determined. Logistic regression was performed to assess factors that significantly impacted the odds of requiring postoperative hospitalization.Among the 64,981 patients who underwent cataract surgery, rates of hospitalization within 7, 14, 30, and 90 days were 0.3%, 0.5%, 1.3% and 4.2%, respectively. Among the 10,674 patients who had no major preexisting medical comorbidities, 0.1% were hospitalized within 7 days. The odds of hospitalization increased by 35% (OR = 1.35 [CI, 1.23-1.48]) with the presence of each additional comorbidity and by 14% with each additional hospitalization in the 3 years prior to cataract surgery (OR = 1.14 [CI, 1.10-1,18]). Those who were hospitalized in the 30 days prior to cataract surgery had 524% increased odds of being hospitalized within 7 days after cataract surgery (OR = 6.24, [CI, 3.37-11.57]) compared to those with no record of preoperative hospitalization. Postoperative hospitalizations were most commonly due to cardiovascular conditions, comprising over 25% of primary diagnoses associated with hospitalization.The risk of hospitalization after cataract surgery is low, and is very low among those with no major preexisting medical comorbidities. Opportunities may exist to limit comprehensive preoperative evaluation and testing to those who have serious pre-existing medical comorbidities.
View details for DOI 10.1371/journal.pone.0149819
View details for Web of Science ID 000371276100158
View details for PubMedID 26901594
View details for PubMedCentralID PMC4762614
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Hypothyroidism and Glaucoma in The United States
PLOS ONE
2015; 10 (7)
Abstract
To investigate the association between hypothyroidism and glaucomatous disease.This cross-sectional study included all subjects above the age of 40 years from two nationwide surveys: the 2008 National Health Interview Survey (NHIS) as well as the 2007 and 2008 National Health and Nutrition Examination Survey (NHANES). The presence or absence of glaucoma, thyroid disease and other demographic and health-related information including comorbidities was ascertained via interview. Blood samples were collected from NHANES subjects and analyzed for thyrotropin (TSH).A total of 13,599 and 3,839 NHIS and NHANES participants respectively were analyzed to assess for a possible relationship between self-reported glaucoma, and self-reported hypothyroidism as well as self-reported thyroid disease. The unadjusted odds ratio (OR) for NHIS showed a significant association between self-reported glaucoma and self-reported hypothyroidism (OR 1.46, 95% confidence interval [CI] 1.07-1.99). Multivariate logistic regression analysis adjusted for age, gender, race, comorbidities, and health-related behavior, however, showed no association between self-reported glaucoma and hypothyroidism or thyroid disease in both surveys (OR 1.60, 95%CI 0.87-2.95 for NHIS; OR 1.05, 95%CI 0.59-1.88 for NHANES).A previously reported association between hypothyroidism and glaucomatous disease was not confirmed in two large U.S. health survey populations. While such an association was noted in the univariate analysis for the NHIS survey, such a relationship was not found in the multivariate analysis after adjustment for potential confounding variables.
View details for DOI 10.1371/journal.pone.0133688
View details for Web of Science ID 000358838400049
View details for PubMedID 26230664
View details for PubMedCentralID PMC4521841
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Self-reported Calcium Supplementation and Age-Related Macular Degeneration
JAMA OPHTHALMOLOGY
2015; 133 (7): 746-754
Abstract
Despite widespread use of calcium supplementation among elderly people, little is known about the association between such consumption and the prevalence of age-related macular degeneration (AMD) in the United States.To investigate the association between self-reported supplementary calcium consumption and the prevalence of AMD in a representative US sample.This cross-sectional study included 3191 participants 40 years and older in the 2007-2008 National Health and Nutrition Examination Survey (NHANES) who were evaluated for the presence or absence of AMD by fundus photography. Participants were interviewed regarding use of dietary supplements and antacids during the 30-day period preceding enrollment. Self-reported supplementary intake of calcium was aggregated and divided into quintiles. Fundus photographs were graded for the presence or absence of AMD. Information regarding demographics, comorbidities, and health-related behaviors was obtained via interview. Multivariable logistic regression models were created to determine the odds of an AMD diagnosis among participants in each quintile of self-reported calcium vs participants not self-reporting supplementary calcium consumption after adjusting for confounders.Self-reported use of calcium supplements.Presence or absence of AMD by fundus photography.A total of 248 participants (7.8%) were diagnosed with AMD. Mean ages were 67.2 years for those with AMD and 55.8 for those without AMD. After adjustment for potential confounding variables, study participants who self-reported consumption of more than 800 mg/d of supplementary calcium were found to have higher odds of an AMD diagnosis based on fundus photography evaluation compared with those not self-reporting supplementary calcium consumption (odds ratio, 1.85; 95% CI, 1.25-2.75). The association between self-reported supplementary calcium intake and AMD was stronger in older than younger individuals (odds ratio, 2.63; 95% CI, 1.52-4.54). A clear dose-response association between the quintiles of self-reported supplementary calcium intake and AMD was not established.Self-reported supplementary calcium consumption is associated with increased prevalence of AMD, with the findings suggesting a threshold rather than a dose-response relationship. The stronger association in older individuals may be due to relatively longer duration of calcium supplementation in older individuals.
View details for DOI 10.1001/jamaophthalmol.2015.0514
View details for Web of Science ID 000357823100021
View details for PubMedID 25856252
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The Impact of Central Corneal Thickness on the Risk for Glaucoma in a Large Multiethnic Population
JOURNAL OF GLAUCOMA
2014; 23 (9): 606-612
Abstract
To investigate the relationship between central corneal thickness (CCT) and demographics, and determine whether CCT may be a substantial mediator of the relationships between glaucoma and its demographic risk factors.This cross-sectional study included patients in the Kaiser Permanente Northern California health plan from January 1, 2007 to December 31, 2011 who were 40 years and older and had a documented CCT measurement (N=81,082). Those with any cornea-related diagnoses or a history of corneal refractive surgery were excluded. Demographic characteristics, including age, sex, and race/ethnicity, as well as clinical information including glaucoma-related diagnosis, diabetic status, CCT, and intraocular pressure were gathered from the electronic medical record.Multivariate linear regression analysis indicated that female sex, increased age, and black race were significantly associated with thinner corneas. A subgroup analysis among Asians revealed that Chinese, Japanese, and Koreans had corneas 6 to 13 µm thicker than South and Southeast Asians, Filipinos, and Pacific Islanders for each diagnosis (P<0.001). In our population, 24.5% (N=19878) had some form of open-angle glaucoma; 21.9% (N=17,779) did not have any glaucoma-related diagnosis. Variation in CCT accounted for only 6.68% [95% confidence interval (CI), 6.14%-7.24%] of the increased risk of open-angle glaucoma seen with increasing age, but explained as much as 29.4% (95% CI, 27.0%-32.6%) of the increased risk of glaucoma seen among blacks, and 29.5% (95% CI, 23.5%-37.0%) of the increased risk of glaucoma seen among Hispanics.CCT seems to explain a substantial portion of the increased risk of glaucoma seen among blacks and Hispanics.
View details for DOI 10.1097/IJG.0000000000000088
View details for Web of Science ID 000345865000005
View details for PubMedID 25055208
View details for PubMedCentralID PMC4250426
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Association Between Serum Ferritin and Glaucoma in the South Korean Population
JAMA OPHTHALMOLOGY
2014; 132 (12): 1414-1420
Abstract
Evidence suggests that altered iron metabolism may be associated with oxidative damage to several organ systems, including the eye. Supplementary iron consumption is also associated with greater odds of self-reported glaucoma.To investigate the association between serum ferritin level and the likelihood of a glaucoma diagnosis in a cross-sectional, population-based study.Data were collected from 17,476 participants in the first and second years of the Fifth Korea National Health and Nutrition Examination Survey, a cross-sectional study of the South Korean population conducted from January 1, 2010, through December 31, 2011. Data pertaining to the serum ferritin level were aggregated and divided into quartiles. Demographic, comorbidity, and health-related behavior information was obtained via interview.The presence or absence of glaucoma. The definition of glaucoma was based on criteria established by the International Society of Geographical and Epidemiological Ophthalmology.Participants whose serum ferritin level was greater than 61 ng/mL (to convert to picomoles per liter, multiply by 2.247) had significantly higher odds of a glaucoma diagnosis when compared with those with a level less than 31 ng/mL, after adjustment for potential confounders (ferritin levels of 31-61 ng/mL: odds ratio [OR], 1.17; 95% CI, 0.84-1.62; ferritin levels of 62-112 ng/mL: OR, 1.60; 95% CI, 1.16-2.20; and ferritin levels of 113-3018 ng/mL: OR, 1.89; 95% CI, 1.32-2.72).Our study reveals that a higher serum ferritin level was associated with greater odds of glaucoma in a representative sample of the South Korean population, even at levels normally observed in the general population. This novel finding may help elucidate the pathogenesis and lead to novel therapeutic approaches for glaucomatous disease.
View details for DOI 10.1001/jamaophthalmol.2014.2876
View details for Web of Science ID 000346176400006
View details for PubMedID 25171442
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Racial Disparities in Uncorrected and Undercorrected Refractive Error in the United States
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE
2014; 55 (10)
Abstract
To identify risk factors for inadequately corrected refractive error in the United States.This cross-sectional study included 12,758 participants 12 years of age and older from the 2005 to 2008 National Health and Nutrition Examination Survey. The primary outcome was the proportion of individuals with inadequate refractive correction for whom refractive correction would result in a visual acuity of 20/40 or better. The primary predictor was race/ethnicity. Secondary predictors included age, sex, annual household income, education, insurance, type of refractive error, current corrective lens use, presenting and best corrected visual acuity, cataract surgery, glaucoma, and age-related macular degeneration.Overall, 50.6% of subjects had a refractive error which was correctable to 20/40 or better with refraction. The percentage of subjects with correctable refractive error who were inadequately corrected was 11.7%. Odds of inadequate refractive correction were significantly greater in Mexican Americans and non-Hispanic blacks than in their non-Hispanic white counterparts in all age groups, with the greatest disparity in the 12- to 19-year-old group. Other risk factors associated with inadequate refractive correction in adults but not in teenagers included low annual household income, low education, and lack of health insurance.Racial disparities in refractive error correction were most pronounced in those under 20 years of age, as well as in adults with low annual household income, low education level, and lack of health insurance. Targeted efforts to provide culturally appropriate education, accessible vision screening, appropriate refractive correction, and routine follow-up to these medically underserved groups should be pursued as a public health strategy.
View details for DOI 10.1167/iovs.13-12662
View details for Web of Science ID 000344730500049
View details for PubMedID 25249602
View details for PubMedCentralID PMC4215743
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Intraocular pressure reduction after cataract extraction in normal eyes: Influence of ethnicity and anterior segment parameters - response
CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY
2014; 42 (5): 508-508
View details for Web of Science ID 000339952400022
View details for PubMedID 24304665
View details for PubMedCentralID PMC4004723
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Age-related macular degeneration and protective effect of HMG Co-A reductase inhibitors (statins): results from the National Health and Nutrition Examination Survey 2005-2008
EYE
2014; 28 (4): 472-480
Abstract
To determine the association of hydroxymethylglutarylcoenzyme A (HMG Co-A) reductase inhibitor (statin) use with the prevalence of age-related macular degeneration (AMD).This cross-sectional study included 5604 participants in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2008, ≥ 40 years of age, who were ascertained with regard to the diagnosis of AMD, the use of statins, and comorbidities and health-related behaviors such as smoking.The mean age of participants denying or confirming a history of AMD was 68 (SEM 0.90) and 55 (SEM 0.36) years, respectively. Individuals 68 years of age or older who were classified as long-term users of statins had statistically significant less self-reported AMD (odds ratio (OR) 0.64, 95% confidence interval (CI) 0.49-0.84; P=0.002), after adjusting for potential confounding variables. No significant association was found between the prevalence of AMD and statin consumption among subjects between 40 and 67 years of age (OR 1.61, 95% CI 0.85-3.03; P=0.137).Our results suggest a possible beneficial effect of statin intake for the prevention of AMD in individuals 68 years of age or older.
View details for DOI 10.1038/eye.2014.8
View details for Web of Science ID 000334360000016
View details for PubMedID 24503725
View details for PubMedCentralID PMC3983650
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Association between Visual Field Defects and Quality of Life in the United States.
Ophthalmology
2014; 121 (3): 733-740
Abstract
To investigate the association between visual field defects and quality of life in the United States population.Cross-sectional study.A total of 5186 participants in the 2005 through 2008 National Health and Nutrition Examination Survey 40 years of age and older without a self-reported history of age-related macular degeneration or prior refractive surgery who had undergone frequency doubling technology perimetric testing.Frequency doubling technology perimetry was performed in both eyes. Results from the better eye were used to categorize subjects as normal or having mild, moderate, or severe visual field loss. Subjects completed surveys about their visual and physical functioning ability.Disability pertaining to 6 vision-related activities, 2 visual function questions, and 5 physical functioning domains.Eighty-one percent of subjects had normal visual fields and 10%, 7%, and 2% demonstrated mild, moderate, and severe visual field defects, respectively. Subjects with greater severity of visual field defects had greater difficulty with vision-related activities. Subjects with severe visual field defects demonstrated the greatest odds of difficulty with all 6 activities. The 2 activities impacted most adversely were daytime driving in familiar places (odds ratio [OR], 12.4; 95% confidence interval [CI], 6.1-25.1) and noticing objects off to the side when walking (OR, 7.7; 95% CI, 4.7-12.7). Subjects with severe visual field defects had greater odds of worrying about eyesight (OR, 3.4; 95% CI, 2.0-5.8) and being limited by vision in the time spent on daily activities (OR, 5.1; 95% CI, 3.0-8.5). Subjects with severe visual field defects demonstrated the greatest odds of difficulty with 3 physical function domains, including activities of daily living (OR, 2.45; 95% CI, 1.37-4.38), instrumental activities of daily living (OR, 2.45; 95% CI, 1.37-4.38), as well as leisure and social activities (OR, 3.29; 95% CI, 1.87-5.77).Greater severity of visual field abnormality was associated with significantly greater odds of disability with vision-related function and physical function. These findings support the necessity of routine screening to find those who may benefit from therapy to prevent progressive glaucomatous vision loss.
View details for DOI 10.1016/j.ophtha.2013.09.043
View details for PubMedID 24342021
View details for PubMedCentralID PMC3943627
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Glaucoma Prevalence and the Intake of Iron and Calcium in a Population-based Study
CURRENT EYE RESEARCH
2013; 38 (10): 1049-1056
Abstract
Previous work has suggested a possible relationship between nutritional supplementation with iron and calcium, and a diagnosis of glaucoma. The present study investigates the association between dietary and total calcium and iron consumption with a diagnosis of glaucoma.This cross-sectional study included 6316 participants in the National Health and Nutrition Examination Survey (NHANES 2005-2008), age 40 or older, who participated in the dietary interview portion of NHANES. Intake of the oxidants calcium and iron was assessed using the National Cancer Institute Method of analyzing data from multiple 24-h dietary recall interviews. Participants self-reported the presence or absence of glaucoma as well as information pertaining to demographics, health-related behaviors and comorbidities.Adjusted odds of glaucoma increased with higher total consumption of calcium (p-trend <0.0001) and iron (p-trend <0.0001). Adjusted odds of glaucoma was significantly greater for total calcium intake at the third (OR 1.58, 95% CI 1.32-1.89) and fourth quintile levels (OR 1.21, 95% CI 1.03-1.43) and for total iron intake at the fourth (OR 2.95, 95% CI 2.52-3.45) and fifth quintile levels (OR 1.58, 95% CI 1.36-1.83), compared with the corresponding lowest quintile of intake. In contrast, a tendency towards decreased odds of glaucoma was observed with increasing dietary calcium (p-trend = 0.0008) and iron intake (p-trend = 0.0022).While greater total consumption of calcium and iron may be associated with increased odds of glaucoma, dietary rather than supplemental consumption of these oxidants was found to be associated with lower odds of glaucoma. Additional research is necessary to elucidate the relationship between glaucoma and oxidant intake from foods versus supplements, and to prospectively evaluate whether oxidant intake is related to glaucoma incidence and progression.
View details for DOI 10.3109/02713683.2013.803124
View details for Web of Science ID 000323719500006
View details for PubMedID 23790096
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Ethnic differences in intraocular pressure reduction and changes in anterior segment biometric parameters following cataract surgery by phacoemulsification
CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY
2013; 41 (5): 442-449
Abstract
To determine the association between ethnicity and changes in intraocular pressure and anterior segment biometric parameters following cataract surgery by phacoemulsification in nonglaucomatous subjects.Prospective clinical cohort study.Caucasian and Asian subjects.Customized software was used to calculate parameters from anterior segment optical coherence tomography images obtained preoperatively and at 3 months following cataract surgery by phacoemulsification. The percentage changes in intraocular pressure and anterior segment biometric parameters following cataract surgery by phacoemulsification were modelled as a function of ethnicity using linear mixed-effects regression, a likelihood ratio test function that adjusted for age, sex and the use of both eyes in the same subject, to determine the association between ethnicity and postoperative outcomes.Intraocular pressure, angle opening distance, anterior chamber depth, anterior chamber volume, and angle recess area.Fifty Asian and 23 Caucasian nonglaucomatous eyes were analysed. Postoperative decrease in intraocular pressure and increases in angle opening distance, anterior chamber depth, anterior chamber volume and angle recess area were observed within each ethnic group (P < 0.005). The percent changes in intraocular pressure, angle opening distance, anterior chamber depth, anterior chamber volume and angle recess area did not differ between ethnic groups (P > 0.05).In this study, regardless of ethnic classification, subjects who received cataract surgery by phacoemulsification experienced a significant postoperative decrease in intraocular pressure and increases in angle opening distance, anterior chamber depth, anterior chamber volume and angle recess area. The percent changes in postoperative outcomes did not differ significantly by ethnicity.
View details for DOI 10.1111/ceo.12032
View details for Web of Science ID 000320928600004
View details for PubMedID 23146132
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Glaucoma and vitamins A, C, and E supplement intake and serum levels in a population-based sample of the United States
EYE
2013; 27 (4): 487-494
Abstract
To investigate the potential association between glaucoma prevalence and supplemental intake, as well as serum levels of vitamins A, C and E.This cross-sectional study included 2912 participants in the 2005-2006 National Health and Nutrition Examination Survey, age ≥40 years, who self-reported a presence or absence of glaucoma. Participants were interviewed regarding the use of dietary supplements during the preceding 30-day period. Participants also underwent serum measurements of vitamins A, C, and E (both alpha- and gamma-tocopherol). Information on the primary outcome measure, presence or absence of glaucoma, as well as demographic information, comorbidities and health-related behaviors, was assessed via interview.Multivariate odds ratios for self-reported glaucoma, comparing the highest quartile of consumption to no consumption, and adjusted for potential confounding variables were 0.48 (95% confidence interval (CI) 0.13-1.82) for vitamin A, 0.47 (95% CI 0.23-0.97) for vitamin C, and 2.59 (95% CI 0.89-7.56) for vitamin E. Adjusted odds ratios for self-reported glaucoma comparing the highest vs lowest quintiles of vitamin serum levels were 1.44 (95% CI 0.79-2.62) for vitamin A, 0.94 (95% CI 0.42-2.11) for vitamin C, 1.40 (95% CI 0.70-2.81) for alpha-tocopherol, and 0.64 (95% CI 0.24-1.70) for gamma-tocopherol.Neither supplementary consumption with nor serum levels of vitamins A and E were found to be associated with glaucoma prevalence. While low- and high-dose supplementary consumption of vitamin C was found to be associated with decreased odds of glaucoma, serum levels of vitamin C did not correlate with glaucoma prevalence.
View details for DOI 10.1038/eye.2013.10
View details for Web of Science ID 000317594000005
View details for PubMedID 23429409
View details for PubMedCentralID PMC3626010
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Association between Myopia and Glaucoma in the United States Population
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE
2013; 54 (1): 830-835
Abstract
To investigate the association between myopia and the prevalence of glaucoma.This cross-sectional study included 5277 participants from the 2005 to 2008 National Health and Nutrition Examination Survey, greater than or equal to 40 years old, without history of cataract or refractive surgery, who underwent auto-refraction measurement. The predictor was refractive status; emmetropia (-0.99 to +0.99 diopters [D]), mild myopia (-1.00 to -2.99 D), moderate myopia (-3.00 to -5.99 D), severe myopia (> -6.00 D), and hyperopia (> 1.00 D). The outcomes were self-reported glaucoma, vertical cup-to-disc ratio and visual field defects as found on frequency doubling technology (FDT) testingOdds of self-reported glaucoma were not significantly increased in mild (odds ratio [OR] 0.90, confidence interval [CI] 0.56-1.45), moderate (OR 1.40, CI 0.62-3.16), or severe (OR 0.26, CI 0.08-0.80) myopes compared with emmetropes. Odds of vertical cup-to-disc ratio greater than or equal to 0.7 were not significantly increased in mild (OR 0.84, CI 0.31-2.25), moderate (OR 0.37, CI 0.04-3.57), or severe (OR 0.85, CI 0.09-8.42) myopes compared with emmetropes. Odds of any visual field defects were significantly increased in mild (OR 2.02, CI 1.28-3.19), moderate (OR 3.09, CI 1.42-6.72), and severe (OR 14.43, CI 5.13-40.61) myopes compared with emmetropes. The χ(2) test indicated a significant difference (P = 0.001) in the distribution of subjects with each category of visual field status across subjects with each refractive status; the proportion of subjects with worse visual field defects increased with worsening myopia severity.The association between myopia and visual field defects may represent an increased risk of glaucoma among myopes, and the lack of association with self-reported glaucoma may suggest a need for greater glaucoma surveillance in this population.
View details for DOI 10.1167/iovs.12-11158
View details for Web of Science ID 000314338400109
View details for PubMedID 23299483
View details for PubMedCentralID PMC3562121
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Prevalence and Predictors of Depression Among Participants With Glaucoma in a Nationally Representative Population Sample
AMERICAN JOURNAL OF OPHTHALMOLOGY
2012; 154 (3): 436-444
Abstract
To investigate the prevalence of and risk factors for depression among participants with glaucoma and the predictive value of glaucoma for depression.Cross-sectional study.This study included 6760 participants in the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2008, aged ≥40 years, who reported a presence or absence of glaucoma. Demographic and disease-related information was obtained by interview. Self-reported measures of vision were ascertained via items from the Visual Function Questionnaire (VFQ-25). Participants underwent visual acuity examination, fundus photography, and visual field testing with screening frequency-doubling technology (FDT N-30-5). The main outcome was presence of depression, as determined by a score ≥10 on the Patient Health Questionnaire-9 (PHQ-9).Prevalence of depression among participants with and without glaucoma was 10.9% (SEM 2.2%) and 6.9% (SEM 0.62%), respectively. While the presence of glaucoma was significantly associated with depression after adjustment for demographic factors (OR 1.80, 95% CI 1.16-2.79), this association was not significant after adjustment for self-reported general health condition (OR 1.35, 95% CI 0.822-2.23). Among participants with glaucoma, objective measures of glaucoma severity were not significant predictors for depression. However, several self-reported measures of visual function were significantly associated with depression.Glaucoma is a significant predictor of depression after adjustment for demographic factors and multiple comorbidities, but not after adjustment for self-reported general health condition. Among participants with glaucoma, self-reported measures of vision were significant risk factors for depression, whereas objective measures of vision were not.
View details for DOI 10.1016/j.ajo.2012.03.039
View details for Web of Science ID 000308115600005
View details for PubMedID 22789562
View details for PubMedCentralID PMC3422443
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The Association between Glaucoma Prevalence and Supplementation with the Oxidants Calcium and Iron
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE
2012; 53 (2): 725-731
Abstract
To investigate the relationship between supplementary consumption of the oxidants calcium and iron and the prevalence of glaucoma.This cross-sectional study included 3833 participants in the National Health and Nutrition Examination Survey (NHANES) for 2007 and 2008, ≥ 40 years of age, who reported a presence or absence of glaucoma. Participants were interviewed regarding the use of dietary supplements and antacids during the preceding 30-day period. Data pertaining to the supplementary intake of calcium and iron was aggregated and divided into quintiles. Information regarding the presence or absence of glaucoma and demographics, comorbidities, and health-related behavior was obtained via interview.Participants who consumed ≥ 800 mg/d of supplementary calcium or ≥ 18 mg/d of supplementary iron had significantly higher odds of having been diagnosed with glaucoma than did those who had not consumed supplementary calcium or iron, after adjustment for potential confounders (odds ratio [OR] 2.44, 95% confidence interval [CI] 1.25-4.76 for calcium; OR 3.80, 95% CI 1.79-8.06 for iron). Concurrent consumption of both calcium and iron above these levels was associated with still greater odds of having been diagnosed with glaucoma (OR 7.24, 95% CI 2.42-21.62). A clear dose-response relationship between quintiles of supplementary calcium or iron intake and glaucoma prevalence was not found.These results suggest that there may be a threshold intake of iron and calcium above which there is an increased risk of development of glaucoma. Prospective longitudinal studies are needed, to assess whether oxidant intake is a risk factor for development and progression of glaucoma.
View details for DOI 10.1167/iovs.11-9038
View details for Web of Science ID 000302788600024
View details for PubMedID 22247455
View details for PubMedCentralID PMC3317417
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Asian Americans and Obesity in California: A Protective Effect of Biculturalism
JOURNAL OF IMMIGRANT AND MINORITY HEALTH
2011; 13 (2): 276-283
Abstract
Prior studies comparing US-born and foreign-born Asian Americans have shown that birth in the US conveys greater risk of obesity. Our study investigates whether retention of Asian culture might be protective for obesity despite acculturation to US lifestyle. We classified self-identified Asian American respondents of the California Health Interview Survey as traditional, bicultural, and acculturated using nativity and language proficiency in English and Asian language. We then examined the association of acculturation with overweight/obesity (BMI ≥ 25 kg/m²) in a multivariate regression model. Acculturated respondents had higher adjusted odds of being overweight/obese than bicultural respondents (2.13 [1.40-3.23] for men, 3.28 [2.14-5.04] for women), but bicultural respondents had similar odds of being overweight/obese as traditional respondents (.98 [.69-1.41] for men, .72 [.50-1.05] for women). Among the bicultural, second and first generation respondents were equally likely to be overweight/obese. Biculturalism in Asian Americans as measured by Asian language retention appears protective against obesity. Further research is needed to understand the mechanisms underlying this association.
View details for DOI 10.1007/s10903-010-9426-5
View details for Web of Science ID 000288256800012
View details for PubMedID 21153765
View details for PubMedCentralID PMC3056137
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Rapid deletional peripheral CD8 T cell tolerance induced by allogeneic bone marrow: Role of donor class II MHC and B cells
JOURNAL OF IMMUNOLOGY
2008; 181 (6): 4371-4380
Abstract
Mixed chimerism and donor-specific tolerance are achieved in mice receiving 3 Gy of total body irradiation and anti-CD154 mAb followed by allogeneic bone marrow (BM) transplantation. In this model, recipient CD4 cells are critically important for CD8 tolerance. To evaluate the role of CD4 cells recognizing donor MHC class II directly, we used class II-deficient donor marrow and were not able to achieve chimerism unless recipient CD8 cells were depleted, indicating that directly alloreactive CD4 cells were necessary for CD8 tolerance. To identify the MHC class II(+) donor cells promoting this tolerance, we used donor BM lacking certain cell populations or used positively selected cell populations. Neither donor CD11c(+) dendritic cells, B cells, T cells, nor donor-derived IL-10 were critical for chimerism induction. Purified donor B cells induced early chimerism and donor-specific cell-mediated lympholysis tolerance in both strain combinations tested. In contrast, positively selected CD11b(+) monocytes/myeloid cells did not induce early chimerism in either strain combination. Donor cell preparations containing B cells were able to induce early deletion of donor-reactive TCR-transgenic 2C CD8 T cells, whereas those devoid of B cells had reduced activity. Thus, induction of stable mixed chimerism depends on the expression of MHC class II on the donor marrow, but no requisite donor cell lineage was identified. Donor BM-derived B cells induced early chimerism, donor-specific cell-mediated lympholysis tolerance, and deletion of donor-reactive CD8 T cells, whereas CD11b(+) cells did not. Thus, BM-derived B cells are potent tolerogenic APCs for alloreactive CD8 cells.
View details for Web of Science ID 000259250400076
View details for PubMedID 18768896
View details for PubMedCentralID PMC2628539
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Protection against lethal Aspergillus fumigatus infection in mice by allogeneic myeloid progenitors is not major histocompatibility complex restricted
45th Annual Meeting and Exhibition of the American-Society-of-Hematology
UNIV CHICAGO PRESS. 2005: 1666–71
Abstract
Invasive fungal infections are a leading cause of morbidity and mortality after myelotoxic chemotherapy or radiation exposure. The resulting depletion of myeloid precursors under these conditions appears to be the factor that limits approaches to accelerate immune reconstitution. In a murine model of myeloablation after radiation exposure, we demonstrated that highly purified common myeloid and granulocyte-monocyte progenitors (CMPs/GMPs) accelerated myeloid recovery and, thus, enhanced innate immunity as measured by survival after a lethal challenge with Aspergillus fumigatus. Of greatest significance was the demonstration that the protection afforded by CMPs/GMPs was not major histocompatibility complex restricted. Furthermore, the effect of CMP/GMP cellular therapy was additive with that of liposomal amphotericin B treatment. These observations greatly expand the potential donor pool and, thus, the clinical utility of CMP/GMP cellular therapy in patients with myeloid depletion.
View details for Web of Science ID 000232333000022
View details for PubMedID 16206084