- Pediatric Cardiology
Clinical Assistant Professor, Pediatrics - Cardiology
Member, Cardiovascular Institute
Board Certification: American Board of Pediatrics, Pediatric Cardiology (2022)
Residency: Stanford Health Care at Lucile Packard Children's Hospital (2013) CA
Medical Education: Vanderbilt University School of Medicine (2010) TN
Fellowship: Stanford University Pediatric Cardiology Fellowship (2016) CA
Board Certification: American Board of Pediatrics, Pediatrics (2013)
Usability of a Novel Digital Asthma Management Program
MOSBY-ELSEVIER. 2019: AB170
View details for DOI 10.1016/j.jaci.2018.12.521
View details for Web of Science ID 000457771200514
Passive Nocturnal Physiologic Monitoring Enables Early Detection of Exacerbations in Asthmatic Children: A Proof of Concept Study.
American journal of respiratory and critical care medicine
RATIONALE: Asthma management depends on prompt identification of symptoms, which challenges both patients and providers. In asthma, a misapprehension of health between exacerbations can compromise compliance. Thus, there is a need for a tool that permits objective longitudinal monitoring without increasing the burden of patient compliance.OBJECTIVES: We sought to determine whether changes in nocturnal physiology are associated with asthma symptoms in pediatric patients.METHODS: Using a contactless bed sensor, nocturnal heart rate, respiratory rate, relative stroke volume, and movement in asthmatic children 5-18 years old (n=16) were recorded. Asthma symptoms and Asthma Control Test score were reported every two weeks. Random forest model was used to identify physiologic parameters associated with asthma symptoms. Elastic net regression was used to identify variables associated with Asthma Control Test score.MEASUREMENTS AND MAIN RESULTS: The model on the full cohort performed with sensitivity of 47.2%, specificity of 96.3%, and accuracy of 87.4%; heart rate and respiratory parameters were the most important variables in this model. The model predicted asthma symptoms 35% of the time on the day prior to perception of symptoms, and 100% of the time for a select subject for which the model performed with greater sensitivity. Multivariable and bivariable analyses demonstrated significant association between heart rate and respiratory rate parameters and Asthma Control Test score.CONCLUSIONS: Nocturnal physiologic changes correlate with asthma symptoms, supporting the notion that nocturnal physiologic monitoring represents an objective diagnostic tool capable longitudinally assessing disease control and predicting asthma exacerbations in asthmatic children at home.
View details for PubMedID 29688023
Biodesign for Digital Health
DIGITAL HEALTH: SCALING HEALTHCARE TO THE WORLD
View details for DOI 10.1007/978-3-319-61446-5_16
View details for Web of Science ID 000431892700017
Accuracy of Pulse Oximeters Intended for Hypoxemic Pediatric Patients
PEDIATRIC CRITICAL CARE MEDICINE
2016; 17 (4): 315-320
Prior studies have shown inaccuracies in pulse oximetry readings at saturations less than 85%; however, no large studies have evaluated new sensors marketed for these low saturations. This study's purpose was to evaluate two sensors with claims of improved accuracy in children with saturations less than 85%.Prospective observational study.Single institution; cardiac catheterization laboratory, and operating room.Fifty patients weighing 3-20 kg with baseline saturations less than 90% undergoing surgical or catheterization procedure.Data collected included demographics, diagnosis, continuous saturations from three different pulse oximeters (Masimo LNCS [Masimo, Irvine, CA], Masimo Blue [Masimo], and Nellcor Max-I [Medtronic, Dublin, Ireland]) and up to four blood samples for co-oximetry as the gold-standard arterial oxygen saturation. Analysis included scatter plots, smoothed regression estimates of mean continuous saturation levels plotted against corresponding arterial oxygen saturation values, and Bland-Altman plots. Bland-Altman analysis indicated increasing levels of bias and variability for decreasing arterial oxygen saturation levels for all three sensors, with a statistically significant increase in mean difference observed for decreasing arterial oxygen saturation level. The Masimo Blue sensor had the lowest mean difference, SD and Bland-Altman limits in patients with saturations less than or equal to 85%. At saturation range of less than or equal to 85% and greater than 75%, 14% of the samples obtained from Masimo Blue, 24% of the readings from the Nellcor, and 31% from the Masimo Standard sensors were greater than or equal to 5% points difference. All three sensors had a further increase in these differences for arterial oxygen saturation values less than 75%.The Masimo Blue sensor has improved accuracy at saturations 75-85% versus the Nellcor and Masimo Standard sensors. The accuracy of peripheral capillary oxygen saturation of the Masimo Blue sensor was within 5% points of the arterial oxygen saturation the majority of the time. Currently, at saturations less than or equal to 85%, pulse oximetry alone should not be relied on in making clinical decisions.
View details for DOI 10.1097/PCC.0000000000000660
View details for Web of Science ID 000373211600006
Diagnosis and Management of Pediatric Brugada Syndrome: A Survey of Pediatric Electrophysiologists
PACE-PACING AND CLINICAL ELECTROPHYSIOLOGY
2014; 37 (5): 638-642
Brugada syndrome (BrS) can be difficult to diagnose and treat, especially in the young patient. As there is currently no consensus on the evaluation and treatment of BrS in the pediatric population, we sought to describe the current practice for the diagnosis and treatment of BrS among pediatric electrophysiologists.A web-based survey was distributed to 204 physician members (MDs) of The Pediatric and Adult Congenital Electrophysiology Society (PACES). Practice characteristics, BrS patient attributes, and diagnostic and therapeutic preferences were collected.Responses were obtained from 83 pediatric electrophysiologists. The most common initial presentation was family history. There is a large variation in testing, particularly in the use of electrophysiology (EP) studies, drug challenge testing, and genetic testing. Despite limited treatment options, there is only consensus in the therapeutic approach to the pediatric patient with symptomatic BrS with 97% of physicians recommending an implantable cardioverter defibrillator (ICD). In the asymptomatic patient, a wide variation in therapy was seen with only 27% of physicians recommending an ICD CONCLUSIONS: Significant practice variation exists among pediatric electrophysiologists with deviation from accepted diagnostic and therapeutic practices for adult BrS patients. Further studies are necessary to establish best practice guidelines for BrS in the pediatric EP community.
View details for DOI 10.1111/pace.12346
View details for Web of Science ID 000334863000016
View details for PubMedID 24456371
Prognosis of Right Ventricular Failure in Patients With Left Ventricular Assist Device Based on Decision Tree With SMOTE
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE
2012; 16 (3): 383-390
Right ventricular failure is a significant complication following implantation of a left ventricular assist device (LVAD), which increases morbidity and mortality. Consequently, researchers have sought predictors that may identify patients at risk. However, they have lacked sensitivity and/or specificity. This study investigated the use of a decision tree technology to explore the preoperative data space for combinatorial relationships that may be more accurate and precise. We retrospectively analyzed the records of 183 patients with initial LVAD implantation at the Artificial Heart Program, University of Pittsburgh Medical Center, between May 1996 and October 2009. Among those patients, 27 later required a right ventricular assist device (RVAD+) and 156 remained on LVAD (RVAD-) until the time of transplantation or death. A synthetic minority oversampling technique (SMOTE) was applied to the RVAD+ group to compensate for the disparity of sample size. Twenty-one resampling levels were evaluated, with decision tree model built for each. Among these models, the top six predictors of the need for an RVAD were transpulmonary gradient (TPG), age, international normalized ratio (INR), heart rate (HR), aspartate aminotransferase (AST), prothrombin time, and right ventricular systolic pressure. TPG was identified to be the most predictive variable in 15 out of 21 models, and constituted the first splitting node with 7 mmHg as the breakpoint. Oversampling was shown to improve the senstivity of the models monotonically, although asymptotically, while the specificity was diminished to a lesser degree. The model built upon 5X synthetic RVAD+ oversampling was found to provide the best compromise between sensitivity and specificity, included TPG (layer 1), age (layer 2), right atrial pressure (layer 3), HR (layer 4,7), INR (layer 4, 9), alanine aminotransferase (layer 5), white blood cell count (layer 5,6, &7), the number of inotrope agents (layer 6), creatinine (layer 8), AST (layer 9, 10), and cardiac output (layer 9). It exhibited 85% sensitivity, 83% specificity, and 0.87 area under the receiver operating characteristic curve (RoC), which was found to be greatly improved compared to previously published studies.
View details for DOI 10.1109/TITB.2012.2187458
View details for Web of Science ID 000303997700011
View details for PubMedID 22334033
Decision tree for adjuvant right ventricular support in patients receiving a left ventricular assist device
JOURNAL OF HEART AND LUNG TRANSPLANTATION
2012; 31 (2): 140-149
Right ventricular (RV) failure is a significant complication after implantation of a left ventricular assist device (LVAD). It is therefore important to identify patients at risk a priori. However, prognostic models derived from multivariate analyses have had limited predictive power.This study retrospectively analyzed the records of 183 LVAD recipients between May 1996 and October 2009; of these, 27 later required a RVAD (RVAD(+)) and 156 remained on LVAD only (RVAD(-)) until transplant or death. A decision tree model was constructed to represent combinatorial non-linear relationships of the pre-operative data that are predictive of the need for RVAD support.An optimal set of 8 pre-operative variables were identified: transpulmonary gradient, age, right atrial pressure, international normalized ratio, heart rate, white blood cell count, alanine aminotransferase, and the number of inotropic agents. The resultant decision tree, which consisted of 28 branches and 15 leaves, identified RVAD(+) patients with 85% sensitivity, RVAD(-) patients with 83% specificity, and exhibited an area under the receiver operating characteristic curve of 0.87.The decision tree model developed in this study exhibited several advantages compared with existing risk scores. Quantitatively, it provided improved prognosis of RV support by encoding the non-linear, synergic interactions among pre-operative variables. Because of its intuitive structure, it more closely mimics clinical reasoning and therefore can be more readily interpreted. Further development with additional multicenter, longitudinal data may provide a valuable prognostic tool for triage of LVAD therapy and, potentially, improve outcomes.
View details for DOI 10.1016/j.healun.2011.11.003
View details for Web of Science ID 000300545100005
View details for PubMedID 22168963
View details for PubMedCentralID PMC3273573