- Interventional Pulmonology
- Pulmonary Medicine
- Pleural Disease
- Lung Cancer
- Critical Care
- Internal Medicine
Clinical Assistant Professor, Medicine - Pulmonary, Allergy & Critical Care Medicine
Board Certification, American Association of Bronchology and Interventional Pulmonology, Interventional Pulmonology (2021)
Board Certification: American Board of Internal Medicine, Critical Care Medicine (2019)
Board Certification: American Board of Internal Medicine, Pulmonary Disease (2018)
Board Certification: American Board of Internal Medicine, Internal Medicine (2016)
Fellowship, Cleveland Clinic, Interventional Pulmonary Medicine (2020)
Fellowship, Stanford University, Pulmonary & Critical Care Medicine (2019)
Residency, Stanford University, Internal Medicine (2016)
Medical Education, Albert Einstein College of Medicine, Doctor of Medicine (M.D.) (2013)
Prospective validation of an 11-gene mRNA host response score for mortality risk stratification in the intensive care unit.
2021; 11 (1): 13062
Several clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p<0.01) and within 60days (40% vs 15%, p=0.06). The 11-gene score improved prognostication with a categorical Net Reclassification Improvement index of 0.37 (p=0.03) and an Integrated Discrimination Improvement index of 0.07 (p=0.02) when combined with Simplified Acute Physiology Score 3 or Acute Physiology and Chronic Health Evaluation II score. The test performed poorly in the 95 independent samples collected>24h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.
View details for DOI 10.1038/s41598-021-91201-7
View details for PubMedID 34158514
- "I Now Walk Into the Wild": Atelectasis During Peripheral Bronchoscopy Under General Anesthesia. Chest 2020; 158 (6): 2268–69
- Atypical Blastomycosis Masquerading as Lofgren Syndrome. American journal of respiratory and critical care medicine 2020
A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.
2020; 11 (1): 1177
Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N=1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1(IMX-BVN-1), without retraining, to an independent cohort (N=163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36h of hospital admission (N=70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.
View details for DOI 10.1038/s41467-020-14975-w
View details for PubMedID 32132525
What is the value of electromagnetic navigation in lung cancer and to what extent does it require improvement?
Expert review of respiratory medicine
2020; 14 (7): 655–69
Lung nodules are being identified with increasing frequency. With this growing burden of nodules comes a growing need for diagnostic technologies extending beyond the current reach of conventional bronchoscopy. One such method for diagnosing peripheral lung lesions is electromagnetic navigational bronchoscopy (ENB), which comprises a set of tools designed to aid the bronchoscopist in identifying, accessing, and sampling peripheral lung lesions under virtual guidance.Herein we present an in-depth review of ENB, including commercially available electromagnetic navigation platforms, factors influencing diagnostic yield, adjunctive imaging and biopsy tools, potential risks, cost, technical shortcomings, and competing technologies. A review of the scientific literature was conducted primarily through PubMed, ScienceDirect, and Google Scholar, and pertinent publications and abstracts from the inception of electromagnetic navigation through early 2020 were considered. We also share our perspective on the future of ENB from both a diagnostic and a therapeutic standpoint.ENB is currently a leading tool in the diagnostic evaluation of peripheral lung lesions. The future of ENB rests not only on its potential to expand into the therapeutic realm but also on its ability to keep pace with competing diagnostic and therapeutic technologies.
View details for DOI 10.1080/17476348.2020.1748012
View details for PubMedID 32216487