Faculty Bibliography

BACKGROUND/UNASSIGNED:Effective management of alcohol withdrawal syndrome during hospitalization is paramount to patient safety and quality care. NYC Health + Hospitals initiated a quality improvement project to pilot an electronic health record (EHR) integrated, nurse-driven CIWA-Ar symptom-triggered protocol, including recommendations for medications for alcohol use disorder (MAUD), in medical and surgical units at 3 public hospitals. OBJECTIVE/UNASSIGNED:To describe implementation processes and to report related implementation outcomes (appropriateness, feasibility, and adoption) of the updated CIWA-Ar protocol in a safety net hospital setting. METHODS/UNASSIGNED:NYC Health + Hospitals implemented a standardized CIWA-Ar symptom-triggered, nurse-driven EHR protocol on March 15, 2022. The protocol included order sets, practice advisories, task lists, and reminders for assessments and orders. We measured nursing perspectives on feasibility and appropriateness at 6 months via a survey. We measured provider adoption as the proportion of admissions with a CIWA-Ar protocol ordered among admissions that triggered a recommendation, and MAUD use as the proportion of admissions with a MAUD order during hospitalization among all patients with a protocol ordered. RESULTS/UNASSIGNED:= .249). CONCLUSIONS/UNASSIGNED:The CIWA-Ar protocol was appropriate, feasible, and adopted at NYC public hospitals. Quality improvements to ensure protocol fidelity with benzodiazepine dosing and MAUD prescribing are needed.

The rapid evolution of generative artificial intelligence (AI) is poised to transform medicine and medical education. Large language models (LLMs) have begun to demonstrate capabilities in reasoning, diagnosis, documentation, and patient communication that can rival or exceed those of clinicians. In medical education, AI is reshaping how students learn and how faculty teach-offering individualized, context-sensitive guidance at scale. This article outlines the current state of AI integration in health care, examines how systems can responsibly implement it to enhance patient care and education, and raises critical questions about ethics and safety as we harness its transformative potential.

OBJECTIVE:To evaluate whether the risk of long COVID among individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during pregnancy differs from that of individuals who were not pregnant at time of virus acquisition. METHODS:We conducted a multicenter observational cohort study at 79 NIH RECOVER (Researching COVID to Enhance Recovery) sites. Individuals assigned female at birth aged 18-45 years with an index (first) SARS-CoV-2 infection on or after December 1, 2021, were included. The exposure was pregnancy (any gestational age) at the time of index SARS-CoV-2 infection. The primary outcome was long COVID 6 months after index infection , defined as RECOVER-Adult Long COVID Research Index score 11 or higher based on a detailed symptom survey. To account for confounding and differential selection between participants who were pregnant and not pregnant at infection, propensity score-matching methods were used to balance the groups on variables potentially associated with both pregnancy status and long COVID. RESULTS:Overall 2,423 participants were included; 580 (23.9%) were pregnant at index SARS-CoV-2 infection. The median age at infection was 33 years (interquartile range 28-38 years), and 2,131 of participants (90.0%) with known vaccination status were vaccinated. After propensity score matching, the adjusted long COVID prevalence estimates 6 months after index infection were 10.2% (95% CI, 6.2-14.3%) among those pregnant at infection and 10.6% (95% CI, 8.8-12.4%) among those not pregnant at infection. Pregnancy was not associated with a difference in adjusted risk of long COVID (adjusted risk ratio 0.96, 95% CI, 0.63-1.48). CONCLUSION/CONCLUSIONS:Acquisition of SARS-CoV-2 during pregnancy was not associated with a differential risk of long COVID at 6 months compared with similar-aged individuals who acquired SARS-CoV-2 outside of pregnancy.

BACKGROUND/UNASSIGNED:Academic dermatologists manage a broad array of responsibilities, often extending beyond clinical duties to include education, research, mentorship, and administrative work. OBJECTIVE/UNASSIGNED:This study aimed to quantify the scope of paid and unpaid responsibilities among academic dermatologists in the United States and identify disparities based on gender, career stage, and geography. METHODS/UNASSIGNED:A cross-sectional survey of 63 board-certified academic dermatologists from 12 institutions collected data on demographics, workweek allocation, after-hours tasks, compensation, burnout, and resilience from January to May 2025. RESULTS/UNASSIGNED:Respondents reported spending 58.3% of their time on clinical care, 15.9% on administrative duties, 13.8% on education, and 11.9% on research. Nearly half received 11 to 50 daily patient messages via the clinical inbox, and over 80% took hospital call duties, with most receiving no extra compensation. Burnout affected 63.5% of respondents and was significantly more prevalent among women, early-career physicians, and those in the Mid-Atlantic and Northeast regions. Resilience scores were lower among women. Consulting opportunities, often associated with supplemental income and career advancement, were more common among male and senior physicians. Parental leave policies were inconsistently applied and poorly understood; nearly 20% of respondents had 8 or fewer weeks of paid parental leave. LIMITATIONS/UNASSIGNED:Study limitations include the relatively small sample size and overrepresentation of the Northeast region, potentially hindering generalizability. Additionally, no significant race-based differences were observed, which may be due to insufficient sample sizes within comparator groups. CONCLUSION/UNASSIGNED:These findings highlight the cumulative burden of undercompensated labor, inadequate institutional support, and gender disparities in workload and opportunity. Structural changes in compensation transparency, workload distribution, recognition of academic labor, and support for early-career and female physicians are essential to fostering sustainability and equity within academic dermatology.

BACKGROUND:Epidermal growth factor receptor (EGFR) exon 20 insertions (Ex20ins) are the third most common type of EGFR mutation, occurring in up to 12% of EGFR-mutated non-small cell lung cancers (NSCLC). Ex20ins-mutated NSCLC can be resistant to most approved tyrosine kinase inhibitors (TKIs). The Phase III PAPILLON trial (NCT04538664) demonstrated that amivantamab plus chemotherapy significantly improves progression-free survival (PFS) compared to chemotherapy alone, leading to its approval as a first-line treatment for patients with Ex20ins NSCLC. PAPILLON further evaluated patient-reported outcomes (PROs) and time to symptomatic progression (TTSP). METHODS:The open-label, multicenter trial randomized 308 treatment-naïve patients with advanced or metastatic NSCLC harboring Ex20ins to receive either amivantamab plus carboplatin-pemetrexed (n = 154) or chemotherapy alone (n = 154). TTSP was defined as the time to onset or worsening of lung cancer-related symptoms necessitating treatment change or clinical intervention, or death. PROs were assessed using the PROMIS PF8c and EORTC QLQ-C30. RESULTS:At 12 months, 77 % of patients in the amivantamab-chemotherapy arm remained free of symptomatic progression versus 60 % in the chemotherapy arm (HR, 0.67; 95 % CI, 0.46-0.98; p = 0.04). Physical functioning and global health status PROs were maintained in both arms, with a higher proportion of patients treated in the amivantamab-chemotherapy arm reporting stable or improved quality of life at 6 and 12 months. CONCLUSIONS:Amivantamab plus chemotherapy significantly delays symptomatic progression without compromising health-related quality of life, reinforcing its role as a first-line treatment for Ex20ins-mutated NSCLC.

BACKGROUND:Cognitive interviewing is a methodological technique to elicit feedback on item comprehension and response categories by the target population. This method can be particularly relevant when working with vulnerable populations, such as people who use drugs, and for complex behaviors, including the use of multiple drugs (i.e., polysubstance use). While cognitive interviewing is recognized as an important technique, few case studies of the method have been published. OBJECTIVE:The current manuscript details the cognitive interview method employed as part of the development of a novel polysubstance assessment tool. RESULTS:Participants (n=28) with recent polysubstance use provided qualitative feedback using an iterative study design. Results detail the decision-making process of the study team to improve comprehension of complex behaviors, specifically simultaneous and same-day polysubstance use. Notably, the administration modality changed from self to interviewer-administered to facilitate participant understanding. CONCLUSIONS:Findings highlight the utility of the cognitive interview method in improving assessments of substance use.

IMPORTANCE/OBJECTIVE:Patients with poor glycaemic control have a high risk for major cardiovascular events. Improving glycaemic monitoring in patients with diabetes can improve morbidity and mortality. OBJECTIVE:To assess the effectiveness of a patient portal message in prompting patients with poorly controlled diabetes without a recent glycated haemoglobin (HbA1c) result to have their HbA1c repeated. DESIGN/METHODS:A pragmatic, randomised clinical trial. SETTING/METHODS:A large academic health system consisting of over 350 ambulatory practices. PARTICIPANTS/METHODS:Patients who had an HbA1c greater than 10% who had not had a repeat HbA1c in the prior 6 months. EXPOSURES/METHODS:A single electronic health record (EHR)-based patient portal message to prompt patients to have a repeat HbA1c test versus usual care. MAIN OUTCOMES/RESULTS:The primary outcome was a follow-up HbA1c test result within 90 days of randomisation. RESULTS:The study included 2573 patients with a mean (SD) HbA1c of 11.2%. Among 1317 patients in the intervention group, 24.2% had follow-up HbA1c tests completed within 90 days, versus 21.1% of 1256 patients in the control group (p=0.07). Patients in the intervention group were more likely to log into the patient portal within 60 days as compared with the control group (61.2% vs 52.3%, p<0.001). CONCLUSIONS:Among patients with poorly controlled diabetes and no recent HbA1c result, a brief patient portal message did not significantly increase follow-up testing but did increase patient engagement with the patient portal. Automated patient messages could be considered as a part of multipronged efforts to involve patients in their diabetes care.

BACKGROUND:Large-scale genetic and epigenetic studies have identified numerous genes linked to lung function. However, proteomics, which can offer more direct insights into pathophysiologic processes, remains underexplored. We aimed to identify circulating proteins related to lung function. METHODS:/FVC) in relation to abundance in circulation of 4693 proteins assessed using the SOMAScan™ platform. Study-level associations were determined using robust linear regression, adjusting for confounders including age, sex, height, weight, and smoking. Results were then meta-analysed using inverse-variance weighting. RESULTS:). The 473 enriched pathways identified include those involving inflammation and organismal injury. Protein-protein networks indicate potential orchestrators of lung function, including STAT3 and EGFR. Associations with 411 proteins were validated in the UK Biobank using the Olink 3K platform (560 overlapping proteins). 179 proteins identified were related to COPD in our data. While most associated proteins are likely biomarkers of impaired lung function, Mendelian randomisation provides preliminary evidence suggesting potential causality for 34 proteins. Our findings include known biomarkers of lung diseases including COPD. Notably, 89% of associated proteins have not been previously implicated in lung function. CONCLUSION/CONCLUSIONS:This comprehensive investigation identified novel protein-lung function associations that could improve understanding of lung disease pathogenesis, aid in the discovery of circulating biomarkers and accelerate development of new management strategies for respiratory conditions.

OBJECTIVES/OBJECTIVE:Extracorporeal membrane oxygenation (ECMO) is a life-saving therapy for severe cardiopulmonary failure, but structured training remains constrained by costs, logistics, and the absence of validated high-fidelity simulators. This study aimed to develop an ECMO digital twin capable of supporting training in virtual reality (VR). METHODS:We integrated high-frequency ECMO machine data with electronic health record information from 335 patients across two centres. Data streams were synchronised at a 30-second resolution. A hierarchical two-stage system was designed: Model 1 predicted ECMO device outputs, while Model 2 combined those outputs with patient vital functions such as heart rate and blood pressure. This model was integrated into a VR simulation and underwent testing by 21 experts. RESULTS:Model 2 demonstrated Root Mean Square Errors (RMSE) of 15.23 mmHg (diastolic arterial blood pressure), 19.50BPM (heart rate), 2.94% (peripheral oxygen saturation), and 1.42 mmHg (end-tidal carbon dioxide) on the test set. Neural networks produced clinically coherent predictions. The models were implemented in an Unreal Engine-based VR simulator using the open neural network exchange format, with real-time latency inference and scenario switching. Expert testing confirmed good performance and clinically plausible physiological responses in the simulation. CONCLUSIONS:High-resolution ECMO data can be transformed into a digital twin for VR training. This framework broadens access to advanced ECMO education and establishes a foundation for multicentre validation, federated learning, and future expansion towards a critical-care digital-twin platform.