Hossein Estiri

Long COVID Persistence and Surveillance Gaps Across 58 US Hospitals Supplement 1. eTable 1. ICD-10 codes retained for PASC case identification with chronicity classifications. Supplement 2. eFigure 1. Federated multi-site implementation workflow for PASC phenotyping across four regions. eTable 2. Demographic and clinical characteristics of COVID-19 cases across four regions. eFigure 2. Organ-specific PASC prevalence across four regions. eFigure 3.

Abstract The impact of antiviral therapies, including Paxlovid, on post-acute sequelae of COVID-19 (PASC) remains inconclusive. We analyzed data from 19,413 patients (age > 18) from a validated PASC research cohort in New England who experienced at least one COVID-19 infection episode between January 1, 2022, and June 7, 2022, totaling 22,094 episodes.

Abstract The temporal sequence of clinical events is crucial in outcomes research, yet standard machine learning (ML) approaches often overlook this aspect in electronic health records (EHRs), limiting predictive accuracy. We introduce Temporal Learning with Dynamic Range (TLDR), a time-sensitive ML framework, to identify risk factors for post-acute sequelae of SARS-CoV-2 infection (PASC).