ArticleEClinicalMedicine2023
Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort study.
Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Interventions for the management of long covid (post-covid condition): living systematic review.BMJ (Clinical research ed.) · 2024Pooled it
- Article
- Multimorbidity patterns and phenotype transitions in patients with clinician-coded long COVID: a multicenter US electronic health record cohort study.BMC infectious diseases · 2026Article
- Lung fibroblast activation protein expression is associated with extracellular matrix remodelling in post-acute sequelae of SARS-CoV-2.ERJ open research · 2026Article
- Long COVID Persistence and Surveillance Gaps Across 58 US Hospitals.JAMA network open · 2026Article
- Temporal Learning with Dynamic Range (TLDR) for modeling recurrent exposure and treatment outcomes.Scientific reports · 2026Article
- Algorithm dependence of patient phenotypes in Long COVID: a patient-led, multi-method clustering of 6031 patients using 162 self-reported symptoms.Oxford open immunology · 2026Article
- Identifying subtypes of Long COVID: a systematic review.EClinicalMedicine · 2026Article
- COVID-19-associated neurological and psychological manifestations.Nature reviews. Disease primers · 2025Review
- Decoding long COVID-associated cardiovascular dysfunction: Mechanisms, models, and new approach methodologies.Journal of molecular and cellular cardiology · 2025Review
- Subdomains of Post-COVID Syndrome (PCS) - a population-based study.BMC infectious diseases · 2025Article
- From Stagnation to Strategy: Challenges in Advancing Long COVID Research.Journal of evaluation in clinical practice · 2025Review
- Label efficient phenotyping for Long COVID using electronic health records.NPJ digital medicine · 2025Article
- The Development and Initial Validation of the Memorial Symptom Assessment Scale-Long COVID (MSAS-LC): A Promising Tool for Measuring Long COVID.International journal of environmental research and public health · 2025Article
- Precision phenotyping for curating research cohorts of patients with unexplained post-acute sequelae of COVID-19.Med (New York, N.Y.) · 2025Article
- [Post-COVID-19 condition-Clinical phenotyping in practice].Der Nervenarzt · 2024Article
- Finding Long-COVID: temporal topic modeling of electronic health records from the N3C and RECOVER programs.NPJ digital medicine · 2024Article
- Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs.medRxiv : the preprint server for health sciences · 2024Article
- Current update on the neurological manifestations of long COVID: more questions than answers.EXCLI journal · 2024Review
- Digital approaches in post-COVID healthcare: a systematic review of technological innovations in disease management.Biology methods & protocols · 2024Review
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
Background: Characterizing Post-Acute Sequelae of COVID (SARS-CoV-2 Infection), or Methods: We conducted a retrospective multi-centre observational cohort study, leveraging longitudinal electronic health record (EHR) data of 30,422 patients from three healthcare systems in the Consortium for the Clinical Characterization of COVID-19 by EHR (4CE). From the total cohort, we applied a deductive approach on 12,424 individuals with follow-up data and developed a distributed representation learning process for providing augmented definitions for PASC sub-phenotypes. Findings: Our framework characterized seven PASC sub-phenotypes. We estimated that on average 15.7% of the hospitalized COVID-19 patients were likely to suffer from at least one PASC symptom and almost 5.98%, on average, had multiple symptoms. Joint pain and dyspnea had the highest prevalence, with an average prevalence of 5.45% and 4.53%, respectively. Interpretation: We provided a scalable framework to every participating healthcare system for estimating PASC sub-phenotypes prevalence and temporal attributes, thus developing a unified model that characterizes augmented sub-phenotypes across the different systems. Funding: Authors are supported by National Institute of Allergy and Infectious Diseases, National Institute on Aging, National Center for Advancing Translational Sciences, National Medical Research Council, National Institute of Neurological Disorders and Stroke, European Union, National Institutes of Health, National Center for Advancing Translational Sciences.
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Registered trials
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