ArticleCommunications medicine2024
Identification of risk factors of Long COVID and predictive modeling in the RECOVER EHR cohorts.
Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Taurine supplementation as a therapeutic strategy for cellular senescence and chronic inflammation in long COVID: a systematic review and meta-analysis.BMC infectious diseases · 2026Pooled it
- Risk of long covid in patients with pre-existing chronic respiratory diseases: a systematic review and meta-analysis.BMJ open respiratory research · 2025Pooled it
- Harmonization of Real-World Data for Vaccine-Preventable Infectious Diseases: Integration of SARS-CoV-2 Diagnostic and Serologic Data From Multiple Sources.Open forum infectious diseases · 2026Article
- Factors Associated with Long COVID in the Pediatric Population: A Retrospective Case-Control Study.Clinics and practice · 2026Article
- A mixed-methods study comparing clinical and patient-reported perspectives on long COVID: insights from electronic health records and narrative journal entries.BMC infectious diseases · 2026Observational
- Mapping spatial and social inequities of long COVID across the United States: a retrospective cohort study.Lancet regional health. Americas · 2026Article
- Differential Factors Associated With the Presence of Persistent Symptoms in Individuals Diagnosed With Long COVID: Protocol for a Longitudinal Matched Case-Control Study.JMIR research protocols · 2026Observational
- Postacute Sequelae Following Omicron COVID-19 in Patients With Cancer.JAMA network open · 2026Article
- Longitudinal modeling of Post-COVID-19 condition over three years: A machine learning approach using clinical, neuropsychological, and fluid markers.Scientific reports · 2026Article
- Cancer and COVID-19: A review of immune insights and partnerships to inform public health strategy.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2026Review
- Association of chronic disease risk and physical activity measured by wearable devices in the All of Us program.Communications medicine · 2026Article
- Analysis of Long COVID characteristics and risk factors in individuals infected with COVID-19: a follow-up study based on a cohort of 2,792 participants.Frontiers in public health · 2026Article
- Bridging Gaps in Long COVID Therapy: A Review.Current medicinal chemistry · 2026Review
- A Predictive Model for the Development of Long COVID in Children.International journal of environmental research and public health · 2025Article
- Advances in Understanding Long COVID: Pathophysiological Mechanisms and the Role of Omics Technologies in Biomarker Identification.Molecular diagnosis & therapy · 2025Review
- Neuroimmune pathophysiology of long COVID.Psychiatry and clinical neurosciences · 2025Review
- SatHealth: A Multimodal Public Health Dataset with Satellite-based Environmental Factors.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2025Article
- Long COVID after SARS-CoV-2 during pregnancy in the United States.Nature communications · 2025Article
- Wearable data reveals distinct characteristics of individuals with persistent symptoms after a SARS-CoV-2 infection.NPJ digital medicine · 2025Article
- Coronavirus Disease 2019 (COVID-19) Real World Data Infrastructure: A Big-Data Resource for Study of the Impact of COVID-19 in Patient Populations With Immunocompromising Conditions.Open forum infectious diseases · 2025Article
Corrections and comments
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Authors and funding
20 authors.
Funding
Abstract
backgroundSARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors.
methodsIn this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests.
resultsWe observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7-0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6).
conclusionsThis observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.