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Published, Version of Record (VoR)Open Access (License Unspecified), Open
Preprint
Machine learning models predict long COVID outcomes based on baseline clinical and immunologic factors
medRxiv
13 Feb 2025
Abstract
The post-acute sequelae of SARS-CoV-2 (PASC), also known as long COVID, remain a significant health issue that is incompletely understood. Predicting which acutely infected individuals will go on to develop long COVID is challenging due to the lack of established biomarkers, clear disease mechanisms, or well-defined sub-phenotypes. Machine learning (ML) models offer the potential to address this by leveraging clinical data to enhance diagnostic precision. We utilized clinical data, including antibody titers and viral load measurements collected at the time of hospital admission, to predict the likelihood of acute COVID-19 progressing to long COVID. Our machine learning models achieved median AUROC values ranging from 0.64 to 0.66 and AUPRC values between 0.51 and 0.54, demonstrating their predictive capabilities. Feature importance analysis revealed that low antibody titers and high viral loads at hospital admission were the strongest predictors of long COVID outcomes. Comorbidities, including chronic respiratory, cardiac, and neurologic diseases, as well as female sex, were also identified as significant risk factors for long COVID. Our findings suggest that ML models have the potential to identify patients at risk for developing long COVID based on baseline clinical characteristics. These models can help guide early interventions, improving patient outcomes and mitigating the long-term public health impacts of SARS-CoV-2.
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Details
- Title
- Machine learning models predict long COVID outcomes based on baseline clinical and immunologic factors
- Creators
- Naresh Doni Jayavelu - University of WashingtonHady Samaha - Emory and Henry CollegeSonia Tandon WimalasenaAnnmarie Hoch - Boston Children's HospitalJeremy P Gygi - Yale School of MedicineGisela GabernetAl Ozonoff - Boston Children's HospitalShanshan Liu - Boston Children's HospitalCarly E. Milliren - Boston Children's HospitalOfer Levy - Boston Children's HospitalLindsey R. Baden - Brigham and Women's HospitalEsther Melamed - The University of Texas at AustinLauren I. R. Ehrlich - The University of Texas at AustinGrace A. McComsey - Case Western Reserve UniversityRafick P. Sekaly - Case Western Reserve UniversityCharles B. Cairns - Drexel UniversityElias K. Haddad - Drexel UniversityJoanna Schaenman - University of California, Los AngelesAlbert C. Shaw - Yale School of MedicineDavid A. Hafler - Yale School of MedicineRuth R. Montgomery - Yale School of MedicineDavid B. Corry - Baylor College of Medicinea and the Center for Translational Research on Inflammatory DiseasesFarrah Kheradmand - Baylor College of Medicinea and the Center for Translational Research on Inflammatory DiseasesMark A. Atkinson - University of FloridaScott C. Brakenridge - University of FloridaNelson I Agudelo Higuita - OU HealthJordan P. Metcalf - OU HealthCatherine L. Hough - Oregon Health & Science UniversityWilliam B. Messer - Oregon Health & Science UniversityBali Pulendran - Stanford University School of MedicineKari C. Nadeau - Stanford University School of MedicineMark M. Davis - Stanford University School of MedicineLinda N. Geng - Stanford University School of MedicineAna Fernandez Sesma - Icahn School of Medicine at Mount SinaiViviana Simon - Icahn School of Medicine at Mount SinaiFlorian Krammer - Icahn School of Medicine at Mount SinaiMonica Kraft - University of ArizonaChris Bime - University of ArizonaCarolyn S. Calfee - University of California, San FranciscoDavid J. Erle - University of California, San FranciscoCharles R. Langelier - University of California, San FranciscoLeying Guan - Yale School of Public HealthHolden T. Maecker - Stanford University School of MedicineBjoern Peters - La Jolla Institute for ImmunologySteven H. Kleinstein - Yale School of MedicineElaine F. Reed - University of California, Los AngelesJoann Diray-Arce - Boston Children's HospitalNadine Rouphael - Boston Children's HospitalMatthew C. Altman - University of Washington
- Publication Details
- medRxiv
- Publisher
- Cold Spring Harbor Laboratory Press
- Edition
- 1.1
- Number of pages
- 30
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- College of Medicine; Infectious Diseases (and HIV Medicine); Emergency Medicine
- Other Identifier
- 991022030047904721