Logo image
Back
Identifying commonalities and differences between EHR representations of PASC and ME/CFS in the RECOVER EHR cohort
Journal article   Peer reviewed

Identifying commonalities and differences between EHR representations of PASC and ME/CFS in the RECOVER EHR cohort

John P. Powers, Tomas J. McIntee, Abhishek Bhatia, Charisse R. Madlock-Brown, Jaime Seltzer, Anisha Sekar, Nita Jain, Mady Hornig, Elle Seibert, Peter J. Leese, …
Communications medicine, Vol.5(1), 109
04/11/2025
DOI: 10.1038/s43856-025-00827-5
PMCID: PMC11986062
PMID: 40210986

View Online

Abstract

Background Shared symptoms and biological abnormalities between post-acute sequelae of SARS-CoV-2 infection (PASC) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) could suggest common pathophysiological bases and would support coordinated treatment efforts. Empirical studies comparing these syndromes are needed to better understand their commonalities and differences. Methods We analyzed electronic health record data from 6.5 million adult patients from the National COVID Cohort Collaborative. PASC and ME/CFS diagnostic groups were defined based on recorded diagnoses, and other recorded conditions within the two groups were used to train separate machine learning-driven computable phenotypes (CPs). The most predictive conditions for each CP were examined and compared, and the overlap of patients labeled by each CP was examined. Condition records from the diagnostic groups were also used to statistically derive condition clusters. Rates of subphenotypes based on these clusters were compared between PASC and ME/CFS groups. Results Approximately half of patients labeled by one CP are also labeled by the other. Dyspnea, fatigue, and cognitive impairment are the most-predictive conditions shared by both CPs, whereas other most-predictive conditions are specific to one CP. Recorded conditions separate into cardiopulmonary, neurological, and comorbidity clusters, with the cardiopulmonary cluster showing partial specificity for the PASC groups. Conclusions Data-driven approaches indicate substantial overlap in the condition records associated with PASC and ME/CFS diagnoses. Nevertheless, cardiopulmonary conditions are somewhat more commonly associated with PASC diagnosis, whereas other conditions, such as pain and sleep disturbances, are more associated with ME/CFS diagnosis. These findings suggest that symptom management approaches to these illnesses could overlap. Plain language summary Post-acute sequelae of SARS-CoV-2 infection (PASC; also known as Long COVID) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) appear to share much in common. Understanding their similarities and differences could help to guide treatment for these complex illnesses. We analyzed data from 6.5 million adult patients from the National COVID Cohort Collaborative to evaluate patterns in their health records. We find several conditions associated with both PASC and ME/CFS diagnoses, such as difficulty breathing, fatigue, and concentration difficulties. We also find some differences. Cardiac and respiratory conditions are more typical with PASC diagnoses. Records of pain, sleep disturbances, and neuropsychiatric conditions more commonly accompany ME/CFS diagnoses. Overall, the similarities we see could support overlapping symptom management approaches across these illnesses. Powers et al. investigate commonalities and differences between electronic health record patterns associated with post-acute sequelae of SARS-CoV-2 infection and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Records of dyspnea, fatigue, and cognitive impairment are common diagnoses and recommend common symptom management.
 692/699 692/700/139 Article General Medicine Medicine & Public Health

Details

Metrics

15 Record Views
2 Times Cited - Web of Science
Logo image