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

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.

Source: Powers JP, McIntee TJ, Bhatia A, Madlock-Brown CR, Seltzer J, Sekar A, Jain N, Hornig M, Seibert E, Leese PJ, Haendel M, Moffitt R, Pfaff ER; N3C Consortium and RECOVER-EHR. Identifying commonalities and differences between EHR representations of PASC and ME/CFS in the RECOVER EHR cohort. Commun Med (Lond). 2025 Apr 11;5(1):109. doi: 10.1038/s43856-025-00827-5. PMID: 40210986. https://www.nature.com/articles/s43856-025-00827-5 (Full text)

Wearable Devices Enable Long COVID Patients to Decrease Symptom Severity: A Case Series From Pilot User Testing

Abstract:

Purpose: Long COVID is a debilitating condition that is estimated to affect over 65M individuals across the world after a Coronavirus Disease 2019 (COVID-19) infection and has no broadly effective treatments. People with Long COVID have reported that pacing helps manage their symptoms, but it is difficult to implement. Based on experiences in the Long COVID community, we hypothesized that wearable devices can help individuals pace and reduce their Long COVID symptom severity.

Methods: To inform the design of a larger study, we performed user testing by distributing Garmin® devices, the study surveys and pacing educational materials to 11 individuals with Long COVID, and conducting interviews to learn about their experience.

Results: Eight of the 9 (89%) individuals reported that the information provided was helpful for their symptom management, and 2 testers did not complete the final survey. Four (44%) users had not used a wearable device before and none had trouble setting up their device. Due to the limited sample size and lack of control group, generalizability is unknown.

Conclusions: The most user testers reported that the study materials were helpful for their symptom management. These results are a promising indication of the potential for wearable devices and educational materials to help individuals with Long COVID, and potentially other chronic conditions such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), decrease symptom severity.

Source: Goosen A, Foster-Bonds R, Vogel JM. Wearable Devices Enable Long COVID Patients to Decrease Symptom Severity: A Case Series From Pilot User Testing. Cardiopulm Phys Ther J. 2024 Dec 3;36(2):99-104. doi: 10.1097/CPT.0000000000000268. PMID: 40190996; PMCID: PMC11970588. https://pmc.ncbi.nlm.nih.gov/articles/PMC11970588/ (Full text)