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Identifying subtypes of Long COVID: a systematic review

Bing-Yi Wang, Xu-Fei Luo, Mei-Hua Wu, Zi-Jun Wang, Jie Zhang, Zi-Jing Wang, Q. Shi, Jiayi Liu et al.

EClinicalMedicine, 2025

43 participants · 9 citations

Abstract

Summary Background Long COVID, a persistent condition following SARS-CoV-2 infection, exhibits diverse symptoms across multiple organ systems. This study aims to summarize the existing clustering and classification approaches to support the management of Long COVID. Methods Following PRISMA guidelines, we systematically searched PubMed, Embase, Web of Science, and Google Scholar from their inception to January 21, 2025, and updated the search on October 1, 2025, to identify studies that presented a way to categorize Long COVID patients or symptoms. Data extraction and quality assessment were conducted for eligible studies. We presented symptom co-occurrence networks, and performed meta-analysis to estimate the percentage of different organ system-based symptom clusters. In addition, we conducted an exploratory analysis of the determinants of different symptom clusters. The protocol was registered in OSF (https://doi.org/10.17605/OSF.IO/J483F). Findings Forty-seven cohort studies and 17 cross-sectional studies categorizing Long COVID subtypes or symptoms were included, encompassing 2.43 million participants across 20 countries. The methodological quality of the cohort studies was on average high (mean Newcastle–Ottawa scale score: 7.5/9), and of the 17 cross-sectional studies moderate (mean Joanna Briggs Institute tool score: 0.61/1.00). Patients or symptoms were categorized either according to the co-occurrence of symptoms (n = 30 studies, 46.9%); by the affected organ…

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Evidence Hub reads this as a systematic review, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 43 participants or records.

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