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Symptom Trajectories and Clinical Subtypes in Post-COVID-19 Condition: Systematic Review and Clustering Analysis
Mingzhi Hu1, Tian Song1, Zhaoyuan Gong1
1Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, No 16, Nanxiao Street, Dongzhimen, Dongcheng District, Beijing, 100700, China, 86 18515189525.
JMIR Public Health and Surveillance
|July 18, 2025
Summary
Post-COVID-19 condition involves evolving symptoms, with neurological issues like dizziness becoming prominent over time. Understanding these symptom trajectories is key for effective patient management and future epidemic preparedness.
Area of Science:
- Epidemiology of infectious diseases
- Longitudinal health studies
- Public health surveillance
Background:
- Post-COVID-19 condition presents complex, poorly understood symptoms impacting patient quality of life.
- A significant knowledge gap exists regarding the disease's trajectory and symptom evolution.
Purpose of the Study:
- To comprehensively characterize the temporal evolution of post-COVID-19 condition symptoms.
- To identify core symptom clusters and clinical phenotypes for better disease trajectory understanding.
Main Methods:
- Systematic literature search (PubMed, Web of Science, Embase) from Dec 2019 to Mar 2024.
- Meta-analysis of symptom prevalence and network analysis of symptom interrelationships.
- Clustering analysis to identify distinct clinical subtypes.
Main Results:
- Analyzed 108 studies (63,771 patients); fatigue was most prevalent.
- Respiratory symptoms like dyspnea declined over time; neurological symptoms, particularly dizziness, became dominant.
- Regional variations observed; distinct subtypes converged into a chronic pattern.
Conclusions:
- Post-COVID-19 symptoms dynamically evolve, with neurological issues persisting.
- Findings support region-specific surveillance and early warning systems for postinfectious sequelae.
- Monitoring symptom trajectories aids in identifying intervention points for future epidemics.
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