It is important to determine whether the persistent cognitive and fatigue complaints, as part of post-acute sequelae of COVID-19 (PASC), are associated with underlying patterns and specific symptoms clusters. Therefore, the aim of the present study was to investigate symptom clusters and clinical phenotypes in PASC. We included n = 153 individuals (53 years old, 66% female, 2 years post SARS-CoV-2 infection) categorized into groups with (n = 88) and without (n = 65) PASC, defined by severe fatigue and concentration problems using validated cut-offs. Symptom clusters (i.e., component loadings and component scores) were identified using principal component analyses (PCA, eigenvalue[EV]>1.0), using clinical, somatic, coping and sleep factors, symptom severity, neuropsychological and physical tests (totalling 19 tests and questionnaires). We then used logistic regression techniques on (participant-level) component scores (standardized) to investigate associations with PASC. Finally, K-means clustering methods to identify clinical phenotypes. Analyses were adjusted for age, sex, education, nationality and time since infection. PCA identified 5 components, explaining 70% of the variance. We labelled these components as follows: (1) PEM, ME/CFS and sleep symptoms, coping factors (EV = 7.0, 36.9% variance), (2) information-processing speed (EV = 2.5, 13.3%), (3) executive functioning (EV = 1.5, 8.0%, (4) physical performance (EV = 1.2, 6.5%), (5) somatic comorbidities and hospital admission (EV = 1.0, 5.5%). Logistic regression showed that only the first component scores (Odds ratio [95% confidence interval] = 97.1 [16.5–570.3], p < 0.001,), and none of the others (all p > 0.05), associated with PASC. Cluster analysis revealed two distinct clinical phenotypes among individuals with severe chronic fatigue: one marked by physical impairment and the other by diminished cognitive performance. Consistent with existing literature, we confirmed that PASC is a heterogeneous syndrome marked by extensive, interrelated symptoms. Notably, we identified specific cognitive and physical clinical phenotypes. These findings are important for future targeted diagnosis and treatment.
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Verfaillie et al. (2026) studied this question.
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