m+Medelevator.RU
← Поиск публикаций
PloS one · 2026

Post-acute sequelae of COVID-19 (PASC) are associated with distinct clinical phenotypes two years after SARS-CoV-2 infection: A data-driven approach.

СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Verfaillie Sander C J, Verveen Anouk, Visser Denise, Nieuwkerk Pythia, Appelman Brent, Boellaard Ronald, van Heugten Caroline M, Horn Janneke, Hulst Hanneke E, de Jong Menno D, Kuut Tanja A, Maaden Tessa van der, van Os Yvonne M G, Prins Maria, Visser-Meily Johanna M A, van Vugt Michele, van den Wijngaard Cees C, van Berckel Bart N M, Bosch Jos A, Tolboom Nelleke, Knoop Hans

Аннотация

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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты