COVCOG 1: Factors Predicting Physical, Neurological and Cognitive Symptoms in Long COVID in a Community Sample. A First Publication From the COVID and Cognition Study.

COVID-19 Long COVID cognition executive functions language memory neurological symptoms

Journal

Frontiers in aging neuroscience
ISSN: 1663-4365
Titre abrégé: Front Aging Neurosci
Pays: Switzerland
ID NLM: 101525824

Informations de publication

Date de publication:
2022
Historique:
received: 29 10 2021
accepted: 31 01 2022
entrez: 4 4 2022
pubmed: 5 4 2022
medline: 5 4 2022
Statut: epublish

Résumé

Since its first emergence in December 2019, coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has evolved into a global pandemic. Whilst often considered a respiratory disease, a large proportion of COVID-19 patients report neurological symptoms, and there is accumulating evidence for neural damage in some individuals, with recent studies suggesting loss of gray matter in multiple regions, particularly in the left hemisphere. There are a number of mechanisms by which COVID-19 infection may lead to neurological symptoms and structural and functional changes in the brain, and it is reasonable to expect that many of these may translate into cognitive problems. Indeed, cognitive problems are one of the most commonly reported symptoms in those experiencing "Long COVID"-the chronic illness following COVID-19 infection that affects between 10 and 25% of patients. The COVID and Cognition Study is a part cross-sectional, part longitudinal, study documenting and aiming to understand the cognitive problems in Long COVID. In this first paper from the study, we document the characteristics of our sample of 181 individuals who had experienced COVID-19 infection, and 185 who had not. We explore which factors may be predictive of ongoing symptoms and their severity, as well as conducting an in-depth analysis of symptom profiles. Finally, we explore which factors predict the presence and severity of cognitive symptoms, both throughout the ongoing illness and at the time of testing. The main finding from this first analysis is that that severity of initial illness is a significant predictor of the presence and severity of ongoing symptoms, and that some symptoms during the initial illness-particularly limb weakness-may be more common in those that have more severe ongoing symptoms. Symptom profiles can be well described in terms of 5 or 6 factors, reflecting the variety of this highly heterogenous condition experienced by the individual. Specifically, we found that neurological/psychiatric and fatigue/mixed symptoms during the initial illness, and that neurological, gastrointestinal, and cardiopulmonary/fatigue symptoms during the ongoing illness, predicted experience of cognitive symptoms.

Identifiants

pubmed: 35370617
doi: 10.3389/fnagi.2022.804922
pmc: PMC8968323
doi:

Types de publication

Journal Article

Langues

eng

Pagination

804922

Informations de copyright

Copyright © 2022 Guo, Benito Ballesteros, Yeung, Liu, Saha, Curtis, Kaser, Haggard and Cheke.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Panyuan Guo (P)

Department of Psychology, University of Cambridge, Cambridge, United Kingdom.

Alvaro Benito Ballesteros (A)

Department of Psychology, University of Cambridge, Cambridge, United Kingdom.

Sabine P Yeung (SP)

Department of Psychology, University of Cambridge, Cambridge, United Kingdom.

Ruby Liu (R)

Department of Psychology, University of Cambridge, Cambridge, United Kingdom.

Arka Saha (A)

Department of Psychology, University of Cambridge, Cambridge, United Kingdom.

Lyn Curtis (L)

School of Psychology, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom.

Muzaffer Kaser (M)

Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom.

Mark P Haggard (MP)

Department of Psychology, University of Cambridge, Cambridge, United Kingdom.

Lucy G Cheke (LG)

Department of Psychology, University of Cambridge, Cambridge, United Kingdom.

Classifications MeSH