Cognitive Impairment in Long COVID Patients Presenting with Psychiatric Sequelae: A Cross-sectional Study
Notice bibliographique
Résumé
Introduction: Coronavirus Disease-2019 (COVID-19) affects mental health, causing various psychiatric symptoms, including cognitive impairment, which may persist for a long time. To develop effective strategies for combating this global health burden, it is necessary to ascertain whether COVID-19 itself causes cognitive decline or whether other factors also play any role. Aim: To determine the prevalence of cognitive impairment in long COVID patients who present with post-COVID-19 psychiatric sequelae, and to investigate its association with socio-demographic factors, depression, anxiety, and stress. Materials and Methods: A cross-sectional study was conducted from July 2022 to June 2023 at a ‘Post-COVID Mental Health Clinic’ in a tertiary care medical college in Kolkata, India. A total of 204 subjects were selected through simple random sampling, aged between 18 and 65 years, of both sexes, who had recovered from COVID-19 more than three months but less than six months prior, and who presented with post-COVID-19 psychiatric sequelae, excluding those with a history of psychiatric disease before contracting COVID-19. The dependent variable, cognition, was measured using the Montreal Cognitive Assessment (MoCA) score, while independent variables included socio-demographic factors, depression, anxiety, and stress, measured by the Depression Anxiety Stress Scale -21 (DASS-21) scores. The Chisquare test was used to find the association between cognition and socio-demographic variables and Pearson’s correlation test was applied to measure the association of cognition with depression, anxiety, and stress scores. Results: The prevalence of cognitive impairment was found to be 86.8%. Chi-square tests of association showed no significant association with socio-demographic factors. However, there was a significant correlation between the severity of depression (r-value=-0.337, p-value<0.001), anxiety (r-value=-0.275, p-value<0.001), and stress (r-value=-0.277, p-value<0.001) with cognitive impairment. When controlling for anxiety and stress, only depression showed a significant correlation (r-value=- 0.221, p-value=0.002). Simple linear regression indicated that the severity of depression significantly predicted the severity of cognitive impairment {R2 =0.114, F(1, 202)=25.88, p-value<0.001}. Conclusion: Cognitive impairment was found to be unrelated to socio-demographic factors, post-COVID-19 anxiety, or stress, except for post-COVID-19 depression, which was identified as a significant predictor of cognitive dysfunction in some patients. This suggests that COVID-19 infection itself may be the most important factor contributing to post-COVID-19 cognitive impairment in patients with post-COVID-19 psychiatric sequelae.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».