Post-Acute COVID-19 Effects on Diagnostic Conversion Rates And Standardized Cognitive and Motor Test Scores in a Longitudinal Study of Independent, Community-Recruited Elderly Subjects
Notice bibliographique
Résumé
There is considerable concern about the long-term consequences of COVID-19 infection, generally referred to as post-acute sequelae, including declines in cognitive and motor abilities. The degree to which COVID-19 contributes additional burden to normal aging trajectories remains unclear. Additionally, the impact of COVID-19 on subjects under study for age-related neurological diseases is a potential confounder that needs definition. This study investigated whether having had a COVID-19 illness was associated with a differential decline in cognitive or motor function in older adults, utilizing data from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) and Brain and Body Donation Program (BBDP), a longitudinal clinicopathological study based in metropolitan Phoenix, Arizona. Subjects were included if they 1) had completed a questionnaire about their experience with COVID-19 illness 2) were classified as cognitively normal at pre-pandemic diagnostic cognitive consensus conferences and 3) had one or more subsequent diagnostic conferences between July 1, 2020 and August 30, 2025. All subjects had serial standardized research-dedicated clinical evaluations including the Montreal Cognitive Assessment (MoCA) and the Unified Parkinson's Disease Rating Scale (UPDRS). Specific objectives were to compare, between those who reported having had or not having had COVID-19, rates of conversion to cognitive impairment or dementia as well as pre-pandemic and final MoCA and UPDRS motor scores. A total of 100 subjects self-reported having had COVID-19 while 71 denied having had it. Their related acute illness severity was generally mild, with only 10% having had hospital treatment and none having required ventilator support. Post-acute symptoms were also mild; only 1 subject reported having "long Covid". Both cognitive and motor performance, as measured by MoCA and UPDRS part 3 scores, declined slightly (not statistically significant) over the study period. Conversion of cognitive diagnosis from normal to impaired or dementia occurred in 26% of those having had COVID-19 and in 32% of those not having had COVID-19; the difference was not significant. All subjects diagnosed with PD at the start of the study were also diagnosed with PD at the end of the study; no subjects converted from not having to having probable PD. Logistic regression analysis indicated that subjects' report of having had COVID-19 was not significantly associated with conversion to cognitive impairment or dementia while greater age, male sex, possession of one or more apolipoprotein E- ɛ4 alleles, and a diagnosis of probable PD all conferred a significantly greater likelihood of conversion. The results suggest that having a mild COVID-19 illness is not associated with greater declines on cognitive or motor screening tests than would be expected from age-related changes alone. Limitations of this analysis include small sample sizes, potential misclassification of COVID-19 status, and reliance on relatively crude clinical metrics that may miss significant functional changes. Additionally, we were unable to separately assess for varying COVID-19 severity dependent on whether or not the subject had been vaccinated, the number and type of vaccinations, and the particular SARS-CoV-2 variants that were circulating at the time of illness.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».