Identifying predictors of cognitive decline in long-term care: a scoping review
Notice bibliographique
Résumé
BACKGROUND: Cognitive impairment can cause social, emotional, and financial burdens on individuals, caregivers, and healthcare providers. This is especially important in settings such as long-term care (LTC) homes which largely consist of vulnerable older adults. Thus, the objective of this study is to review and summarize current research examining risk factors of cognitive decline in older adults within LTC. METHODS: This scoping review includes primary observational research studies assessing within-person change in cognition over time in LTC or equivalent settings in high resource countries. A mean participant age of ≥ 65 years was required. Searches were conducted in Medline, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and PyscInfo on June 27th, 2022 and included articles published during or after the year 2000. Title, abstract, and full-text screening was performed by two independent reviewers using Covidence. Specific predictors along with their associated relation with cognitive decline were extracted by a team of reviewers into a spreadsheet. RESULTS: Thirty-eight studies were included in this review. The mean sample size was 14 620. Eighty-seven unique predictors were examined in relation to cognitive decline. Dementia was the most studied predictor (examined by 9 of 38 studies), and the most conclusive, with eight of those studies identifying it as a risk factor for cognitive decline. Other predictors that were identified as risk factors included arterial stiffness (identified by 2 of 2 studies), physical frailty (2 of 2 studies), sub-syndromal delirium (2 of 2 studies), and undergoing the first wave of COVID-19 lockdowns (2 of 2 studies). ADL independence was the most conclusive protective factor (3 of 4 studies), followed by social engagement (2 of 3 studies). Many remaining predictors showed no association and/or conflicting results. CONCLUSIONS: Dementia was the most common risk factor, while ADL independence was the most common protective factor associated with cognitive decline in LTC residents. This information can be used to stratify residents by risk severity and provide better personalized care for older adults through the targeted management of cognitive decline.
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 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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».