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Enregistrement W7036870899

Cognitive associations of benzodiazepine use in older adults

2011· article· en· W7036870899 sur OpenAlexaboutno aff

Notice bibliographique

RevueResearchOnline at James Cook University (James Cook University) · 2011
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueScientific Computing and Data Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCognitionPopulationDiseaseSet (abstract data type)Identification (biology)Risk factor
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Use of prescription medications for various conditions is highly prevalent in older adults, often leading to the use of multiple medications. The resulting polypharmacy is widely recognized as a risk factor for many negative outcomes, but less is known about the risks of specific types of medication upon cognitive functions. Benzodiazepines are commonly prescribed for the treatment of anxiety and insomnia, among other conditions. While dependency with continued use has been the subject of much concern over this type of medication, other literature has suggested an increased risk of cognitive impairment with chronic use of benzodiazepines. The nature of the cognitive changes and the domains of cognitive function most likely to be affected have differed across various studies. Here we describe the associations between measures of various domains of cognitive functioning and benzodiazepine use in 2879 older Canadian adults from the Canadian Study of Health and Aging (CSHA; 64.3% female, mean age 81.0 years, SD=7.44). These people underwent a comprehensive medical and psychosocial evaluation that included a record of medications used, in addition to a complete personal and medical history. The CSHA was a community-based epidemiological study of the prevalence of dementia and its associated risk factors in over 10,000 Canadians. Benzodiazepines were classified according to their half-life: short (under 12 hours), medium (12 to 40 hours) or long half-life (over 40 hours); 35 elderly people were excluded since they were taking more than one class of benzodiazepine. A comprehensive neuropsychological battery that assessed the major domains of cognitive functioning was administered to all participants who completed the CSHA clinical assessment. Neuropsychological test scores for the domains of short- and long-term memory, abstract reasoning, judgement, visuoconstruction, and language formed were the primary independent variables, while gender, age, and years of education were used as covariates in logistic regression models predicting use of each class of drug. Education was not a significant covariate for any analysis. Gender proved to be a significant covariate in the case of the medium-half life drugs, but not for the other two classes. Age was a significant covariate for the majority of test scores for the short and long half-life drugs. After controlling for the covariates, the results showed a broader range of cognitive impairments with the use of short half-life benzodiazepines than with the medium half-life or the long half-life benzodiazepine compounds. Six cognitive measures, assessing abstract reasoning and comprehension, verbal fluency, verbal memory, and visuoconstruction skills (BlockDesign), showed poorer performance among those who used short half-life benzodiazepines, two measures, those of abstract reasoning and comprehension, showed impaired performance by those using medium half-life benzodiazepines, and three measures, for abstract reasoning, verbal memory, and visuoconstruction skills, showed lower performance by those taking long halflife benzodiazepines. Wechsler Similarities, the measure of abstract reasoning, was the only showing significant differences common across all three drug class models. Results are discussed in terms of both the relative extent of lower neuropsychological test scores and the context of increasing evidence of impaired functioning associated with benzodiazepine use.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,221
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0030,005
Études des sciences et des technologies0,0010,001
Communication savante0,0000,001
Science ouverte0,0020,002
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,198
Tête enseignante GPT0,341
Écart entre enseignants0,144 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2011
Routes d'admission1
Résumé présentoui

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