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Enregistrement W1600274186 · doi:10.1111/jgs.13506

Outcomes of Cognitive Fluctuations in Dementia Patients

2015· letter· en· W1600274186 sur OpenAlexaffabout
Gwen Li Sin, Brian J. Mainland, Jimmy Lee, Tisha J. Ornstein, Kenneth I. Shulman, Nathan Herrmann

Notice bibliographique

RevueJournal of the American Geriatrics Society · 2015
Typeletter
Langueen
DomaineMedicine
ThématiqueDementia and Cognitive Impairment Research
Établissements canadiensToronto Metropolitan UniversitySunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésDementiaMedicineDeliriumDementia with Lewy bodiesPsychiatryComorbidityGeriatric psychiatryCognitionVascular dementiaDiseaseGerontologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

To the Editor: Cognitive fluctuations (CFs) are defined as spontaneous alterations in cognition, attention, and arousal that can range from transient blackouts to a delirious state and stupor. CFs were originally associated with dementia with Lewy bodies (80–90%)1 but are also present in Alzheimer's disease,2 vascular dementia,3 and Parkinson's disease with dementia.4 Delirium and CFs in dementia share many similarities, yet it is important to differentiate between CFs in dementia and delirium because they have different effects on prognosis and treatment. In addition, delirium in dementia is commonly associated with death and institutionalization.5 This study aimed to assess the degree of CFs and the relationship with subsequent morbidity and mortality in nursing home residents with dementia. It was hypothesized that CFs would be associated with greater mortality and acute care hospitalizations. Residents with dementia at the Sunnybrook Health Sciences Centre Veteran Affairs Canada long-term care unit were recruited. Residents were excluded if they had severe visual or hearing impairment. The research ethics board of Sunnybrook Health Sciences Centre approved the study. Informed consent was obtained from a substitute decision-maker and the resident. Each subject underwent a diagnostic interview by a geriatric psychiatrist (NH) to ensure that Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for dementia were met. Comorbid diagnoses upon recruitment were used to calculate the Charlson Comorbidity Index. All participants were assessed using the Severe Impairment Battery.6 The presence of cognitive fluctuations was determined using the Dementia Cognitive Fluctuation Scale (DCFS).7 All participants were followed prospectively for 6 months. Outcomes of interest were death and hospitalizations. A geriatric psychiatrist (GLS) who was blinded to the presence of CFs obtained the information from the hospital database and chart reviews using a standardized data collection form. A Cox proportional hazards model was used to determine the relationship between CFs and subsequent hospitalization or death. Age, sex, Severe Impairment Battery Total score, and Charlson Comorbidity Index were included a priori in the model as covariates. All analyses were conducted using SPSS 20.0 (SPSS, Inc., Chicago, IL), and statistical significance was set at a two-tailed P-value < .05. The sample characteristics of the 55 participants are shown in Table 1. One participant was lost to follow-up, four required hospitalization (hip fracture (n = 2), pathological femur fracture (n = 1), community-acquired pneumonia (n = 1)), and four (7.3%) died during follow-up (metastatic lung cancer, sepsis, acute renal failure, end-stage Parkinson's disease). Because of the small numbers of participants, both outcomes were combined into a single outcome. Ratings on the DCFS were not significantly different between the groups with and without death and hospitalization (Mann–Whitney U = 134.00, z = −0.79, P = .45). There were also no significant differences in baseline demographic and clinical variables between the two groups. The a priori hypothesized model was not significant in predicting the events (−2 log likelihood = 53.833; chi-square = 1.314, P = .93). CF was not a significant predictor of events over 6 months (hazard ratio = 0.94, 95% confidence interval = 0.65–1.34, P = .71). This is the first study on the short-term prognosis of CFs in dementia. No association was found between CFs and mortality and morbidity, although the factors associated with mortality and morbidity for institutionalized individuals with end-stage dementia remains unclear. Factors such as age, sex, and type of dementia have been inconsistently identified as predictors of mortality.8 A limitation of this study was the small sample size and small number with death and hospitalization. Previous studies examining 6-month survival in nursing home residents with advanced dementia found 6-month mortality to range from 18.3%9 to 56.3%,10 but the current study's mortality over an identical time period was unexpectedly low. It is difficult to differentiate between CFs and delirium and what was rated as CFs could well have been symptoms of delirium, although the subjects were well known to the primary caregivers and were not reported to display any acute behavioral or cognitive change during recruitment. Although it is possible that CFs herald the onset of delirium and its consequences, if anything, this should have biased the study in favor of finding an association between CFs and negative outcomes. The original DCFS study involved younger community-dwelling individuals,7 and respondents for the DCFS in the current study were nursing home staff, rather than caretakers of individuals with dementia recruited through outpatient dementia referrals, as in the original study.7 These methodological differences may have limited the validity of using the DCFS to assess for CFs in the current study sample. CFs occur commonly in dementia of all types. Although similar in presentation to delirium, it is yet to be determined whether CFs are associated with the negative outcomes attributable to delirium in dementia. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. J. Lee was supported by the Singapore Ministry of Health's National Medical Research Council (Grant NMRC/TA/002/2012). Author Contributions: Herrmann, Shulman, Ornstein, Mainlaind, Sin: study concept and design. Herrmann, Mainland, Sin: acquisition of subjects and data. Mainland, Herrmann, Lee, Sin: data analysis and interpretation. All authors were involved in preparation of the manuscript. Sponsor's Role: There was no sponsor.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,002
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,014
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0020,002
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 Opus0,019
Tête enseignante GPT0,319
Écart entre enseignants0,300 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations2
Publié2015
Routes d'admission2
Résumé présentoui

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