The Burden of Frailty on Mood, Cognition, Quality of Life, and Level of Independence in Patients on Hemodialysis: Regina Hemodialysis Frailty Study
Notice bibliographique
Résumé
Background: The prevalence of frailty is disproportionately increased in patients with chronic kidney disease (CKD) in comparison with non-CKD counterparts and is the highest in patients on hemodialysis (HD). While the cross-sectional measurement of frailty on HD has been associated with adverse clinical events, there is a paucity of data on longitudinal assessment of frailty and its relationship to outcomes. Objective: The objectives were to (1) evaluate changes in frailty status, level of independence, mood, cognition, and quality of life (QoL) over a 12-month period and (2) explore the relationship between frailty status and level of independence, mood, cognition, and QoL at 2 different time points (at baseline and at 1 year). Design: This is a prospective cohort study involving 100 prevalent HD patients. Setting: Regina General Hospital and Wascana Dialysis Unit in Regina, Saskatchewan, Canada, between January 2015 and January 2017. Patients: One hundred prevalent HD patients underwent frailty assessments using the Fried criteria at baseline and 1 year later. Measurements: Frailty was assessed using the Fried criteria, which included assessments of unintentional weight loss, weakness (handgrip strength), slowness (walking speed), and questionnaires for physical activity and self-perceived exhaustion. Cognition, mood, and QoL were measured using questionnaires (Montreal Cognitive Assessment [MoCA], Geriatric Depression Scale [GDS], and EuroQol [EQ-5D] utility scores and visual analog scale [VAS], respectively). Methods: Frailty status was reported as a binary variable: frail vs. nonfrail (prefrail and robust). Differences across baseline and 1-year groups were assessed using McNemar’s test or Wilcoxon signed-rank test, as appropriate. We assessed the differences between frail and nonfrail groups using the Mann–Whitney U test or chi-square test/Fisher’s exact test where appropriate. Results: Ninety-seven of the 100 patients had complete initial assessments. The median (interquartile range [IQR]) duration of dialysis at baseline was 35.5 (13.75-71.75 months). One year later, 22 had died, 10 refused assessments, and 3 had relocated. In comparison with baseline vs 1 year, the number of frail patients was 68.1% vs. 67.7%; prefrail 26.8% vs. 26.1%; robust 5.1% vs. 6.2%; MoCA ≥24, 69% vs. 64.5%; GDS score ≥ 2, 52.8% vs. 47.7%; median EQ-5D utility score 0.81 vs. 0.77; and median EQ-VAS 60 vs. 50. Similarly, in comparison with baseline vs. 1 year, the number of independent patients was 82% vs. 63%, independent with support 17% vs. 31%, and long-term care home 0% vs. 3.1%. Eighteen of the 22 patients (82%) who died were frail. At 1 year, the median (IQR) MoCA was 24 (19-25) vs. 25 (21-26; P = .039) and median (IQR) GDS was 2 (1-3) vs. 1(0-2; P = .034). Likewise, median (IQR) EQ-5D utility score was 0.78 (0.6-0.82) vs. 0.81 (0.78-0.85; P = .023). There were significant changes in self-care (27% vs. 0%), P = 0.006, and daily activities (68.2% vs. 38.1%), P = 0.021. Limitations: This is a single-center study, so direct inferences must be interpreted in the context of the demographics of the study population. Patients were undergoing dialysis for a median of 36 months before undergoing initial assessment. Conclusions: Frailty and prefrailty in our dialysis patients is near-ubiquitous and will need to be proactively addressed to improve subsequent health care outcomes.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 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 ».