Use of the FRAIL Questionnaire in Patients With End-Stage Kidney Disease
Notice bibliographique
Résumé
Background: Frailty is a clinical phenotype of decreased physiologic reserve that is associated with increased morbidity and mortality. The most meaningful way to assess frailty in patients with end-stage kidney disease (ESKD) is unknown. Objective: To assess the prevalence of frailty in ESKD patients using the easy-to-administer FRAIL scale and, to determine its association with mortality, transplantation, and hospitalization. Design: A cohort study was used. Setting: The Ottawa Hospital, Ottawa, Ontario, Canada, was the setting of this study. Patients: All eligible adult ESKD patients treated with dialysis from August to November 2017 at The Ottawa Hospital were invited to participate. Measurements: The FRAIL scale. Methods: Eligible patients completed an exercise survey with FRAIL questions embedded within the instrument. Number of comorbid illnesses was determined from the electronic medical record and weight loss was calculated from target weight in the patients’ dialysis prescription. Mortality, transplant status, and hospitalizations were ascertained from the electronic medical record 18 months later; differences by frailty status were evaluated using descriptive statistics. Kaplan-Meier and Cox regression models were used to examine the association between frailty and transplant. Results: Of 476 ESKD patients screened, 261 participated; 101 receiving peritoneal dialysis, 135 intermittent hemodialysis, and 25 home hemodialysis. Thirty-nine, 145, and 77 were frail, pre-frail, and not frail, respectively. Employment status, ethnicity, and comorbid illnesses differed significantly by frailty status, but mortality did not. In univariate analysis, frail patients were less likely to be listed for ( P = .05) and to receive a kidney transplant ( P = .02). However, after adjusting for age and modality, frailty was not statistically associated with a decreased likelihood of transplant (Hazard Ratio: 0.15; confidence interval [CI], 0.02-1.15; P = .068). The results were similar when accounting for the competing risk of death ( P = .060). Frail patients were more likely to be hospitalized ( P = .01) and spend more time in the hospital ( P = .04). Limitations: Single-center design with a relatively short follow-up and small sample size limiting the number of variables that could be assessed in analysis. We also excluded patients who were unable to communicate in English or French and those patients with physical limitations such as amputations, potentially affecting generalizability. Conclusions: Frail ESKD patients as identified by the FRAIL scale are less likely to receive a renal transplant; this association diminished statistically after adjusting for age and modality and when accounting for the competing risk of death. Frail patients were at increased risk of hospitalization. Further study with larger patient numbers and longer follow-up is needed to determine the usefulness of the FRAIL scale in predicting adverse outcomes. Trial registration: Not required as this was an observational study.
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 | 0,004 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 ».