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Enregistrement W4379051786 · doi:10.1016/j.xkme.2023.100684

Frailty and Clinical Outcomes in Patients Treated With Hemodialysis: A Prospective Cohort Study

2023· article· en· W4379051786 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
fundUn bailleur canadien est enregistré sur le travail.
aboutLe titre ou le résumé porte un signal canadien du lexique géographique.

Notice bibliographique

RevueKidney Medicine · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueDialysis and Renal Disease Management
Établissements canadiensUniversity of TorontoUniversity of British ColumbiaUniversity of AlbertaUniversity of Calgary
Organismes subventionnairesCanadian Institutes of Health ResearchCanada Foundation for Innovation
Mots-clésHemodialysisMedicineProspective cohort studyCohortCohort studyInternal medicineIntensive care medicine

Résumé

récupéré en direct d'OpenAlex

Rationale and ObjectiveFrailty is common among people with kidney failure treated with hemodialysis (HD). The objective was to describe how frailty evolves over time in people treated by HD, how improvements in frailty and frailty markers are associate with clinical outcomes, and the characteristics that are associated with improvement in frailty.Study DesignProspective cohort study.Setting and ParticipantsAdults initiating thrice weekly in-center HD in Canada.ExposureWe classified frailty using a 5-point score (3 or more indicates frailty) based on physical inactivity, slowness or weakness, poor endurance or exhaustion, and malnutrition. We categorized the frailty trajectory as never present, improving, deteriorating, and always present.OutcomesAll-cause death, hospitalizations, and placement into long-term care.Analytical ApproachWe examined the association between time-varying frailty measures and these outcomes using Cox and negative binomial models, after adjustment for potential confounders.Results985 participants were included and followed up for a median of 33 months; 507 (51%) died, 761 (77%) experienced ≥1 hospitalization and 115 (12%) entered long-term care. Overall, 760 (77%) reported frailty during follow-up. Three-quarters (78%) of those with frailty at baseline remained frail throughout the follow-up, 46% without baseline frailty became frail, and 23% with baseline frailty became nonfrail. Higher frailty scores were associated with an increased risk of mortality (fully adjusted HR, 1.58 per unit; 95% CI, 1.39-1.80) and an increased rate of hospitalization (RR, 1.16 per unit; 95% CI, 1.09-1.23). Compared with those who were frail throughout the follow-up, participants with frailty at baseline but improving during follow-up showed a lower mortality (HR, 0.59; 95% CI, 0.42-0.81), and a lower rate of hospitalization (RR, 0.70; 95% CI, 0.56-0.87).LimitationsThere was missing data on frailty at baseline and during follow-up.ConclusionsFrailty was associated with a higher risk of poor outcomes compared with those without frailty, and participants whose status improved from frail to nonfrail showed better clinical outcomes than those who remained frail. These findings emphasize the importance of identifying and implementing effective treatments for frailty in patients receiving maintenance HD. Frailty is common among people with kidney failure treated with hemodialysis (HD). The objective was to describe how frailty evolves over time in people treated by HD, how improvements in frailty and frailty markers are associate with clinical outcomes, and the characteristics that are associated with improvement in frailty. Prospective cohort study. Adults initiating thrice weekly in-center HD in Canada. We classified frailty using a 5-point score (3 or more indicates frailty) based on physical inactivity, slowness or weakness, poor endurance or exhaustion, and malnutrition. We categorized the frailty trajectory as never present, improving, deteriorating, and always present. All-cause death, hospitalizations, and placement into long-term care. We examined the association between time-varying frailty measures and these outcomes using Cox and negative binomial models, after adjustment for potential confounders. 985 participants were included and followed up for a median of 33 months; 507 (51%) died, 761 (77%) experienced ≥1 hospitalization and 115 (12%) entered long-term care. Overall, 760 (77%) reported frailty during follow-up. Three-quarters (78%) of those with frailty at baseline remained frail throughout the follow-up, 46% without baseline frailty became frail, and 23% with baseline frailty became nonfrail. Higher frailty scores were associated with an increased risk of mortality (fully adjusted HR, 1.58 per unit; 95% CI, 1.39-1.80) and an increased rate of hospitalization (RR, 1.16 per unit; 95% CI, 1.09-1.23). Compared with those who were frail throughout the follow-up, participants with frailty at baseline but improving during follow-up showed a lower mortality (HR, 0.59; 95% CI, 0.42-0.81), and a lower rate of hospitalization (RR, 0.70; 95% CI, 0.56-0.87). There was missing data on frailty at baseline and during follow-up. Frailty was associated with a higher risk of poor outcomes compared with those without frailty, and participants whose status improved from frail to nonfrail showed better clinical outcomes than those who remained frail. These findings emphasize the importance of identifying and implementing effective treatments for frailty in patients receiving maintenance HD.

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.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,016
Score d'incertitude au seuil0,460

Scores Codex et Gemma par catégorie

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

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 Opus0,024
Tête enseignante GPT0,330
Écart entre enseignants0,306 · 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