P1582THE BURDEN OF FRAILTY ON MOOD, COGNITION, QUALITY OF LIFE AND LEVEL OF INDEPENDENCE IN PATIENTS ON HEMODIALYSIS
Notice bibliographique
Résumé
Abstract Background and Aims Frailty is an all-embracing syndrome of diminished physiological reserve to stressors resulting in reduced physical ability and increased vulnerability to hospitalization and mortality. There is data on cross-sectional frailty assessments and its subsequent relationship to mobility, quality of life, depression, cognitive decline, nursing home admissions, and disability. The most widely used definition in the literature is known as the Fried Frailty Phenotype. It is based on five physical domains that can be assessed by self-report (weight loss, low physical activity, and exhaustion) and objective measures (weakness and slow gait speed). Based on the number of deficits, individuals are characterized as robust (0), pre-frail (1-2/5) and frail (≥ 3/5). The prevalence of frailty is disproportionately increased in patients with chronic kidney disease (CKD) in comparison to non-CKD counterparts and is the highest in patients on hemodialysis. While the cross-sectional measurement of frailty on hemodialysis patients has been associated with adverse clinical events, there is a paucity of data on longitudinal assessment of frailty and its relationship to outcomes. The primary objective of the study was to evaluate the change in frailty status in patients on hemodialysis over 12 months in relation to the level of independence. The secondary objective was to determine the changes in frailty and explore a relationship with mood, quality of life, and cognition. Method We conducted a prospective cohort study amongst 100 prevalent hemodialysis patients at the Regina General Hospital, Saskatchewan, Canada between January 2015 and January 2017. The patients underwent frailty assessments at baseline and one year later. 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 quality of life were measured using questionnaires [Montreal Cognitive Assessment (MoCA), Geriatric Depression Score (GDS), and EuroQol (EQ-5D) utility scores and Visual Analogue Scores (VAS) respectively]. 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 non-frail (composite of robust and pre-frail) of groups using Mann–Whitney test or Chi-square test/ Fisher’s exact test where appropriate. Results 97/100 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 relocated. 18/22 (82%) who died were frail. At baseline, 68% were frail, 27% were pre-frail and 5% were robust. At baseline, 69% had MoCA score≥ 24, 53% had GDS score≥ 2, median EQ-5D utility score was 0.80 (0.70-0.85), median EQ-VAS was 60 (44-80). 82% of the patients were independent, 17% were independent with support, and 1% required support from home care. Even though death was not a pre-specified endpoint, we found that a fifth of our patients (22/100) patients had died by the time of the next assessment in 12 months. 18/22 (82%) had been identified as frail suggesting majority of the deaths had occurred in frail patients. Conclusion To our knowledge, this is the first Canadian study that explores the relationship between longitudinal changes in frailty with the level of independence, mood, cognition, and quality of life. We show high prevalence (95%) of frail and pre-frail status at baseline which remained unchanged one year later. Frail patients on dialysis were older, had challenges with mobility and self-care in comparison to their non-frail counterparts. Frailty and pre-frailty is near-ubiquitous in our dialysis patients and will need to be proactively addressed to improve subsequent healthcare 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 | 0,000 | 0,002 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,003 | 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 ».