Abstract 2828: Caregivers And Their Impact On Inpatient Rehabilitation Efficiency And Effectiveness Amongst Recent Stroke Survivors In An Urbanised Asian Society
Notice bibliographique
Résumé
Introduction: Cross-cultural differences could influence the relationship between caregiving and rehabilitation outcomes in stroke survivors between different societies. We aimed to determine independent factors of rehabilitation effectiveness (REs) and rehabilitation efficiency (REy) amongst recent stroke survivors in Singapore, and examine if having a caregiver affected these outcomes. Methods: We retrospectively studied all stroke patients fulfilling inclusion criteria (n=3796) from all Singaporean rehabilitation hospitals from 1996-2005. We used backward mixed model linear regression (multivariate) to test the relationship between independent variables and REs and REy. Admission and discharge Shah-modified Barthel Indices were used to calculate REs and REy. We further explored the effect of caregiver availability, number of caregivers, and relationship of caregiver to patient on REs and REy. Mixed logistic regression identified independent predictors of caregiver availability and caregiver relationship to patient, mixed Poisson modelling identified independent predictors of caregiver number; mixed linear regression identified the relationship of REy and REs with caregiver factors. Results: Having a caregiver independently predicted poorer REs and log REy; other predictors included older age, Malay ethnicity, ischemic stroke, longer time to admission, dementia. Within our population, 95.8% (3640/3796) had caregivers and 94.2% (3429/3640) of them provided physical care (defined as primary caregivers). Of patients with primary caregivers, 41.2% relied on live-in hired help (foreign domestic workers, FDWs), 27.6% on spouses and 21.6% on first-degree relatives. Independent factors associated with caregiver availability and number were older age, female, being married, higher socioeconomic status, and having a religion (all p<0.05). Compared to those who had spouse as primary caregiver, having a child or parent (β=-4.1, 95%CI=-8.0 to -0.1, p=0.042) or FDW (β=-6.9, 95%CI=-9.9 to -3.9, p<0.001) as primary caregiver were predictive of poorer REs, while having a child or parent (β=-0.140, 95%CI=-0.280 to 0.001, p=0.052) or FDW (β=-0.110, 95%CI=-0.210 to -0.001, p=0.048) as primary caregiver were predictive of poorer log REy. Conclusions: In this Asian population, having a caregiver was surprisingly associated with poorer REs and REy in stroke patients, perhaps due to differing socio-cultural contexts; only 49.2% of patients depended on spouse/near relatives as primary caregivers, compared with higher estimates in Western populations. REs further declined with decreasing closeness of relationship between primary caregiver and patient, and REy was poorer in patients with hired help as primary caregivers. Perhaps the role of hired help in stroke caregiving should be re-thought, as dependence on FDWs is high in many Asian cities due to population ageing.
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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 | 0,001 | 0,003 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».