Latent class analysis of intrinsic capacity and its association with quality of life in hospitalized older people with stroke: a cross-sectional study.

Abstract

Objective: This study aimed to identify latent classes of intrinsic capacity among hospitalized older people with stroke and to examine the associations of these classes with stroke-specific quality of life.

Methods: A cross-sectional design was used, and 314 hospitalized older people with stroke were consecutively recruited. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS), comorbidity burden using the Age-adjusted Charlson Comorbidity Index (ACCI), perceived social support using the Perceived Social Support Scale (PSSS), intrinsic capacity across five domains using the Intrinsic Capacity Assessment Tool, and stroke-specific quality of life using the Stroke-Specific Quality of Life Scale (SS-QOL). Latent class analysis identified intrinsic-capacity profiles, and multivariable logistic regression was used to examine factors associated with latent-class membership, and ANOVA was used to compare SS-QOL scores across the identified classes.

Results: LCA identified three latent classes of intrinsic capacity among hospitalized older people with stroke: the low motor-low vitality group (27.70%), the low cognitive-moderate vitality, psychological, and sensory group (17.20%), and the function maintenance group (55.10%). Multinomial logistic regression showed that age, stroke severity, sleep duration, and social support were associated with membership in the low motor-low vitality group, whereas education level was associated with membership in the low cognitive-moderate vitality, psychological, and sensory group. Significant differences were observed in most stroke-specific quality-of-life domains across the identified groups (p < 0.05).

Conclusion: Three distinct intrinsic-capacity profiles were identified among hospitalized older people with stroke, and these profiles were associated with different levels of stroke-specific quality of life. Both clinical and psychosocial factors were associated with profile membership, highlighting the need for targeted interventions to preserve intrinsic capacity and improve quality of life.