Latent transitions in quality of life and the influencing factors among patients with first-ever ischemic stroke: a prospective longitudinal study.

BACKGROUND

Ischemic stroke (IS) is the second leading cause of death and disability globally, with quality of life (QoL) post-stroke influenced by various factors. Conventional static analytical approaches fail to capture the dynamic transitions between health states over time. This study aimed to characterize the temporal evolution of distinct QoL phenotypes and elucidate the phase-specific mechanisms driving these transitions.

METHODS

In this prospective longitudinal study, 442 patients with first-ever IS were assessed for QoL using the Stroke-Specific Quality of Life Scale (SS-QoL) at the acute phase (T0), 1 month (T1), 3 months (T2), and 6 months (T3). Latent Profile Analysis (LPA) was utilized to identify distinct QoL phenotypes, while Latent Transition Analysis (LTA) modeled the probabilities of shifting between latent states. Multi-period Firth’s penalized logistic regression was employed to identify stage-specific determinants of improvement or deterioration across recovery intervals.

RESULTS

Three distinct QoL classes (high, moderate, and low) were identified at four time points. The high QoL class exhibited stability but was vulnerable to late declines, while the moderate QoL class showed frequent fluctuations. The low QoL class showed potential for improvement but was at risk for persistent poor outcomes. During the T0-T1 period, improvement was significantly impeded by metabolic and physiological burdens—specifically elevated LDL (β = -0.495, p = 0.013), venous thromboembolism risk (β = -0.990, p = 0.008), and higher Body Roundness Index (β = -0.424, p = 0.001)—but facilitated by left-sided hemiparesis (β = 0.746, p = 0.032). For the transition in the T1-T2 phase, higher LDL levels (β = 0.793, p = 0.047) significantly increased the odds of deterioration, whereas higher total cholesterol (β = -0.620, p = 0.022) reduced it. During the T2-T3 period, resilience (β = -0.054, p = 0.012) and greater functional exercise adherence at 6 months (β = -0.035, p = 0.007) were linked to reduced deterioration.

CONCLUSIONS

Transitions between post-stroke QoL states are driven by divergent determinants across recovery phases. The management of IS should follow a continuous, phased approach that prioritizes early control of vascular and metabolic risk factors, sustained engagement in functional rehabilitation over the long term, and systematic integration of psychological support in the later stages, in order to optimize long-term QoL.