Abstract

Introduction: Research on the trajectory of survivors’ quality of life over time has generally focused on the first six months post-stroke, and results are inconsistent. Indeed, while some studies found an improvement of the stroke survivors’ quality of life from one to six months post-stroke, other studies showed an improvement during inpatient rehabilitation but a worsening at six months after discharge. Aim: To investigate the longitudinal growth trajectories of disease-specific quality of life dimensions and their predictors over one year. Methods: A multicentric longitudinal design were used for this study. Four hundred and fifteen stroke survivors (mean age 70.6 + 12.2 years; 81% ischemic stroke) were recruited after discharge from rehabilitation hospitals and were followed up every three months for one year. Changes in stroke impact scale dimension scores were evaluated using hierarchical linear models and linear, logarithmic, quadratic, and cubic time slope. Results: We observed a significant linear and quadratic increase in most stroke impact scale dimensions from the baseline to 12-month follow-up. The communication dimension was stable over time, while the memory dimension increased only linearly. Higher physical dimensions scores were predicted by lower age, hypercholesterolemia, and better physical functioning at baseline, while higher communication was predicted by lower age, better physical functioning, and a diagnosis of peripheral vascular disease. Better memory was predicted by lower age, married status, better physical functioning, and left-hemisphere stroke. Better participation was predicted by lower age and better physical functioning. No predictors were observed for emotion. Conclusions: Disease-specific quality of life significant increase from the baseline to 12-month follow-up, especially in physical dimensions. Lower age, hypercholesterolemia, better physical functioning and diagnosis of peripheral vascular disease seem to be predictors or better quality of life. Through the analyses of predictors, we identified stroke survivors who are more at risk and who need more tailored interventions to improve quality of life.

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