• 1. School of Health Services and Management, Shanxi University of Chinese Medicine, Taiyuan 030619, P. R. China;
  • 2. National International Joint Research Center for Molecular Chinese Medicine, Shanxi Key Laboratory of Chinese Medicine Encephalopathy, Shanxi University of Chinese Medicine, Taiyuan 030619, P. R. China;
  • 3. Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, Shanxi Medical University, Taiyuan 03001, P. R. China;
ZHANG Yanbo, Email: sxmuzyb@126.com
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Objective To categorize and describe stroke-patients based on factors related to patient reported outcomes. Methods A questionnaire survey was conducted among stroke-patients in nine hospitals and communities in Shanxi Province. The general information questionnaire and stroke-patient reported outcome manual (Stroke-PROM) were completed. Latent profile analysis was used to analyze the scores of Stroke-PROM, and the explicit variables of the model were the final scores of each dimension. ANOVA and correlation analysis were used to measure the correlation between the factors and subtypes. Results Four unique stroke-patient profiles emerged, including a low physiological and low social group (9%), a high physiological and middle social group (40%), a middle physiological and middle social group (26%), and a middle physiological and high social group (25%). There were significant differences in scores of four areas among patients with different subtypes (P<0.05). Moreover, there was a correlation between age, payment, exercise and subtypes (P<0.05). Conclusion There are obvious grouping characteristics for stroke patients. It is necessary to focus on stroke patients who are advanced in age, have a self-funded status and lack exercise, and provide targeted nursing measures to improve their quality of life.

Citation: YANG Jie, ZHANG Yao, YAN Juanjuan, PEI Zhongyang, HU Anxia, ZHANG Yanbo. Exploring heterogeneity of stroke-patients with latent class analysis based on patient reported outcomes. Chinese Journal of Evidence-Based Medicine, 2023, 23(4): 379-385. doi: 10.7507/1672-2531.202210150 Copy

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