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Journal of Nursing ›› 2024, Vol. 31 ›› Issue (6): 6-12.doi: 10.16460/j.issn1008-9969.2024.06.006

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Multidimensional frailty development trajectory and its influencing factors in middle-aged and elderly stroke patients

XUE Rong1, ZHANG Kai-li1, CHEN Bao-yun2a, MA Rong-hui2b, ZHANG Yu-xin1   

  1. 1. School of Nursing, Xuzhou Medical University, Xuzhou 221000, China;
    2a. Dept. of Nursing Administration; 2b. Dept. of Neurology, Xuzhou Central Hospital, Xuzhou 221009, China
  • Received:2023-11-26 Online:2024-03-25 Published:2024-04-08

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Abstract: Objective To explore the development trajectory of multidimensional frailty in middle-aged and elderly stroke patients and its influencing factors, and to provide theoretical basis for clinical staff to carry out frailty intervention. Methods Middle-aged and elderly stroke patients hospitalized in the Department of Neurology of a tertiary Grade-A hospital in Xuzhou City from October to December 2022 were selected as the study objects. The general information questionnaire, Zung Self-rating Anxiety Scale and Zung Self-rating Depression Scale were used to collect the baseline data of the patients. Tilburg Frailty Scale was used to collect the multidimensional frailty score of the patients 48 hours after admission, 3 months and 6 months after discharge, and the potential category growth model to explore the category of multidimensional frailty development trajectory of middle-aged and elderly stroke patients. Disordered multi-classification Logistic regression and decision tree model were used to analyze and identify the influencing factors of trajectory category. Results The multidimensional frailty development of middle-aged and elderly stroke patients could be divided into three categories: non-frail and stable group (42.8%), low level of frailty with rapid increase (36.3%) and high level of frailty with slow increase (20.9%). Logistic regression analysis showed that age, marital status, educational level, stroke severity score, comorbidity score, activity of daily living score and anxiety were the influencing factors of multidimensional frailty development trajectory in middle-aged and elderly stroke patients (P<0.05). Further analysis of decision tree model showed that the activity of daily living score was the most important factor, followed by anxiety and stroke severity score. Conclusion In this study, multidimensional frailty development trajectory of 3 categories of middle-aged and elderly stroke patients is identified, which verify the heterogeneity of frailty development. In the future, medical personnel can identify the development trajectory of multidimensional frailty in different categories of patients through screening, develop targeted frailty intervention and home frailty management programs, and delay or even reverse multidimensional frailty.

Key words: middle-aged and elderly people, stroke, multidimensional frailty, trajectory, latent class growth model

CLC Number: 

  • R473.74
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