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中华养生保健 ›› 2024, Vol. 42 ›› Issue (12): 5-9.

• 论著 • 上一篇    下一篇

永久心脏起搏器植入术后患者自我管理能力影响因素分析与干预模型的构建

朱瑜1, 史超2,*   

  1. 1.新疆医科大学健康管理学院,新疆 乌鲁木齐,830054;
    2.新疆医科大学第一附属医院护理部,新疆 乌鲁木齐,830054
  • 出版日期:2024-06-16 发布日期:2024-06-14
  • 通讯作者: *史超,E-mail:1209386992@qq.com。
  • 作者简介:朱瑜(1994—),女,汉族,籍贯:新疆维吾尔自治区乌鲁木齐市,硕士研究生在读,研究方向:心血管护理、健康管理。
  • 基金资助:
    新疆维吾尔自治区护理学会基金项目(2023XH029); 新疆维吾尔自治区研究生创新项目(XJ2023G200)

Analysis of Factors Influencing Patients' Self-Management Ability after Permanent Pacemaker Implantation and Construction of an Intervention Model

ZHU Yu, SHI Chao   

  1. 1. College of Health Management, Xinjiang Medical University, Urumqi 830054, China;
    2. Department of Nursing, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China
  • Online:2024-06-16 Published:2024-06-14

摘要: 目的 了解永久心脏起搏器植入术后患者的自我管理能力现状,分析相关影响因素,通过影响因素权重构建干预模型。方法 选择2020年1月—2023年1月在新疆医科大学第一附属医院心脏内科行永久起搏器植入术的210例患者作为研究对象,采用问卷调查法收集患者术后6个月的自我管理能力情况,应用单因素和Logistic回归分析探讨患者术后自我管理能力的影响因素。根据分析结果构建干预模型,采用ROC曲线对模型条目的可行性进行验证。结果 患者自我管理能力普遍较差(得分率为60.23%);单因素分析结果显示,年龄、患病病程、文化程度等9项因素是患者术后自我管理能力的影响因素;Logistic回归分析结果表明,有并发症、文化程度为小学及以下的、无慢性病等6项因素是自我管理能力较低的独立因素;通过对Logistic回归中危险系数(权重)及ROC曲线结果分析,初步建立以提高“有并发症、小学及以下文化程度、慢性病史及病程≤5年”的患者术后自我管理能力的干预模型。结论 基于循证理念构建心脏起搏器植入术后患者自我管理干预模型,对术后患者自我管理能力的提升具有良好的理论和实践价值。

关键词: 永久起搏器植入术, 自我管理能力, 干预模型

Abstract: Objective To understand the current status of self-management ability of patients after permanent pacemaker implantation, analyze the relevant influencing factors, and construct an intervention model by weighting the influencing factors. Methods A total of 210 patients who underwent permanent pacemaker implantation in the Department of Cardiology of a tertiary hospital in Xinjiang from January 2020 to January 2023 were selected as the study subjects, and the questionnaire method was used to collect the self-management ability of the patients in the 6 months after the operation, and the influencing factors of the patients' self-management ability after the operation were investigated by using univariate and logistic regression analysis. The intervention model was constructed according to the analysis results, and the feasibility of the model entries was verified by using ROC curves. Results The patients' self-management ability was generally poor (score of 60.23%); the results of univariate analysis showed that 9 factors, including age, disease duration, and literacy level, were the influencing factors of the patients' self-management ability after surgery; the results of logistic regression analysis showed that 6 factors, including the presence of complications, the literacy level of elementary school and below, and the absence of chronic diseases, were the independent factors affecting the low self-management ability. By analyzing the results of logistic regression risk factors (weights) and ROC curves, the preliminary model was established to improve the ability of "patients with complications,The intervention model of postoperative self-management ability of patients with "elementary school education or below, chronic disease history and disease duration ≤5 years" was constructed. Conclusion Constructing a self-management intervention model for patients after pacemaker implantation based on evidence-based concepts has good theoretical and practical value for the improvement of self-management ability of postoperative patients.

Key words: Permanent Pacemaker Implantation, Self-management Ability, Intervention Modeling

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