冠心病患者经皮冠状动脉介入术后自我管理能力的影响因素分析及列线图模型构建

Influencing factors of self-management ability of coronary heart disease patients after percutaneous coronary intervention and construction of nomogram model

  • 摘要:
    目的 分析冠心病患者经皮冠状动脉介入术(PCI)治疗后自我管理能力的影响因素并构建列线图模型。
    方法 选取行PCI治疗的247例冠心病患者作为研究对象,均接受冠心病自我管理行为量表(CSMS)评估。通过多因素Logistic回归分析筛选出冠心病患者PCI治疗后自我管理能力的独立影响因素,应用R软件构建列线图模型,采用受试者工作特征(ROC)曲线、校准曲线和Hosmer-Lemeshow拟合优度检验评估列线图模型的区分度、校准度和拟合效度。
    结果 247例患者的平均CSMS评分为(86.79±9.22)分,以86.79分为临界值将患者分为低分组89例、高分组158例; 低分组年龄、受教育程度、家庭人均月收入、自我效能与高分组比较,差异有统计学意义(P < 0.05)。多因素Logistic回归分析结果显示,年龄、受教育程度、家庭人均月收入、自我效能为冠心病患者PCI治疗后自我管理能力的独立影响因素(P < 0.05); 基于4个影响因素构建列线图模型发现,年龄>70岁增加86.2分权重,受教育程度为高中以下增加87.4分权重,家庭人均月收入 < 3 500元人民币增加82.3分权重,自我效能较低增加99.6分权重。ROC曲线分析结果显示,列线图模型预测冠心病患者PCI治疗后自我管理能力的曲线下面积为0.842(95%CI: 0.794~0.890); 校准曲线斜率接近1, 拟合优度检验χ2=10.226、P=0.233。
    结论 年龄、受教育程度、家庭人均月收入、自我效能为冠心病患者PCI治疗后自我管理能力的影响因素, 据此构建的列线图模型对自我管理能力具有较高的预测价值。

     

    Abstract:
    Objective To analyze the influencing factors of self-management ability of coronary heart disease patients after percutaneous coronary intervention (PCI) and construct a nomogram model.
    Methods A total of 247 CHD patients who underwent PCI were selected as the research subjects, and all of them were evaluated by Coronary Heart Disease Self-management Scale (CSMS). Multivariate Logistic regression analysis was used to screen out the independent influencing factors of self-management ability of CHD patientsafter PCI, and R software was used to construct a nomogram model. The discrimination, calibration, and goodness-of-fit of the nomogram model were evaluated by receiver operating characteristic (ROC) curve, calibration curve, and Hosmer-Lemeshow goodness-of-fit test.
    Results The average CSMS score of 247 patients was (86.79±9.22), and these patients were divided into low-score group(89 patients) and high-score group (158 patients)based on the critical value of 86.79 points. There were significant differences in age, education level, monthly per capita family income, and self-efficacy between the low-score group and the high-score group (P < 0.05). Multivariate Logistic regression analysis showed that age, education level, monthly per capita family income, and self-efficacy were independent influencing factors of self-management ability of CHD patients after PCI (P < 0.05). The nomogram model constructed based on the four influencing factors found that age >70 years increased the weight by 86.2 points, education level below high school increased the weight by 87.4 points, monthly per capita family income < 3 500 yuan increased the weight by 82.3 points, and low self-efficacy increased the weight by 99.6 points. The results of ROC curve analysis showed that the area under the curve of the nomogram model for predicting self-management ability ofCHD patients after PCI was 0.842 (95%CI, 0.794 to 0.890). The slope of the calibration curve was close to 1, and the results of goodness-of-fit test was as follows: χ2=10.226, P=0.233.
    Conclusion Age, education level, monthly per capita family income, and self-efficacy are influencing factors of self-management ability of CHD patients after PCI, and the nomogram model constructed based on these factors has high predictive value for self-management ability.

     

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