张学斌, 吴德喜, 段宇, 蔺杰, 孙冬冬. 急性冠脉综合征合并2型糖尿病患者PCI术后一年非计划再入院预测模型构建[J]. 心脏杂志, 2024, 36(1): 21-27. DOI: 10.12125/j.chj.202306051
    引用本文: 张学斌, 吴德喜, 段宇, 蔺杰, 孙冬冬. 急性冠脉综合征合并2型糖尿病患者PCI术后一年非计划再入院预测模型构建[J]. 心脏杂志, 2024, 36(1): 21-27. DOI: 10.12125/j.chj.202306051
    shu
    ZHANG Xue-bin, WU De-xi, DUAN Yu, LIN Jie, SUN Dong-dong. A risk nomogram model for predicting readmission after percutaneous coronary intervention within one year in type 2 diabetes mellitus patients with acute coronary syndrome[J]. Chinese Heart Journal, 2024, 36(1): 21-27. DOI: 10.12125/j.chj.202306051
    Citation: ZHANG Xue-bin, WU De-xi, DUAN Yu, LIN Jie, SUN Dong-dong. A risk nomogram model for predicting readmission after percutaneous coronary intervention within one year in type 2 diabetes mellitus patients with acute coronary syndrome[J]. Chinese Heart Journal, 2024, 36(1): 21-27. DOI: 10.12125/j.chj.202306051
    shu

    急性冠脉综合征合并2型糖尿病患者PCI术后一年非计划再入院预测模型构建

    A risk nomogram model for predicting readmission after percutaneous coronary intervention within one year in type 2 diabetes mellitus patients with acute coronary syndrome

      摘要
    • 摘要:
      目的 研究分析急性冠脉综合征合并2型糖尿病患者PCI术后一年内再入院的影响因素，并构建临床预测模型。
      方法 收集2019年1月～2022年1月就诊于西京医院心血管内科的急性冠脉综合征合并2型糖尿病，且行PCI后顺利出院患者的病历资料。依据患者在出院后一年内是否因主要不良心血管事件再入院分为再入院组和未再入院组。多因素Logistic回归分析患者再入院的影响因素，并构建预测模型。
      结果 多因素Logistic回归分析显示，年龄（OR=1.064, 95%CI: 1.059～1.096）、住院天数（OR=1.109, 95%CI: 1.053～1.169）、糖尿病史 >20年（OR=2.005, 95%CI: 1.346～2.959）、胱抑素C（OR=1.699, 95%CI: 1.299～2.239）、射血分数（OR=0.975, 95%CI: 0.958～0.992）、多血管病变（ OR=1.744, 95%CI: 1.270～2.422）和 ST/ T波改变（OR=1.920, 95%CI: 1.419～2.612），是急性冠脉综合征合并2型糖尿病患者PCI术后一年内再入院的影响因素。基于多因素Logistic回归分析结果构建急性冠脉综合征合并2型糖尿病患者PCI术后一年内再入院的风险预测列线图模型，ROC曲线下面积（AUC）为0.7874（95% CI: 0.7597～0.8152）。
      结论 年龄、住院天数、糖尿病史>20年、胱抑素C、射血分数、多血管病变和ST/T波改变是急性冠脉综合征合并2型糖尿病患者PCI术后一年内再入院的危险因素。临床预测模型评价显示具有较好的区分度和校准度，可作为临床早期预测再入院风险的工具。

       

      Abstract:
      AIM To investigate and evaluate the risk factors associated with readmission within one year after percutaneous coronary intervention (PCI) in patients diagnosed with acute coronary syndrome and type 2 diabetes mellitus and to develop a clinical prediction model.
      METHODS A retrospective medical data analysis was conducted in patients diagnosed with acute coronary syndrome and type 2 diabetes mellitus and discharged after successful PCI between January 2019 and January 2022. The patients were categorized into a readmission group or a non-readmission group based on their hospital readmission status due to major cardiovascular adverse events within a year after PCI. The risk factors associated with the readmission were analyzed using logistic regression.
      RESULTS The findings of multivariate logistic regression analysis indicated that age (OR = 1.064, 95% CI: 1.059～1.096), hospitaldays (OR = 1.109, 95% CI: 1.053～1.169), historyof diabetes exceeding 20 years (OR = 2.005, 95%CI:1.346～2.959), Cystatin C (OR = 1.699,95% CI:1.299～2.239), ejection fraction (OR = 0.975, 95%CI: 0.958～0.992), multi-vessel disease ( OR=1.744, 95%CI: 1.270～2.422) and ST/T wave changes(OR = 1.920, 95% CI: 1.419～2.612) were all significant predictors of readmission risk. Based on these results, a nomogram model for predicting the risks of readmission in this patient population was developed.
      CONCLUSION The risk factors for readmission of patients with acute coronary syndrome complicated with type 2 diabetes within one year after PCI include age, hospitalization days, diabetes history exceeding 20 years, Cystatin C, ejection fraction, multivessel disease and ST/T wave changes. Our nomogram prediction model exhibits good discrimination and effectiveness, rendering it a valuable clinical tool for early predicting the risks of readmission.

       

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