早发急性ST段抬高型心肌梗死患者预后风险列线图模型的构建与验证
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E-mail:guyang1028@163.com;zhangxiwen303@163.com

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R541.4

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南京医科大学附属淮安第一医院科研启动经费项目(YGRS202006);中华国际医学交流基金会心血管多学科整合思维研究基金(Z-2016-23-2101-46)


Establishment and validation of prognostic risk nomogram model among patients with premature ST⁃segment elevation myocardial infarction
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    摘要:

    目的:分析早发ST段抬高型心肌梗死(ST-segment elevated myocardial infarction,STEMI)患者的危险因素,并建立预测早发STEMI患者术后主要心血管不良事件(major adverse cardiac events,MACE)发生风险的列线图模型。方法:选取2017年 1 月—2018 年 12 月在南京医科大学附属淮安第一医院诊断为早发 STEMI 并行经皮冠状动脉介入术(percutaneous coronary intervention,PCI)治疗的166例患者为研究对象,并随访24个月,依据MACE的发生情况,分为MACE组(62例)与非MACE组 (104例)。利用LASSO回归与Cox回归分析筛选危险因素,并构建列线图预测模型。通过受试者工作特征曲线(receiver opera- ting characteristic curve,ROC)、临床决策曲线(decision curve analysis,DCA)、校准曲线等评估模型的效能,并通过Bootstrap法自抽样验证模型的稳定性。结果:LASSO 回归与 Cox 回归结果表明中性粒细胞明胶酶相关脂质运载蛋白(neutrophil gelatin- ase associated lipocalin,NGAL)、肌酐、发生 AMI 至梗死相关动脉开通的时间、左室射血分数(left ventricular ejection fraction, LVEF)、梗死相关动脉为早发STEMI患者术后发生MACE的重要危险因素(P < 0.05),利用这5个预测指标构建了列线图预测模型。在PCI术后6、12、24个月,模型的ROC曲线下面积分别为0.95(95% CI:0.89~1.00)、0.94(95% CI:0.80~0.99)、0.87(95% CI: 0.82~0.93),均大于单个危险因素;Calibration校准曲线接近理想曲线;DCA曲线显示列线图预测模型在0.25~1阈值概率范围内的表现更好。结论:本研究根据早发STEMI患者PCI术后发生MACE的危险因素构建了列线图预测模型,经Bootstrap内部验证后,该预测模型具有较好的效能与稳定性,能够较为准确地预测早发STEMI患者PCI术后6、12、24个月MACE的发生风险。这有助于针对早发STEMI高危患者进行个体化干预治疗,改善其预后。

    Abstract:

    Objective:This study aims to analyze the risk factors of patients with premature ST segment elevation myocardial infarction(STEMI)and to develop a nomogram model to predict the risk of postoperative major adverse cardiac events(MACE)in patients with premature STEMI. Methods:A total of 166 patients diagnosed with premature STEMI undergoing percutaneous coronary intervention(PCI)in the Affiliated Huaian No.1 People’s Hospital of Nanjing Medical University from January 2017 to December 2018 were selected as the research subjects,and they were followed up for 24 months. According to the occurrence of MACE,they were divided into MACE group(62 cases)and non-MACE group(104 cases). Risk factors were screened using LASSO regression with Cox regression analysis,and a nomogram prediction model was constructed. The efficacy of the model was evaluated by receiver operating characteristic curve(ROC),clinical decision curve(DCA),calibration curve,etc.,and the stability of the model was verified by Bootstrap self sampling. Results:The results of LASSO regression and Cox regression showed that neutrophil gelatinase associated lipocalin(NGAL),creatinine,time from AMI to opening of infarct related artery,left ventricular ejection fraction(LVEF),infarct related artery were significant risk factors for the occurrence of postoperative MACE in patients with premature STEMI(P < 0.05),and the nomogram prediction model was constructed using these 5 predictors. The areas under the ROC curves of the models were 0.95 (95% CI:0.89~1.00),0.94(95% CI:0.80~0.99),0.87(95% CI:0.82~0.93)at 6,12,24 months after PCI,respectively,which were larger than those of the individual risk factors. The calibration curve is close to the ideal curve. The DCA curves showed better performance of the nomogram prediction model in the 0.25~1 threshold probability range. Conclusion:In this study,a nomogram prediction model was constructed based on the significant risk factors for the occurrence of MACE after PCI in patients with premature STEMI,and after Bootstrap internal validation,the prediction model had better efficacy and stability,and could accurately predict the risk of MACE at 6,12,and 24 months after PCI in patients with premature STEMI. It is helpful to carry out individualized intervention treatment for high-risk patients with premature STEMI and improve their prognoses.

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张鑫,丁莹,姚毅仁,谷阳,张喜文.早发急性ST段抬高型心肌梗死患者预后风险列线图模型的构建与验证[J].南京医科大学学报(自然科学版),2022,42(11):1539-1546,1552

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  • 在线发布日期: 2022-11-24
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