中国全科医学 ›› 2023, Vol. 26 ›› Issue (29): 3650-3656.DOI: 10.12114/j.issn.1007-9572.2023.0139

• 论著 • 上一篇    下一篇

急性心肌梗死患者行经皮冠状动脉介入治疗术后发生对比剂急性肾损伤风险预测模型的建立与验证研究

王珍1, 申国旗1, 李亚南1, 朱英华1, 仇航1, 郑迪2, 徐通达2, 李文华2,*()   

  1. 1.221004 江苏省徐州市,徐州医科大学研究生院
    2.221004 江苏省徐州市,徐州医科大学附属医院心内科
  • 收稿日期:2023-02-19 修回日期:2023-04-10 出版日期:2023-10-15 发布日期:2023-04-26
  • 通讯作者: 李文华

  • 作者贡献:王珍进行数据整理、论文撰写、统计学分析、论文修改;申国旗进行数据收集及整理;李亚南、朱英华、仇航进行数据收集;郑迪、徐通达进行研究指导;李文华进行研究指导、论文修改。
  • 基金资助:
    江苏省卫生健康委员会面上项目(M2020015)

Development and Validation of a Risk Prediction Model for Contrast-induced Acute Kidney Injury after Percutaneous Coronary Intervention in Patients with Acute Myocardial Infarction

WANG Zhen1, SHEN Guoqi1, LI Yanan1, ZHU Yinghua1, QIU Hang1, ZHENG Di2, XU Tongda2, LI Wenhua2,*()   

  1. 1. Graduate School of Xuzhou Medical University, Xuzhou 221004, China
    2. Department of Cardiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221004, China
  • Received:2023-02-19 Revised:2023-04-10 Published:2023-10-15 Online:2023-04-26
  • Contact: LI Wenhua

摘要: 背景 急性心肌梗死(AMI)早期再灌注治疗是降低AMI患者死亡率的有效方法。经皮冠状动脉介入治疗(PCI)是再灌注治疗的方式之一,PCI术后出现对比剂急性肾损伤(CI-AKI)已成为急性肾损伤的常见原因之一。 目的 探讨AMI患者行PCI术后发生CI-AKI的危险因素,基于危险因素建立关于CI-AKI的风险预测模型,并评价其有效性。 方法 连续收集2019—2021年于徐州医科大学附属医院初诊为AMI并行PCI的1 274例患者的临床资料。依据入院时间顺序按约7∶3的比例分为训练组(2019年1月—2021年3月,900例)和验证组(2021年4—12月,374例);并根据CI-AKI的诊断标准将训练组患者分为CI-AKI组(109例)和non-CI-AKI组(791例)。使用单因素Logistic回归、Lasso回归、交叉验证及多因素Logistic回归筛选独立危险因素,并构建CI-AKI风险列线图,通过计算C-统计量、绘制校准曲线和决策曲线评价其鉴别力、校准能力和临床应用价值。 结果 训练组900例患者中,109例(12.1%)在接受PCI后发生CI-AKI;验证组374例患者中,27例(7.2%)发生CI-AKI。多因素Logistic回归分析结果显示,左心室射血分数(LVEF)〔OR=0.903,95%CI(0.873,0.934)〕、血小板分布宽度〔OR=1.158,95%CI(1.053,1.274)〕、平均血小板体积与淋巴细胞计数比值(MPVLR)〔OR=1.047,95%CI(1.016,1.079)〕、中性粒细胞计数/高密度脂蛋白(NHR)〔OR=1.072,95%CI(1.021,1.124)〕、血肌酐(Scr)〔OR=1.006,95%CI(1.002,1.011)〕、利尿剂〔OR=2.321,95%CI(1.452,3.709)〕是AMI患者PCI术后发生CI-AKI的独立影响因素(P<0.05)。建立包含LVEF、血小板分布宽度、MPVLR、NHR、Scr、利尿剂6个危险因素的预测模型并绘制CI-AKI风险列线图。训练组的C-统计量为0.794〔95%CI(0.766,0.820)〕,验证组的C-统计量为0.799〔95%CI(0.774,0.855)〕,校准图显示,预测结果和实际结果有较好的一致性;决策曲线和临床影响曲线表明,列线图具有临床实用价值。 结论 CI-AKI风险预测模型包括LVEF、血小板分布宽度、MPVLR、NHR、Scr、利尿剂,该预测模型具有良好的区分度和准确性,可以直观、独立地筛选高危人群,对AMI患者PCI后CI-AKI的发生具有较高的预测价值。

关键词: 急性心肌梗死, 经皮冠状动脉介入治疗, 急性肾损伤, 对比剂急性肾损伤, 列线图, 风险预测模型

Abstract:

Background

Early reperfusion therapy for acute myocardial infarction (AMI) is an effective approach to reduce mortality in AMI patients. Percutaneous coronary intervention (PCI) is one of the reperfusion therapy modalities, and contrast-induced acute kidney injury (CI-AKI) after PCI has become one of the common causes of AKI.

Objective

To investigate the risk factors for the development of CI-AKI in AMI patients after PCI, establish a risk prediction model for CI-AKI based on risk factors and evaluate its validity.

Methods

The clinical data of 1 274 patients who attended the Affiliated Hospital of Xuzhou Medical University diagnosed of AMI and treated with PCI were collected consecutively from 2019 to 2021. According to the chronological order of admission, the included patients were divided into the training group (January 2019 to March 2021, 900 cases) and validation group (April 2021 to December 2021, 374 cases) in a ratio of approximately 7∶3; and divided into the CI-AKI and non-CI-AKI groups according to the diagnostic criteria of CI-AKI. Independent risk factors were screened using univariable Logistic regression analysis, Lasso regression, cross-validation, multivariable Logistic regression analysis, and a nomogram for predicting the risk of CI-AKI was plotted. Their discriminatory power, calibration ability, and clinical application value were evaluated by calculating concordance statistic (C-statistic), plotting calibration curve and decision curve.

Results

Among the 900 patients in the training group, 109 patients (12.1%) developed CI-AKI after PCI; among the 374 patients in the validation group, 27 patients (7.2%) developed CI-AKI. Multivariable Logistic regression analysis showed that LVEF〔OR=0.903, 95%CI (0.873, 0.934) 〕, platelet distribution width〔OR=1.158, 95%CI (1.053, 1.274) 〕, MPVLR〔OR=1.047, 95%CI (1.016, 1.079) 〕, NHR〔OR=1.072, 95%CI (1.021, 1.124) 〕, Scr〔OR=1.006, 95%CI (1.002, 1.011) 〕, and diuretics〔OR=2.321, 95%CI (1.452, 3.709) 〕 were independent influencing factors for CI-AKI after PCI in AMI patients (P<0.05). A prediction model containing 6 risk factors of LVEF, platelet distribution width, MPVLR, NHR, Scr and diuretics was constructed and a nomogram for predicting the risk of CI-AKI was plotted. The C-statistic was 0.794〔95%CI (0.766, 0.820) 〕 for the training group and 0.799〔95%CI (0.774, 0.855) 〕 for the validation group, and the calibration plots showed good consistency between the predicted and actual results; the decision curve and clinical impact curve showed clinical application value of nomogram.

Conclusion

The CI-AKI risk prediction model including LVEF, platelet distribution width, MPVLR, NHR, Scr, and diuretics has good discrimination and accuracy, which can intuitively and independently screen high-risk population and has high predictive value for the development of CI-AKI after PCI in AMI patients.

Key words: Acute myocardial infarction, Percutaneous coronary intervention, Acute kidney injury, Contrast-induced acute kidney injury, Nomograms, Risk prediction model