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一种预测ST段抬高型心肌梗死患者急诊经皮冠状动脉介入治疗后心肌内出血的新模型

A New Model for the Prediction of Intramyocardial Hemorrhage in ST-Segment Elevation Myocardial Infarction Patients After Emergency Percutaneous Coronary Intervention.

作者信息

Yang Yongxin, Min Zeting, Ye Yong, Teng Lin, Cao Chunyu, Li Wenjing, Wen Te, Li Song, Ding Jiawang, Yang Jian, Zhou Fei

机构信息

Department of Cardiology, The First College of Clinical Medical Science, China Three Gorges University & Yichang Central People's Hospital, Yichang, China.

Institute of Cardiovascular Diseases, Three Gorges University, Yichang, China.

出版信息

Catheter Cardiovasc Interv. 2025 Sep;106(3):1966-1978. doi: 10.1002/ccd.70042. Epub 2025 Jul 23.

Abstract

BACKGROUND

Intramyocardial hemorrhage (IMH) after emergency percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients is a significant predictor of major adverse cardiovascular events. However, current research lacks a simple and visual predictive model for IMH occurrence.

AIMS

Our study aims to construct a Nomogram model to predict IMH occurrence.

METHODS

Patients with STEMI who underwent PCI at Yichang Central People's Hospital from August 2023 to September 2024 and had CMR 2-10 days post-PCI were included. They were divided into IMH and Non-IMH groups. Risk factors for IMH were identified using Random Forest, single-factor, and multifactor Logistic regression analyses. The constructed nomogram prediction model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and clinical decision analysis (DCA) curves. Bootstrap resampling was used for internal validation.

RESULTS

IMH occurred in 43 patients (Non-IMH:53). Ischemic time, preoperative CK-MB level, and preoperative Myo level were identified as independent risk factors for IMH, while RCA occlusion was a protective factor. A nomogram model based on these four variables was established to predict the risk of IMH occurrence. The model's ROC curve had an area under the curve (AUC) of 0.865, indicating excellent discriminative ability; the calibration curve had a good fit (p = 0.16); the DCA curve showed high clinical applicability. After internal validation, the AUC of the ROC curve was 0.873 (95% CI:0.754-0.921).

CONCLUSION

The Nomogram model constructed based on four clinical risk factors has good predictive value and clinical applicability, providing an effective reference for predicting the risk of IMH occurrence in STEMI patients after PCI.

摘要

背景

ST段抬高型心肌梗死(STEMI)患者急诊经皮冠状动脉介入治疗(PCI)后发生心肌内出血(IMH)是主要不良心血管事件的重要预测指标。然而,目前的研究缺乏一个简单直观的IMH发生预测模型。

目的

本研究旨在构建一个列线图模型来预测IMH的发生。

方法

纳入2023年8月至2024年9月在宜昌市中心人民医院接受PCI治疗且PCI术后2 - 10天进行心脏磁共振成像(CMR)检查的STEMI患者。将他们分为IMH组和非IMH组。使用随机森林、单因素和多因素逻辑回归分析确定IMH的危险因素。使用受试者工作特征(ROC)曲线、校准曲线和临床决策分析(DCA)曲线对构建的列线图预测模型进行评估。采用自助重抽样进行内部验证。

结果

43例患者发生IMH(非IMH组:53例)。缺血时间、术前肌酸激酶同工酶(CK - MB)水平和术前肌红蛋白(Myo)水平被确定为IMH的独立危险因素,而右冠状动脉(RCA)闭塞是一个保护因素。基于这四个变量建立了列线图模型来预测IMH发生风险。该模型的ROC曲线下面积(AUC)为0.865,表明具有良好的判别能力;校准曲线拟合良好(p = 0.16);DCA曲线显示出较高的临床适用性。内部验证后,ROC曲线的AUC为0.873(95%可信区间:0.754 - 0.921)。

结论

基于四个临床危险因素构建的列线图模型具有良好的预测价值和临床适用性,为预测STEMI患者PCI术后IMH发生风险提供了有效参考。

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