Predictive value of hs-cTnI for major adverse cardiovascular events in patients with acute myocardial infarction

ZHAO Jingkun; CHEN Zhenyi

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Predictive value of hs-cTnI for major adverse cardiovascular events in patients with acute myocardial infarction

Clinical Research | 更新时间：2026-01-06

- Predictive value of hs-cTnI for major adverse cardiovascular events in patients with acute myocardial infarction
- J Clin Electrocardiol Vol. 34, Issue 6, Pages: 438-444(2025)
- 作者机构：
  
  1.455000 河南安阳，安阳地区医院心内科（赵景坤）
  450000 河南郑州，河南省中医院心内科（陈振翼）
- 作者简介：
- 基金信息：
- DOI：
  CLC： R542.2
- Received：09 May 2025，
  
  Accepted：21 November 2025，
  
  Published：28 December 2025
- 稿件说明：
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赵景坤, 陈振翼. 急性心肌梗死患者高敏肌钙蛋白I对不良心血管事件的预测价值[J]. 临床心电学杂志, 2025, 34(6): 438-444.

ZHAO Jingkun,CHEN Zhenyi.Predictive value of hs-cTnI for major adverse cardiovascular events in patients with acute myocardial infarction[J].J Clin Electrocardiol,2025,34(06):438-444.
赵景坤, 陈振翼. 急性心肌梗死患者高敏肌钙蛋白I对不良心血管事件的预测价值[J]. 临床心电学杂志, 2025, 34(6): 438-444. DOI：

ZHAO Jingkun,CHEN Zhenyi.Predictive value of hs-cTnI for major adverse cardiovascular events in patients with acute myocardial infarction[J].J Clin Electrocardiol,2025,34(06):438-444. DOI：

摘要

目的

探讨高敏肌钙蛋白I（hs-cTnI）的动态变化与急性心肌梗死（Acute Myocardial Infarction，AMI）患者临床预后的相关性，重点评估其对主要不良心血管事件（Major Adverse Cardiovascular Events，MACE）发生的预测效能，为临床风险分层提供依据。

方法

采用单中心回顾性队列研究，纳入2021年1月至2023年12月确诊AMI的120例患者，根据MACE的发生情况，将患者划分为两组：发生MACE的MACE组（

=52）和未发生MACE的非 MACE组（

=68）。分析基线hs-cTnI、峰值水平、Δhs-cTnI及达峰时间等指标。采用单因素分析筛选潜在影响因素，多因素Logistic回归模型校正混杂因素，用ROC曲线评估各因素诊断价值，并用Kaplan-Meier生存分析比较临床结局差异。

结果

MACE组基线hs-cTnI（≥0.25 ng/mL）和峰值水平（≥1.8 ng/mL）显著高于非MACE组（差异具有统计学意义，

0.001）。多因素分析显示，基线hs-cTnI（OR=7.407，95%

2.732~20.084）、峰值hs-cTnI（OR=3.815，95%

1.392~10.458）及大面积梗死（OR=6.746，95%

2.444~18.624）是MACE的独立预测因子。ROC曲线表明，联合模型（AUC=0.882，95%

0.819~0.946）预测效能最优。生存分析显示，基线hs-cTnI高水平组的短期与长期MACE发生率均显著升高于低水平组（住院期间：49.02%

vs.

14.49%≥12个月随访期：25.49%

vs.

5.80%）组间差异均具有统计学意义（均

0.05）。

结论

hs-cTnI基线值和峰值水平对AMI患者MACE具有显著预测价值，联合梗死面积可进一步提高风险评估准确性，有助于早期识别高危患者并优化干预策略。

Abstract

Objective This study aimed to investigate the correlation between dynamic changes in high-sensitivity cardiac troponin I (hs-cTnI) and clinical outcomes in patients with acute myocardial infarction (AMI)

with a focus on evaluating its predictive value for major adverse cardiovascular events (MACE) to provide evidence for clinical risk stratification. Methods A single-center retrospective cohort study was conducted

enrolling 120 AMI patients diagnosed between January 2021 and December 2023. Patients were divided into a MACE group (

=52) and a non-MACE group (

=68) based on the occurrence of MACE. Baseline hs-cTnI

peak levels

Δhs-cTnI

and time-to-peak were analyzed. Potential influencing factors were initially screened using univariate analysis

followed by multivariate logistic regression to adjust for confounding variables. The diagnostic accuracy of each factor was evaluated using receiver operating characteristic (ROC) curves

while Kaplan-Meier survival analysis was employed to compare differences in clinical outcomes. Results The MACE group had significantly higher baseline hs-cTnI (≥0.25 ng/mL) and peak levels (≥1.8 ng/mL) compared to the non-MACE group (both

0.001). Multivariate analysis identified baseline hs-cTnI (OR=7.407

95%

2.732~20.084)

peak hs-cTnI (OR=3.815

95%

1.392~10.458)

and large infarct size (OR=6.746

95%

2.444~18.624) as independent predictors of MACE. ROC curve analysis showed that the combined model had the highest predictive efficacy (AUC=0.882

95%

0.819~0.946). Survival analysis revealed that patients in the high baseline hs-cTnI group had significantly higher incidence of MACE both during hospitalization (short-term

49.02%

vs.

14.49%) and over the follow-up period of≥12 month (long-term

25.49%

vs.

5.80%) Compared to the low-level group (all

0.05). Conclusions Baseline and peak hs-cTnI levels have significant predictive value for MACE in AMI patients. Combining these with infarct size further improves risk assessment accuracy

aiding in early identification of high-risk patients and optimization of intervention strategies.

关键词

Keywords

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