Postoperative Heart Failure Risk Prediction Models in Chinese Patients With Acute Myocardial Infarction：a Systematic Review and Meta-analysis

Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2025-07-09 Cooperative journals: 《中国全科医学》

WEN Qing SU Yushuang PU Zaichun CHEN Juan GUO Mingfan MAO Xiaorong LUO Tiantian MA Qunhua

Abstract： Background　Acute myocardial infarction（AMI） is one of the leading causes of death worldwide，and percutaneous coronary intervention（PCI） is the preferred clinical treatment option for most AMI patients. However，patients still face a high risk of heart failure（HF） post-PCI，with poor prognosis，severely impacting their quality of life and long-term survival rates. Objective　The risk prediction model of HF after PCI in patients with AMI was evaluated with the aim of providing reference for the development，optimisation and application of the model. Methods　A computerized systematic search was conducted across PubMed，Web of Science，Embase，CNKI，VIP and Wanfang Data for relevant literature on HF risk prediction models in AMI patients post-PCI，with the search period spanning from database inception to November 12，2024. Two researchers independently screened the literature，extracted data，and assessed the quality of included studies using the PROBAST tool. Meta-analysis of HF risk predictors in AMI patients post-PCI was performed using RevMan 5.4 software. Results　A total of 18 papers were included，with a sample number of 6 375 cases，and the incidence rate of HF was 13%. The incidence of HF ranged from 13.7% to 34.8%，with a total of 21 HF risk prediction models for post-PCI in patients with AMI，and the area under the curve of the working characteristic（AUC） of the subjects ranged from 0.657% to 0.966%，with 17 prediction models having good predictive performance（AUC>0.7），and the overall bias of the literature was high risk of bias and good applicability. Statistical analysis of model predictive performance AUC was performed using MedCalc software，and the combined AUC was 0.852（95%CI=0.815-0.890）. Meta-analysis results indicated that age，Gensini score，arrhythmia，serum creatinine（Scr），ventricular wall motion amplitude，hypertension，diabetes mellitus，left ventricular ejection fraction （LVEF），high-sensitivity C-reactive protein（hsCRP），N-terminal pro-brain natriuretic peptide（NT-proBNP），brain natriuretic peptide（BNP），number of lesion vessels，cardiac structural changes，and anterior wall myocardial infarction were predictors of HF in AMI patients post-PCI（P<0.05）. Conclusion　Currently，the risk prediction risk prediction model for post-PCI HF risk prediction in AMI patients is still in the exploratory stage，with good model differentiation but high overall risk of bias，and the study design should be optimised and the reporting process should be improved in the future in order to ensure that a predictive model with strong clinical utility is developed.

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