Influencing factors and construction of a prediction model for poor prognosis in patients with acute myocardial infarction complicated by heart failure

ZHU Houling; HUANG Shan; MA Zetao; WU Yuewei

doi:10.7619/jcmp.20244687

Journal of Clinical Medicine in Practice > 2025 > 29(5): 82-87, 94. > DOI: 10.7619/jcmp.20244687

ZHU Houling, HUANG Shan, MA Zetao, WU Yuewei. Influencing factors and construction of a prediction model for poor prognosis in patients with acute myocardial infarction complicated by heart failure[J]. Journal of Clinical Medicine in Practice, 2025, 29(5): 82-87, 94. DOI: 10.7619/jcmp.20244687

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Influencing factors and construction of a prediction model for poor prognosis in patients with acute myocardial infarction complicated by heart failure

the First Department of Cardiology, the First Hospital Affiliated to Hainan Medical University, Haikou, Hainan, 570100

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Received Date: October 09, 2024
Revised Date: November 10, 2024

Graphical Abstract

Abstract

Abstract

Objective
To explore the influencing factors for poor prognosis in patients with acute myocardial infarction (AMI) complicated by heart failure (HF), construct a nomogram prediction model, and validate its performance.
Methods
A total of 252 patients with AMI complicated by HF were selected as training set and divided into poor prognosis group (60 patients) and good prognosis group (192 patients) based on 1-year follow-up results. Additionally, 86 patients with AMI complicated by HF, with a ratio approximately 1∶3 to the training set, were selected as validation set. Cox regression models were used to analyze the influencing factors for poor prognosis. A nomogram model was constructed based on the screening results and underwent internal and external validation[Hosmer-Lemeshow test was used to assess goodness of fit, calibration curves were plotted to evaluate calibration, receiver operating characteristic (ROC) curves were drawn to analyze discriminative ability, and decision curve analysis (DCA) was conducted to assess clinical utility].
Results
There were no statistically significant differences in clinical data between the training set and validation set (P>0.05). The poor prognosis group had higher levels of serum creatinine and cardiac troponin T (cTnT), higher proportions of patients aged ≥60 years, with time from onset to admission ≥4 hours, with heart function grades Ⅲ to Ⅳ, and a lower left ventricular ejection fraction (LVEF) compared with the good prognosis group (P < 0.05). Multivariate Cox regression analysis showed that time from onset to admission, heart function grade, serum creatinine, cTnT, and LVEF were independent influencing factors for poor prognosis in patients with AMI complicated by HF (P < 0.05). Based on these results, a nomogram model was constructed. Internal validation results showed that the model had good goodness of fit (χ²=13.966, P=0.083), excellent calibration, and good discriminative ability[area under the curve (AUC) was 0.831]. External validation results also showed that the model had good goodness of fit (χ²=6.465, P=0.136), excellent calibration, and good discriminative ability (AUC was 0.884). DCA results indicated that the nomogram model had good clinical net benefit within a high-risk threshold range of 0.02 to 0.98.
Conclusion
Influencing factors for poor prognosis in patients with AMI complicated by HF include time from onset to admission, heart function grade, serum creatinine, cTnT, and LVEF.The constructed nomogram model has high predictive value for poor prognosis in these patients.
- acute myocardial infarction,
- heart failure,
- nomogram model,
- Cox regression models,
- serum creatinine,
- cardiac troponin T,
- decision curve analysis

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References

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Influencing factors and construction of a prediction model for poor prognosis in patients with acute myocardial infarction complicated by heart failure