Objective:

To identify independent risk factors for in-hospital heart failure (HF) in T2DM patients with acute STEMI post-PCI from January 2022 to June 2025 and to create a personalized risk prediction model.

Key Findings:

• Seven independent risk factors for in-hospital HF identified: prior myocardial infarction (OR=4.187, 95% CI: 2.374–7.389), smoking history (OR=2.683, 95% CI: 1.630–4.415), diminished left ventricular ejection fraction (per 1% decrease, OR=0.944), heightened white blood cell count (per 1×10⁹/L increase, OR=1.107), reduced hemoglobin level (per 1 g/L decrease, OR=0.976), increased platelet count (per 50×10⁹/L increase, OR=1.200), and atrial fibrillation (OR=2.121, 95% CI: 1.085–4.146).
• The nomogram showed an AUC of 0.845 and good calibration (P=0.712).
• Sensitivity analysis confirmed model stability with no significant multicollinearity (all VIF <1.5).

Interpretation:

The nomogram model effectively predicts in-hospital HF risk in T2DM patients post-PCI, providing a quantitative tool for early detection of high-risk individuals.

Limitations:

• Single-center study limits generalizability; external validation required for clinical applicability and to assess performance in diverse populations.

Conclusion:

The nomogram demonstrates strong predictive capability but needs external validation across multiple centers for broader clinical use.