Predicting cardiovascular outcomes in elderly patients with acute coronary syndrome: a nomogram approach

Area of Science:

• Cardiology
• Geriatric Medicine
• Medical Informatics

Background:

• ST Elevation Myocardial Infarction (STEMI) remains a significant concern for elderly patients, with a notable risk of Major Adverse Cardiovascular Events (MACE) despite advancements in diagnosis and treatment.
• Identifying high-risk individuals within this demographic is crucial for improving patient outcomes.

Purpose of the Study:

• To develop and validate a predictive nomogram for MACE incidence in elderly STEMI patients undergoing primary Percutaneous Coronary Intervention (PCI).
• To identify key clinical, laboratory, and procedural factors associated with MACE in this population.

Main Methods:

• Retrospective analysis of 65-year-old STEMI patients who underwent primary PCI at Tehran Heart Center.
• Inclusion of demographic, laboratory, clinical, and intra-procedural data.
• Application of univariate and multivariate analyses, decision curve analysis, ROC curves, and calibration plots for nomogram validation using R Studio.

Main Results:

• A nomogram was constructed using 8 significant factors: left-ventricular ejection fraction (LVEF), serum creatinine, hemoglobin, fasting blood glucose, valvular heart disease, post-PCI TIMI flow grade, culprit lesion stent diameter, and post-PCI shock.
• The nomogram demonstrated good predictive performance with an Area Under the Curve (AUC) of 71% for MACE prediction.
• The model showed strong calibration and discriminative ability, validated on a separate testing cohort.

Conclusions:

• A validated nomogram effectively predicts MACE risk in older STEMI patients based on readily available clinical, laboratory, and procedural data.
• This predictive tool can aid clinicians in identifying vulnerable patients who may benefit from more intensive preventative strategies.