Abstract Introduction Despite the significant progress made in diagnosing and treating patients with ST elevation myocardial infarction (STEMI), high-risk subgroups such as older adults (those over 65 years-old) still face considerable residual risk of major adverse cardiovascular events (MACE) following treatment for their index event. Thus, it is crucial to create accurate, validated, and actionable tools to stratify patients according to their risk of MACE after admission for STEMI. Purpose Utilizing clinical data obtained from a registry of patients diagnosed with STEMI, this study aims to develop a nomogram that can reliably predict the likelihood of MACE incidence. Methods Using a large electronic single-center registry, all consecutive patients with STEMI, undergoing primary percutaneous coronary intervention (PCI), and aged 65 and above were identified. Demographic, laboratory, clinical and intra-procedural variables were examined. Univariate and multivariate logistic regression analyses were utilized to identify those factors which were independently associated with MACE incidence in the post PCI follow-up period. A nomogram was developed in a training set, and performance metrics such as receiver operating curves (ROC), calibration plots, and decision curve analysis were used for validation in a testing set. Analyses were performed using tidyverse and rms packages in R programming language. Results 1946 patients were included in the study and split into 70% training and 30% testing sets. Both groups were similar in terms of baseline demographic and clinical characteristics. Mean follow-up period was 17 months. Total MACE incidence in the post PCI follow-up period was 18%. Thirty-eight factors with limited missing information (<5%) were examined for their relationship with MACE incidence and after performing univariate and multivariate analysis 8 were selected for construction of the nomogram: left-ventricular ejection fraction (LVEF), serum creatinine, hemoglobin and fasting blood glucose levels, presence of valvular heart disease, post PCI TIMI flow grade, diameter of the stent placed in the culprit lesion, and presence of shock in the post PCI setting. The area under the curve (AUC) for MACE prediction in post PCI follow-up period showed acceptable discrimination (c-statistic=73%, 95%CI 71.2% to 76.3%). Calibration plots demonstrated that the nomogram model was well-calibrated, and its predictions were closely aligned with observed outcomes. Additionally, decision curve analysis indicated that the model exhibited strong discriminatory ability in predicting MACE. Conclusions A nomogram developed using a combination of laboratory, clinical, and procedural parameters reliably predicts future risk for MACE in older adults following STEMI. Future implementation of this model may identify the highest risk individuals to target more aggressive preventive efforts in a vulnerable cohort of patients.Plot 1Plot 2
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