Nomograms referenced by cardiac magnetic resonance in the prediction of cardiac injuries in patients with ST-elevation myocardial infarction

Background: Evaluation of cardiac injuries is essential in patients with ST-elevation myocardial infarction (STEMI). Cardiac magnetic resonance (CMR) has become the gold standard for quantifying cardiac injuries; however, its routine application is limited. A nomogram is a useful tool for prognostic prediction based on the comprehensive utilization of clinical data. We presumed that the nomogram models established using CMR as a reference could precisely predict cardiac injuries.

Methods: This analysis included 584 patients with acute STEMI from a CMR registry study for STEMI (NCT03768453). The patients were divided into training (n = 408) and testing (n = 176) datasets. The least absolute shrinkage and selection operator method and multivariate logistic regression were used to construct nomograms for predicting left ventricular ejection fraction (LVEF) ≤40%, infarction size (IS) ≥ 20% on the LV mass, and microvascular dysfunction.

Results: The nomogram for predicting LVEF≤40%, IS≥20%, and microvascular dysfunction comprised 14, 10, and 15 predictors, respectively. With the nomograms, the individual risk probability of developing specific outcomes could be calculated, and the weight of each risk factor was demonstrated. The C-index of the nomograms in the training dataset were 0.901, 0.831, and 0.814, respectively, and were comparable in the testing set, showing good nomogram discrimination and calibration. The decision curve analysis demonstrated good clinical effectiveness. Online calculators were also constructed.

Conclusions: With the CMR results as the reference standard, the established nomograms demonstrated good effectiveness in predicting cardiac injuries after STEMI and could provide physicians with a new option for individual risk stratification.