A prognostic nomogram for long-term major adverse cardiovascular events in patients with acute coronary syndrome after percutaneous coronary intervention.

Background: Accurate prediction of major adverse cardiovascular events (MACEs) is very important for the management of acute coronary syndrome (ACS) patients. We aimed to construct an effective prognostic nomogram for individualized risk estimates of MACEs for patients with ACS after percutaneous coronary intervention (PCI).

Methods: This was a prospective study of patients with ACS after PCI from January 2013 to July 2019 (n = 2465). After removing patients with incomplete clinical information, a total of 1986 patients were randomly divided into evaluation (n = 1324) and validation (n = 662) groups. Predictors included in the nomogram were determined by a multivariate Cox proportional hazards regression model based on the training set. Receiver operating characteristic (ROC) curves and calibration curves were used to assess the discrimination and predictive accuracy of the nomogram, which were then compared with those of the classic models. The clinical utility of the nomogram was assessed by X-tile analysis and Kaplan-Meier curve analysis.

Results: Independent prognostic factors, including lactate level, age, left anterior descending branch stenosis, right coronary artery stenosis, brain natriuretic peptide level, and left ventricular ejection fraction, were determined and contained in the nomogram. The nomogram achieved good areas under the ROC curve of 0.712-0.762 in the training set and 0.724-0.818 in the validation set and well-fitted calibration curves. In addition, participants could be divided into two risk groups (low and high) according to this model.

Conclusions: A simple-to-use nomogram incorporating lactate level effectively predicted 6-month, 1-year, and 4-year MACE incidence among patients with ACS after PCI.