Predictive model for left main coronary artery or triple vessel disease in patients with chronic coronary syndromes.

Abstract

Background: Data about prediction of left main coronary artery disease (LMCAD)/three-vessel disease (TVD) in patients with chronic coronary syndromes (CCS) are lacking.

Objectives: This study aimed to develop a model for predicting patients at risk of LMCAD/TVD.

Methods: This study used retrospective data from patients with CCS scheduled for invasive coronary angiography (ICA) and who were retrospectively recruited between January 2018 and December 2020. Predictors were obtained and analyzed by using logistic regression analysis, and generated the prediction score. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. The cut-off value and area under the curve (AUC) were analyzed by using the receiver operating characteristic (ROC) curve.

Results: We recruited 162 patients with CCS. There were 75 patients in the non-LMCAD/TVD and 87 patients in the LMCAD/TVD groups. After the multivariate analysis, new onset of heart failure (HF) or left ventricular systolic dysfunction (LVSD) and suspected CAD, ST elevation (STE) in aVR, STE in V₁ and lateral ST depression (STD) were associated with increased risk of LMCAD/TVD. Based on these 4 predictors, the prediction score was created. The cut-off value of the prediction score by using ROC curve analysis was 3.0. The sensitivity, specificity, PPV, and NPV were 71.26%, 86.67%, 86.11%, and 72.22%, respectively, with an AUC of 0.855.

Conclusions: The CCS patients with new onset of HF or LVSD and suspected CAD, STE in aVR, and STE in V₁ and lateral STD were associated with increased risk of LMCAD/TVD. The novel prediction score could predict LMCAD/TVD in those patients with acceptable sensitivity, specificity, PPV, and NPV.