Nomogram to predict recurrent chest pain in patients with myocardial bridging

Objective Patients with myocardial bridging (MB) frequently experience recurrent chest pain, even in those without coronary heart disease. This study aims to predict the risk of recurrent chest pain in patients with MB by using a novel predictive nomogram. Methods This retrospective study enrolled 250 patients with acute chest pain who underwent coronary computed tomography angiography (CCTA) between January and December 2018, including 111 patients with MB and 139 control patients. Least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression analyses were used to screen for significant parameters that were included to develop a novel predictive nomogram model. Receiver operating characteristic curve, calibration curve, and decision curve analyses were used to evaluate the performance and clinical utility of the nomogram. Results A predictive nomogram was constructed in 111 patients with MB, 34 of whom (30.9%) had recurrent chest pain. The significant predictors screened out by the LASSO regression included age, sex, branch type MB, and systolic compression index. The area under the curves (AUCs) for recurrent chest pain at 12, 24, and 36 months were 0.688, 0.742, and 0.729, respectively, indicating remarkable accuracy of the nomogram. The calibration curve and decision curve analyses indicated a good agreement with the observations and utility of the nomogram. Conclusions This study presents a high-accuracy nomogram to predict recurrent chest pain in patients with MB. This model incorporates clinical risk factors and CT imaging features and can be conveniently used to facilitate the individualised prediction.

Automated summary

This study presents a high-accuracy nomogram to predict recurrent chest pain in patients with myocardial bridging (MB). The model incorporates clinical risk factors and CT imaging features and shows remarkable accuracy.