Abstract
BACKGROUND: In chronic coronary syndrome (CCS), assessing myocardial ischemia is difficult due to its variable severity. Myocardial mechanical parameters are helpful in ischemia detection. This study investigates the use of non-invasive myocardial work (MW) for ischemia detection and risk assessment in CCS patients. METHOD: The study included 115 patients (70 men, mean age 61 years) with suspected or diagnosed CCS in the derivation cohort and 62 patients in the validation cohort. All patients underwent regadenoson stress echocardiography, with early ischemia indicated by coronary flow velocity reserve (CFVR) <2.5. The patients were categorized based on CFVR, and logistic regression was used to assess the association between myocardial work (MW) and ischemia. Model performance was evaluated for accuracy, prediction, and practicality. The risk stratification thresholds were set by sensitivity and specificity. RESULTS: Of the 115 patients, 48 (41.74%) had myocardial ischemia. MW was more sensitive in detecting ischemia than global longitudinal strain. Multivariate analysis showed that global constructive work reserve (△GCW) was independently correlated with CFVR, with the highest AUC (0.777). A model including △GCW and hemoglobin identified ischemia with a C-index of 0.844 in the derivation cohort and 0.82 in the validation cohort, allowing calculation of the probability of ischemia in CCS. Risk levels were defined by probabilities of 20% (low) and 70% (high). CONCLUSION: The incorporation of △GCW and hemoglobin into the prediction model enhances its ability to estimate myocardial ischemia risk. △GCW offered higher sensitivity and incremental diagnostic value in detecting myocardial ischemia in the heterogeneous CCS population.