Prognostic value of gated myocardial perfusion imaging in patients with chronic coronary syndromes: high post-stress wall motion score increase risk in patients with less than severe ischemia

Objective This study aims to evaluate the prognostic value of gated myocardial imaging (GMPI) in patients with chronic coronary syndromes (CCS). Methods and results We retrospectively analyzed 128 CCS patients who underwent a 2-day rest-stress GMPI performed at the Second Affiliated Hospital of Chongqing Medical University and Chongqing Emergency Center from May 2018 to October 2023. Clinical data and GMPI parameters, including summed stress score (SSS), summed difference score (SDS), summed motion score (SMS), phase histogram bandwidth (PBW) and left ventricular ejection fraction (LVEF), were collected. Patients were followed up until the occurrence of major adverse cardiovascular events (MACE), including cardiac death, non-fatal myocardial infarction, unstable angina and re-hospitalization for angina. Cox proportional hazard models and Kaplan-Meier curves were used to identify independent risk factors and calculate event-free survival. Results The mean age of the enrolled patients was 60.3 years, with a median follow-up of 29.0 months. Thirty patients (23.4%) experienced at least once MACE. Multivariate Cox regression analysis identified SDS > 7 ( HR 4.622 P  < 0.001), SMS > 9 ( HR 3.032 P  = 0.007) and diabetes ( HR 3.942 P  < 0.001) as independent risk factors for MACE in CCS-patients. Among patients with SDS ≤ 7, those with SMS>9 exhibited a significantly higher risk of MACE compared to those with SMS ≤ 9 ( HR 3.712 P  = 0.013). Notably, diabetic patients in the SDS ≤ 7 subgroup exhibited a risk of MACE equivalent to that of patients with severe perfusion defects (SDS > 7) (log-rank P  = 0.990). Conclusion GMPI is valuable for risk stratification prognosis assessment in CCS patients. While SDS > 7 remains the strongest predictor, SMS > 9 refines risk stratification in non-severe perfusion defects (SDS ≤ 7). Combine assessment of ischemia and wall motion abnormalities improves prognostic accuracy, particularly in non-severe ischemia subgroups.