医学
血运重建
心脏病学
内科学
冠状动脉疾病
心肌梗塞
缺血
闪烁照相术
比例危险模型
外科
作者
R. Hachamovitch,A. Rozanski,Leslee J. Shaw,Gregory W. Stone,L Thomson,John D. Friedman,Sean Hayes,Ishac Cohen,Guido Germano,Daniel S. Berman
标识
DOI:10.1093/eurheartj/ehq500
摘要
Although pre-revascularization ischaemia testing is recommended, the interaction between the extent of ischaemia and myocardial scar with performance of revascularization on patient survival is unclear. We identified 13 969 patients who underwent adenosine or exercise stress SPECT myocardial perfusion scintigraphy (MPS). The percent myocardium ischaemic (%I) and fixed (%F) were calculated using 5 point/20-segment MPS scoring. Patients lost to follow-up (2.8%) were excluded leaving 13 555 patients [35% with history (Hx) of known coronary artery disease (CAD), 65% exercise stress, 61% male, age 66 ± 12]. Follow-up was performed at 12–18 months for early revascularization and at >7 years for all-cause death (ACD) (mean follow-up 8.7 ± 3.3 years). All-cause death was modelled using Cox proportional hazards modelling adjusting for logistic-based propensity scores, MPS, revascularization, and baseline characteristics. During FU, 3893 ACD (29%, 3.3%/year) and 1226 early revascularizations (9.0%) occurred. After risk-adjustment, a three-way interaction was present between %I, early revascularization, and HxCAD, such that %I identified a survival benefit with early revascularization in patients without prior myocardial infarction (MI), whereas no such benefit was present in patients with prior MI (overall model χ2= 3932, P < 0.001; interaction P < 0.021). Further modelling revealed that after excluding patients with scar >10% total myocardium, %I identified a survival benefit in all patients. In this large observational series with long-term follow-up, patients with significant ischaemia and without extensive scar were likely to realize a survival benefit from early revascularization. In contrast, the survival of patients with minimal ischaemia was superior with medical therapy without early revascularization.
科研通智能强力驱动
Strongly Powered by AbleSci AI