Integrating angio-IMR and CMR-assessed microvascular obstruction for improved risk stratification of STEMI patients

危险分层 心脏病学 内科学 医学 分层(种子) 生物 休眠 植物 种子休眠 发芽
作者
Yang Duan,Qianran Yin,Yinshuang Yang,Hao Miao,Shuguang Han,Qiuming Chi,Haiying Lv,Yuan Lu,Yafeng Zhou
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:15 (1): 5470-5470 被引量:3
标识
DOI:10.1038/s41598-025-88942-0
摘要

Early detection of coronary microvascular dysfunction (CMD) in ST-segment elevation myocardial infarction (STEMI) patients undergoing percutaneous coronary intervention (PCI), is challenging. The index of microcirculatory resistance (caIMR), derived from computational pressure-fluid dynamics (CPFD), allows practical assessment of CMD using only routine coronary angiography. However, the prognostic implications of combining caIMR with microvascular obstruction (MVO) identified through cardiac magnetic resonance (CMR) imaging are unclear. This retrospective study investigates the utility of CPFD-caIMR and CMR-derived MVO in predicting major adverse cardiovascular events (MACEs) in 292 STEMI patients who underwent primary PCI, followed by caIMR and CMR evaluations. Patients were stratified into four groups based on caIMR thresholds (≤ 40 U or > 40 U) and the presence/absence of MVO. The primary endpoint was MACEs, defined as cardiac death, recurrent myocardial infarction, target vessel revascularization, or heart failure readmission. Overall, 101/292 patient exhibited discordant caIMR and MVO results. Specifically, 103 patients had caIMR ≤ 40 U without MVO, while 88 patients showed caIMR > 40 U with MVO. Multivariate analysis identified both caIMR > 40 U and MVO as independent predictors of MACEs, with an HR of 3.572 for each unit increase in CPFD-caIMR > 40 U. Combination of CPFD-caIMR and MVO significantly enhanced predictive accuracy. CPFD-caIMR is a reliable, minimally invasive tool for identifying microvascular dysfunction. Combination with CMR-derived MVO improves risk stratification in STEMI patients following PCI, holding promise for the early identification of high-risk patients, enabling targeted and personalized management.
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