Zhao Ruohan, Zhang Jing, Xie Yu, Tan Yuting, Qi Benling, Bai Lijuan, Wu Jingjing, Cheng Min, Wang Xiang, Lv Qing, Wang Jing, Xie Mingxing
Department of Ultrasound Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Hubei Province Clinical Research Center for Medical Imaging, Wuhan, China.
Front Cardiovasc Med. 2025 Aug 1;12:1598453. doi: 10.3389/fcvm.2025.1598453. eCollection 2025.
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.
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.
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).
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.
在慢性冠状动脉综合征(CCS)中,由于心肌缺血严重程度各异,评估心肌缺血具有一定难度。心肌力学参数有助于缺血检测。本研究探讨了无创心肌作功(MW)在CCS患者缺血检测及风险评估中的应用。
该研究纳入了115例(70例男性,平均年龄61岁)来自推导队列的疑似或确诊CCS患者以及62例来自验证队列的患者。所有患者均接受了雷加昔布负荷超声心动图检查,冠状动脉血流速度储备(CFVR)<2.5提示早期缺血。根据CFVR对患者进行分类,并采用逻辑回归评估心肌作功(MW)与缺血之间的关联。通过准确性、预测性和实用性评估模型性能。根据敏感性和特异性设定风险分层阈值。
115例患者中,48例(41.74%)存在心肌缺血。MW在检测缺血方面比整体纵向应变更敏感。多变量分析显示,整体建设性作功储备(△GCW)与CFVR独立相关,曲线下面积(AUC)最高(0.777)。在推导队列中纳入△GCW和血红蛋白的模型识别缺血的C指数为0.844,在验证队列中为0.82,可计算CCS患者缺血的概率。风险水平由20%(低)和70%(高)的概率定义。
将△GCW和血红蛋白纳入预测模型可增强其估计心肌缺血风险的能力。△GCW在检测异质性CCS人群的心肌缺血方面具有更高的敏感性和增量诊断价值。