Objective: In recent years, the early diagnosis and treatment of coronary microvascular dysfunction (CMD) have become crucial for preventing coronary heart disease. This paper aims to develop a computer-assisted autonomous diagnosis method for CMD by using ECG features and expert features. Approach: Clinical electrocardiogram (ECG), myocardial contrast echocardiography (MCE), and coronary angiography (CAG) are used in our method. Firstly, morphological features, temporal features, and T-wave features of ECG are extracted by multi-channel residual network with BiLSTM (MCResnet-BiLSTM) model and the multi-source T-wave features (MTF) extraction model, respectively. And these features are fused to form ECG features. In addition, the CFR $_\text{MCE}$ is calculated based on the parameters related to the MCE at rest and stress state, and the Angio-IMR is calculated based on CAG. The combination of CFR $_\text{MCE}$ and Angio-IMR is termed as expert features. Furthermore, the hybrid features, fused from the ECG features and the expert features, are input into the multilayer perceptron to implement the identification of CMD. And the weighted sum of the soft maximum loss and center loss is used as the total loss function for training the classification model, which optimizes the classification ability of the model. Result: The proposed method achieved 93.36% accuracy, 94.46% specificity, 92.10% sensitivity, 95.89% precision, and 93.95% F1 score on the clinical dataset of the Second Affiliated Hospital of Zhejiang University. Conclusion: The proposed method accurately extracts global ECG features, combines them with expert features to obtain hybrid features, and uses weighted loss to significantly improve diagnostic accuracy. It provides a novel and practical method for the clinical diagnosis of CMD.

Purpose This research aimed to assess the impact of ticagrelor and clopidogrel on coronary microvascular dysfunction (CMD) and prognosis following acute myocardial infarction (AMI), using the angiography-derived index of microcirculatory resistance (angio-IMR) as a non-invasive assessment tool. Methods In this retrospective study, angio-IMR was performed to evaluate CMD before and after dual antiplatelet therapy (DAPT) with either ticagrelor (90 mg twice daily, n = 184) or clopidogrel (75 mg once daily, n = 72). The primary endpoint is the improvement of CMD evaluated by angio-IMR (delta angio-IMR) following DAPT. Secondary endpoints included myocardial reinfarction and readmission for heart failure during 2-year follow-up. Results Compared with clopidogrel, ticagrelor exhibited a significantly higher delta angio-IMR [− 3.09 (5.14) versus − 1.99 (1.91), P = 0.008], indicating a superior improvement of CMD with ticagrelor treatment. Multivariate Cox regression indicated that ticagrelor treatment was related to a reduced risk of readmission for heart failure [8 (4.3) versus 9 (12.5), adjusted HR = 0.329; 95% CI = 0.116–0.934; P = 0.018] and myocardial reinfarction [7 (3.8) versus 8 (11.1), adjusted HR = 0.349; 95% CI = 0.125–0.975; P = 0.026]. Furthermore, ticagrelor treatment serves as an independent predictor of readmission for heart failure (HR = 0.322; 95% CI = 0.110–0.943; P = 0.039). Conclusion The results of this study indicate a potential association between ticagrelor treatment and improved CMD, as well as a reduced risk of cardiovascular events, including myocardial reinfarction and readmission for heart failure in AMI patients. Further randomized controlled trials are necessary to confirm the potential benefits of ticagrelor on CMD and cardiovascular prognosis. This clinical trial was registered in www.clinicaltrials.gov (NCT05978726).