Associating electrocardiographic abnormalities with coronary artery disease: insights into microvascular dysfunction from dynamic CT perfusion
摘要
Electrocardiographic (ECG) abnormalities serve as important predictors of future cardiovascular events. However, the specific cardiac abnormalities that bridge the gap between ECG abnormalities and subsequent events remain poorly understood. This study aimed to evaluate the relationship between ECG abnormalities and the prevalence of coronary artery disease (CAD) in propensity score-matched patients with suspected CAD who underwent comprehensive cardiac computed tomography (CT).
Materials and methodsA total of 357 patients suspected of CAD underwent ECG and cardiac CT assessments, including calcium scoring, stress dynamic CT perfusion (CTP), coronary CT angiography (CCTA), and CT late enhancement. Propensity score matching based on demographic parameters and CAD risk factors was performed, resulting in 286 matched patients (143 without ECG abnormalities and 143 with ECG abnormalities).
ResultsIn both unadjusted and propensity score-matched analyses, ECG abnormalities were significantly associated with microvascular dysfunction and myocardial scarring (p < 0.05 for both analyses). However, no significant associations were observed between ECG abnormalities and coronary calcification severity or obstructive CAD (≥ 50% luminal narrowing) in the propensity score-matched patients. Among matched patients without obstructive CAD on CCTA, those with ECG abnormalities exhibited a higher prevalence (30%) of microvascular dysfunction, particularly in the diffuse-transmural pattern, compared to that (14%) of patients without ECG abnormalities (p < 0.01).
ConclusionECG abnormalities may not be reliable indicators of the presence of obstructive CAD. However, given their association with microvascular dysfunction, CAD evaluation with comprehensive cardiac CT, including dynamic CTP, is recommended for patients exhibiting ECG abnormalities, particularly to evaluate myocardial perfusion abnormalities.
Key Points