The Egyptian Heart Journal (Apr 2020)

Role of QRS fragmentation in 12-lead surface ECG in prediction of isolated epicardial coronary artery ectasia and its anatomical distribution in patients without acute coronary syndromes

  • Diaa Kamal,
  • Moataz Hashem

DOI
https://doi.org/10.1186/s43044-020-00054-4
Journal volume & issue
Vol. 72, no. 1
pp. 1 – 7

Abstract

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Abstract Background Coronary artery ectasia (CAE) is a form of abnormal coronary artery lumen dilatation associated with epicardial flow disturbances and microvascular dysfunction. QRS complex fragmentation (fQRS) in surface ECG is caused by abnormal depolarization due to myocardial ischemia and scarring. It has been proved in different studies to be positively correlated with adverse cardiac events. This study aimed to assess the role of fQRS as a non-invasive predictor of CAE and its anatomical distribution. A total of 100 patients referred for elective coronary angiography were included and divided into 2 groups: 50 patients with isolated CAE (group A) and 50 patients with angiographically normal coronaries (group B, control group). Both groups were compared regarding clinical, echocardiographic, and ECG characteristics. Results Univariate analysis showed a significant correlation between male sex, smoking, diabetes mellitus, increased systolic blood pressure, fQRS, echocardiographic evidence of diastolic dysfunction, and CAE (P values of 0.005, 0.002, 0.016, 0.027, 0.0001, and 0.04, respectively). Multivariate regression analysis showed that fQRS is the most important independent predictor for the presence of CAE (P < 0.00001) with sensitivity 94%, specificity 88%, PPV 88.7%, and NPV 93.6%. We also found a significant correlation between fQRS distribution in surface ECG and anatomical distribution of CAE [increased territories with multivessel affection (P = 0.00001), anterior leads with LAD affection (P = 0.00001), lateral and inferior leads with LCX affection (P = 0.003 and 0.04, respectively), inferior leads with RCA affection (P = 0.00001)]. Conclusion fQRS in surface ECG can potentially be used as an effective non-invasive method to predict isolated CAE and its anatomical distribution.

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