Choi Y, Lee JH, Seo JI. Change in T/QRS ratio can be a supplementary diagnostic tool in predicting coronary artery disease in patients with NSTEMI.
Am J Emerg Med 2020;
39:48-54. [PMID:
31954545 DOI:
10.1016/j.ajem.2020.01.013]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 01/03/2020] [Accepted: 01/06/2020] [Indexed: 10/25/2022] Open
Abstract
BACKGROUND
Changes in the electrocardiographic findings, namely the ratio T sum to QRS sum (T/QRS ratio), between the initial electrocardiogram (ECG) and the baseline ECG have rarely been investigated in patients with non-ST elevation myocardial infarction (NSTEMI). Thus, we aimed to determine whether changes in various parameters on ECG, including T/QRS ratio, can assist in distinguishing between coronary artery disease (CAD) and NSTEMI without CAD with low to moderate risk.
METHODS
This retrospective study enrolled 2572 patients who presented ischemic symptoms, who were diagnosed with NSTEMI, and who underwent coronary angiography. Overall, 388 patients had prior ECG and echocardiography data available; 110 patients were included after excluding patients with other cardiac diseases except CAD. The population divided into two groups: a coronary stenosis group (n = 78); normal coronary group (n = 32) were analyzed.
RESULTS
We found that acute dynamic change in the most deviated T/QRS ratio in each region of leads of initial ECG from those of remote/recent ECG was an extremely strong predictor of acute CAD (odds ratio, 110; p < .001) compared to that of initial serum troponin I levels, new-onset regional wall motion abnormalities, and new-onset T inversion or ST depression. T/QRS ratio change > 1.5 or <0.5 times in injured regional leads was a significant predictor of CAD.
CONCLUSION
Change in the most deviated T/QRS ratio in the regional leads on initial ECG from the T/QRS ratio in the same lead on remote ECG can assist in predicting CAD risk between patients with CAD and patients with no CAD in NSTEMI.
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