3 years ago

Tpeak-Tend dispersion as a predictor for malignant arrhythmia events in patients with vasospastic angina

Tpeak-Tend interval (Tp-e interval) in electrocardiogram (ECG) has been reported to predict malignant arrhythmia events (MAE) in ST-segment elevation myocardial infarction and ion channelopathy. Tp-e interval and other ECG parameters as predictors for MAE was evaluated in patients with vasospastic angina (VA). Methods and results Sixty-two patients with VA (Non-MAE group) and 20 patients with VA complicated by MAE (MAE group) were enrolled in our Division of Cardiology between January 2010 and December 2015. Continuous variables were analyzed by t-test and categorical variables by Chi-square analysis. Patients with MAE showed greater QTc (corrected QT interval) dispersion (P=0.005), Tp-ec (corrected Tp-e) interval (P=0.001), Tp-ec dispersion (P<0.001) and Tp-e/QT ratio (P<0.001) than those in non-MAE groups when ST-segment elevated. After elevated ST-segment returned, there were no significant differences in these ECG parameters between two groups (All P>0.05). At univariate binary logistic regression analysis QTc dispersion (odds ratio(OR)=1.133; P=0.013), Tp-ec (OR=1.058; P=0.003), Tp-e/QT (OR=1.403; P=0.001), and Tp-ec dispersion (OR=1.497; P=0.004) were significantly associated with MAE. At multivariable logistic regression analysis, Tp-ec dispersion remained a predictor of MAE. Receiver operating characteristic (ROC) curve analysis showed that only AUC (Area under curve) of Tp-ec dispersion had significant difference with those in QTc dispersion (P<0.001), Tp-ec (P=0.003), and Tp-e/QT ratio (P=0.012), respectively. Conclusions QTc dispersion, Tp-ec, Tp-e/QT and Tp-ec dispersion were significantly increased in VA patients with MAE than those without MAE when coronary spasm was onset. Prolonged Tp-ec dispersion was the best discriminators and a strong independent predictor of MAE in VA patients.

Publisher URL: www.sciencedirect.com/science

DOI: S0167527317319289

You might also like
Never Miss Important Research

Researcher is an app designed by academics, for academics. Create a personalised feed in two minutes.
Choose from over 15,000 academics journals covering ten research areas then let Researcher deliver you papers tailored to your interests each day.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.