Principal component analysis of the T wave and prediction of cardiovascular mortality in American Indians: the Strong Heart Study.

Abstract

Increased QT interval dispersion (QTd) is a proposed ECG marker of vulnerability to ventricular arrhythmias and of cardiovascular (CV) mortality. However, principal component analysis (PCA) of the T-wave vector loop may more accurately represent repolarization abnormalities than QTd. Predictive values of QTd and PCA were assessed in 1839 American Indian participants in the first Strong Heart Study examination. T-wave loop morphology was quantified by the ratio of the second to first eigenvalues of the T-wave vector by PCA (PCA ratio); QTd was quantified as the difference between maximum and minimum QT intervals. After 3.7+/-0.9 years mean follow-up, there were 55 CV deaths. In univariate analyses, an increased PCA ratio predicted CV mortality in women (chi2=7.8, P=0.0053) and men (chi2=9.5, P=0.0021). In contrast, increased QTd was a significant predictor of CV mortality in women (chi2=30.6, P<0.0001) but not in men (chi2=2.0, P=NS). In multivariate Cox analyses controlling for risk factors and rate-corrected QT interval, the PCA ratio remained a significant predictor of CV mortality in women (chi2=4.0 P=0.043) and men (chi2=6.4, P=0.011); QTd was a significant predictor in women only (chi2=11.0, P=0.0009). PCA ratios >90th percentile (32% in women and 24.6% in men) identified women with a 3.68-fold increased risk of CV mortality (95% CI, 1.54 to 8.83) and men with a 2.77-fold increased risk (95% CI, 1.18 to 6.49). Abnormalities of repolarization measured by PCA of the T-wave loop predict CV death in men and women, supporting use of PCA for quantifying repolarization abnormalities.