Weighted Time Warping Improves T-Wave Morphology Markers Clinical Significance

Abstract

Background: T-wave (TW) morphology indices based on time-warping ( d_w) have shown significant cardiovascular risk stratification value. However, errors in the location of TW boundaries may impact their prognostic power. Our aim was to test the hypothesis that a weighted time-warping function (WF) would reduce the sensitivity of d_w to these errors and improve their clinical significance.

Methods: The WFs were proportional to (i) the reference TW ( T), and (ii) the absolute value of its derivative ( D). The index d_w was recalculated using these WFs, and its performance was compared to the unweighted control case ( C) in four different scenarios: 1) robustness against simulated TW boundaries location errors; 2) ability to retain physiological information in an electrophysiological cardiac model; 3) ability to monitor blood potassium concentration changes ( ∆[K⁺]) in 29 hemodialysis (HD) patients; 4) and the sudden cardiac death (SCD) risk stratification value of the TW morphology restitution (TMR) index, derived from d_w, in 651 chronic heart failure (CHF) patients.

Results and discussion: The WFs led to a reduced sensitivity ( R) of d_w to TW boundary location errors as compared to C (median R=0.19 and 0.22 and 0.35 for T, D and C, respectively). They also preserved the physiological relationship between d_w and repolarization dispersion changes at ventricular level. No improvements in ∆[K⁺] tracking were observed for the HD patients (Pearson's median correlation [ r] between ∆[K⁺] and d_w was 0.86 ≤ r ≤ 0.90 for T, D and C). In CHF patients, the SCD risk stratification value of TMR was improved by applying T (hazard ratio, HAR, of 2.80), followed by D (HAR=2.32) and C (HAR=2.23).

Conclusions and significance: The proposed WFs, with T showing the best performance, increased the robustness of time-warping based markers against TW location errors preserving their physiological information content and boosting their SCD risk stratification value. Results from this work support the use of T when deriving d_w for future clinical applications.