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Improving long QT syndrome diagnosis by a polynomial-based T-wave morphology characterization.

Abstract：

BACKGROUND:Diagnosing long QT syndrome (LQTS) remains challenging because of a considerable overlap in QT interval between patients with LQTS and healthy subjects. Characterizing T-wave morphology might improve LQTS diagnosis. OBJECTIVE:The purpose of this study was to improve LQTS diagnosis by combining new polynomial-based T-wave morphology parameters with the corrected QT interval (QTc), age, and sex in a model. METHODS:A retrospective cohort consisting of 333 patients with LQTS and 345 genotype-negative family members was used in this study. For each patient, a linear combination of the first 2 Hermite-Gauss (HG) polynomials was fitted to the STT segments of an average complex of all precordial leads and limb leads I and II. The weight coefficients as well as the error of the best fit were used to characterize T-wave morphology. Subjects were classified as patients with LQTS or controls by clinical QTc cutoffs and 3 support vector machine models fed with different features. An external cohort consisting of 72 patients and 45 controls was finally used to check the robustness of the models. RESULTS:Baseline QTc cutoffs were specific but had low sensitivity in diagnosing LQTS. The model with T-wave morphology features, QTc, age, and sex had the best overall accuracy (84%), followed by a model with QTc, age, and sex (79%). The model with T-wave morphology features especially performed better in LQTS type 3 patients (69%). CONCLUSION:T-wave morphologies can be characterized by fitting a linear combination of the first 2 Hermite-Gauss polynomials. Adding T-wave morphology characterization to age, sex, and QTc in a support vector machine model improves LQTS diagnosis.

journal_name

Heart Rhythm

journal_title

Heart rhythm

authors

Hermans BJM,Bennis FC,Vink AS,Koopsen T,Lyon A,Wilde AAM,Nuyens D,Robyns T,Pison L,Postema PG,Delhaas T

doi

10.1016/j.hrthm.2019.12.020

subject

Has Abstract

pub_date

2020-05-01 00:00:00

pages

752-758

issue

5 Pt A

eissn

1547-5271

issn

1556-3871

pii

S1547-5271(20)30001-1

journal_volume

17

pub_type

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