A nonparametric approach to QT interval correction for heart rate
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Updated: Jun 14, 2026

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Published on: August 1, 2019
Duolao Wang1, Yin Bun Cheung, Radivoj Arezina
1Medical Statistics Unit, Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom. Duolao.Wang@lshtm.ac.uk
Abstract:
We propose to use generalized additive models to fit the relationship between QT interval and RR (RR = 60/heart rate), and develop two new methods for correcting the QT for heart rate: the linear additive model and log-transformed linear additive model. The proposed methods are compared with six commonly used parametric models that were used in four clinical trial data sets and a simulated data set. The results show that the linear additive models provide the best fit for the vast majority of individual QT-RR profiles. Moreover, the QT correction formula derived from the linear additive model outperforms other correction methods.
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