Reduced RR Interval Correlations of Long QT Syndrome Patients

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We study RR interval (RRI) correlations in subjects with long QT syndrome (LQTS). We aim to find distinctive differences in nonlinear heart rate variability (HRV) measures between the LQTS subjects and healthy controls. We analyze 24-hour Holter recordings from 127 healthy controls and 115 LQTS samples with unified age distributions. Beta blockers (BB), which are known to affect HRV, are a common treatment for LQTS, and that is the primary confounding factor to be accounted for. We compute conventional short-scale (4-16 RRIs) detrended fluctuation analysis (DFA) scaling exponents α1 at various degrees of detrending and compare the results to other common HRV measures. We complement the study by investigating scale-dependent exponents α(s). We find statistically significant reduction in the short-scale α1 of LQTS for subjects with (Welch's t-test p= 2.5 × 10-13) and without (p=3.2 × 10-8)BBs, These DFA-2 results yield considerable improvement over the linear detrending of DFA-1. Among other common HRV features the DFA α1 is the best indicator for LQTS. Despite the clear differences in the mean behavior, the predictive power of the measures is diminished by large individual variability. The scale-dependent picture may aid in finding optimal HRV indicators for LQTS diagnosis.

Original languageEnglish
Title of host publication2022 Computing in Cardiology, CinC 2022
ISBN (Electronic)9798350300970
Publication statusPublished - 2022
Publication typeA4 Article in conference proceedings
EventComputing in Cardiology - Tampere Hall, Tampere, Finland
Duration: 4 Sept 20227 Sept 2022
Conference number: 49

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X


ConferenceComputing in Cardiology
Abbreviated titleCinC 2022
Internet address

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • General Computer Science
  • Cardiology and Cardiovascular Medicine


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