Optimizing QT Interval Measurement for Preparticipation Screening of Young Athletes.

Abstract

Purpose: Sudden cardiac death (SCD) is the leading cause of death in athletes. Long QT Syndrome (LQTS) is one of the most common cardiogenetic diseases that can lead to SCD and is identified by QT interval prolongation on an electrocardiogram (ECG). Recommendations for QT monitoring in athletes are adopted from non-athlete populations. To improve screening, ECGs of athletes are assessed to determine a more appropriate method for QT interval estimation.

Methods: ECGs (Cardeascreen) were collected from June 2010 to March 2015. ECGs with heart rates greater than 100 bpm were excluded. Fiducial points of outliers were manually corrected if the QRS onset or T wave offset were misidentified. A model of best fit was determined and compared across four QT correction factors. Classification analysis was used to compare the Bazett's corrected QT interval to the 99th percentile uncorrected QT interval.

Results: N=597 high school, n=1207 college, and n=273 professional athletes (n=2077) were analyzed. Mean age was 19+/-3.5 years. QT interval varied by cohort (HS=388+/-30, Col=410+/-33, Pro=407+/-27, p<0.0001). A non-linear power function with a cubic exponent of -0.349 fit the data the best (R2=0.64). Of the four common correction factors, Fridericia had the lowest residual dependence to heart rate (m=-0.10). With standard screening, 75% of athletes within the top 1% for QT interval were not identified for further investigation for LQTS. Conclusion: Up to 75% of athletes possessing an uncorrected QT interval greater than 99% of the population, are not identified for investigation for LQTS using recommended criteria. We propose a new method of risk stratification that replaces QT interval correction. Further study is needed to establish QT interval distributions and risk thresholds in athletes.

(C) 2016 American College of Sports Medicine 


Autor / Fonte:David Pickham, David Hsu, Muhammad Soofi, Jana M Goldberg, Divakar Saini, David Hadley, Marco Perez, Victor F Froelicher Medicine and Science in Sports and Exercise 2016 April 26
Link: http://journals.lww.com/acsm-msse/Abstract/publishahead/Optimizing_QT_Interval_Measurement_for.97533.aspx