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Published on: May 12, 2023
Sex Differences and Utility of Treadmill Testing in Long-QT Syndrome
Lauren A Yee1, Hui-Chen Han1, Brianna Davies1
1Center for Cardiovascular Innovation, Heart Rhythm Services, Division of Cardiology, Department of Medicine University of British Columbia Vancouver British Columbia Canada.
A new 3-step algorithm using exercise electrocardiogram (ECG) effectively diagnoses congenital long-QT syndrome (LQTS), even with ambiguous resting ECGs. This validated tool establishes sex-specific cutoffs for improved accuracy in identifying LQTS carriers.
Area of Science:
- Cardiology
- Genetics
- Electrocardiography
Background:
- Diagnosing congenital long-QT syndrome (LQTS) is challenging due to ambiguous phenotypes and normal-to-borderline resting QT intervals.
- A previously developed 3-step algorithm using exercise-induced corrected QT interval (QTc) changes aids LQTS diagnosis and subtype prediction.
Purpose of the Study:
- To evaluate the diagnostic and predictive utility of the 3-step QT exercise algorithm in a broader LQTS population with milder phenotypes.
- To establish sex-specific QTc cutoffs beyond resting values for improved diagnostic accuracy.
Main Methods:
- Analysis of exercise treadmill tests (Bruce protocol) in 208 LQTS variant carriers (KCNQ1, KCNH2) and 215 controls.
- Receiver operating characteristic (ROC) curve analysis to determine optimal QTc cutoffs during different exercise and recovery phases.
- Evaluation of diagnostic performance across sexes for carrier status and LQTS subtype differentiation.
Main Results:
- A significant proportion of LQTS carriers (78% males, 74% females) presented with normal-to-borderline resting QTc.
- The 4-minute recovery QTc showed the highest predictive value for carrier status (AUC 0.90 females, 0.82 males), with optimal cutoffs of 450 ms (females) and 440 ms (males).
- The 1-minute recovery QTc distinguished LQTS1 from LQTS2 in females (AUC 0.82), while peak exercise QTc was marginally better for males (AUC 0.71).
Conclusions:
- The 3-step QT exercise algorithm is a validated and reliable tool for diagnosing LQTS in populations with ambiguous phenotypes.
- The algorithm provides a simple method for identifying LQTS carriers and predicting major genotype subtypes using sex-specific QTc cutoffs.
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