Abstract 21371: Derivation and Validation of a Simple Exercise-Based Algorithm for Prediction of Genetic Testing in Relatives of LQTS Probands
Introduction: Genetic testing can confirm LQTS in asymptomatic relatives of patients with an identified mutation. However, genetic testing is costly and subject to availability. The accuracy of a simple algorithm incorporating rest and exercise ECG parameters for screening LQTS in asymptomatic relatives was evaluated, using genetic testing as the gold standard.
Methods: Asymptomatic first-degree relatives of probands were recruited from 5 centres. QT and HR were measured at rest, during exercise and recovery. ROC curves were used to establish optimal cut-offs and an algorithm was developed in a derivation cohort. The algorithm was then validated in an independent cohort.
Results: The derivation cohort consisted of 70 relatives (29 LQT1, 21 LQT2, 20 non-carriers). Mean age was 35±18 y, 61% were female and the resting QTc was 466±39 ms. Based on ROC results, resting QTc and end-recovery QTc were established as the best predictors of LQTS and incorporated into the algorithm. Resting QTc was a specific marker of LQTS with mutations found in all 25 patients with an abnormal result. However, mutations were also observed in 71% and 38% of patients with a “borderline“ or “normal” resting QTc respectively. Among these patients, an end-recovery QTc of 445 ms correctly re-stratified 22/24 patients as having “probable LQTS” and 18/21 patients as being “probable non-carriers”. The sensitivity, specificity and overall accuracy of the algorithm were 0.94, 0.90 and 0.93 respectively. When applied to an independent validation cohort (N=117, 45 LQT1, 39 LQT2, 33 non-carriers), the sensitivity, specificity and overall accuracy were 0.94, 0.82 and 0.91 respectively.
Conclusions: A clinical algorithm incorporating resting and exercise-recovery QTc is useful in identifying LQTS in asymptomatic relatives of patients with known LQTS.
- © 2010 by American Heart Association, Inc.