Effect of beta-blockers on QT dynamics in the long QT syndrome: measuring the benefit.

AIMS: Beta-blockers are the standard of care for the treatment of long QT syndrome (LQTS), and have been shown to reduce recurrent syncope and mortality in patients with type 1 LQTS (LQT1). Although beta-blockers have minimal effect on the resting corrected QT interval, their effect on the dynamics of the non-corrected QT interval is unknown, and may provide insight into their protective effects. METHODS AND RESULTS: Twenty-three patients from eight families with genetically distinct mutations for LQT1 performed exercise stress testing before and after beta-blockade. One hundred and fifty-two QT, QTc, and Tpeak-Tend intervals were measured before starting beta-blockers and compared with those at matched identical cycle lengths following beta-blockade. Beta-blockers demonstrated heart-rate-dependent effects on the QT and QTc intervals. In the slowest heart rate tertile (<90 b.p.m.), beta-blockade increased the QT and QTc intervals (QT: 405 vs. 409 ms; P = 0.06; QTc: 459 vs. 464 ms; P = 0.06). In the fastest heart rate tertile (>100 b.p.m.), the use of beta-blocker was associated with a reduction in both the QT and QTc intervals (QT: 367 vs. 358 ms; P < 0.0001; QTc: 500 vs. 486 ms; P < 0.0001). The Tpeak-Tend interval showed minimal change at slower heart rates (<90 b.p.m.) (93 vs. 87 ms; P = 0.09) and at faster heart rates (>100 b.p.m.) (87 vs. 84 ms; P = NS) following beta-blockade. CONCLUSION: Beta-blockers have heart-rate-dependent effects on the QT and QTc intervals in LQTS. They appear to increase the QT and QTc intervals at slower heart rates and shorten them at faster heart rates during exercise.

Derivation and validation of a simple exercise-based algorithm for prediction of genetic testing in relatives of LQTS probands.

BACKGROUND: Genetic testing can diagnose long-QT syndrome (LQTS) in asymptomatic relatives of patients with an identified mutation; however, it is costly and subject to availability. The accuracy of a simple algorithm that incorporates resting and exercise ECG parameters for screening LQTS in asymptomatic relatives was evaluated, with genetic testing as the gold standard. METHODS AND RESULTS: Asymptomatic first-degree relatives of genetically characterized probands were recruited from 5 centers. QT intervals were measured at rest, during exercise, and during recovery. Receiver operating characteristics were used to establish optimal cutoffs. An algorithm for identifying LQTS carriers was developed in a derivation cohort and validated in an independent cohort. The derivation cohort consisted of 69 relatives (28 with LQT1, 20 with LQT2, and 21 noncarriers). Mean age was 35±18 years, and resting corrected QT interval (QTc) was 466±39 ms. Abnormal resting QTc (females ≥480 ms; males ≥470 ms) was 100% specific for gene carrier status, but was observed in only 48% of patients; however, mutations were observed in 68% and 42% of patients with a borderline or normal resting QTc, respectively. Among these patients, 4-minute recovery QTc ≥445 ms correctly restratified 22 of 25 patients as having LQTS and 19 of 21 patients as being noncarriers. The combination of resting and 4-minute recovery QTc in a screening algorithm yielded a sensitivity of 0.94 and specificity of 0.90 for detecting LQTS carriers. When applied to the validation cohort (n=152; 58 with LQT1, 61 with LQT2, and 33 noncarriers; QTc=443±47 ms), sensitivity was 0.92 and specificity was 0.82. CONCLUSIONS: A simple algorithm that incorporates resting and exercise-recovery QTc is useful in identifying LQTS in asymptomatic relatives.

Repolarization dynamics during exercise discriminate between LQT1 and LQT2 genotypes.

UNLABELLED: Genotype and Exercise in LQTS. BACKGROUND: Repolarization dynamics during exercise in patients with long-QT Syndrome (LQTS) may be influenced by various factors such as a patient's genotype. We sought to systematically characterize the repolarization dynamics during exercise in patients with LQTS with a particular focus on the influence of genotype. METHODS: Three groups of patients were studied on the basis of clinical status and genotype: LQT1, LQT2, and normal controls. Twenty-five age- and gender-matched patients were selected for each group. The QTc was measured during bicycle exercise testing and its dynamics were compared between the 3 groups. RESULTS: The degree of QTc prolongation during exercise was greater in LQTS patients (LQT1 80 ± 47 ms, LQT2 64 ± 41 ms, Control 46 ± 20 ms, P = 0.02), with significant differences between LQT1 and LQT2 patients observed at heart rates ≥ 60% of the predicted maximum (P < 0.05). LQT1 patients demonstrated progressive or persistent QTc prolongation at higher heart rates, whereas LQT2 patients demonstrated maximum QTc prolongation at submaximal heart rates (50% of the predicted maximum) with subsequent QTc correction toward baseline values at higher heart rates. Importantly, these observations were consistent regardless of age, gender, or exercise type in subgroup analyses. CONCLUSIONS: Reduced repolarization reserve in LQTS is genotype and heart rate specific.

Utility of the recovery electrocardiogram after exercise: a novel indicator for the diagnosis and genotyping of long QT syndrome?

BACKGROUND: Exercise testing has shown modest utility in the ability to diagnose and genotype long QT syndrome (LQTS). Although numerous small studies have shown a genotype-specific repolarization response to exercise, the repolarization responses during recovery from exercise have received less focus. OBJECTIVE: The purpose of this study was to characterize genotype-specific QT responses during recovery from exercise and to determine its potential as a diagnostic and genotyping tool. METHODS: Seventy-five patients were age and sex matched into three groups (n = 25): LQT1, LQT2, and unaffected controls based on Schwartz score and genetic testing results. Each group underwent upright burst and gradual bicycle exercise testing while being monitored by 12-lead electrocardiogram. RESULTS: LQT1 patients had significantly longer corrected QT (QTc) than LQT2 intervals during early recovery (P <.01). Control subjects showed little variation in QTc throughout the recovery period, maintaining a QTc within normal limits. Each group showed a distinct pattern of QTc adaptation during recovery. LQT1 patients began the recovery period at a QTc of 492 +/- 11 ms, after which the QTc decreased by 33 +/- 11 ms during recovery. Conversely, the LQT2 patients began recovery at its lowest mean QTc of 420 +/- 10 ms, which increased by 40 +/- 16 ms. At the end of recovery, a QTc cut-off value of 445 ms distinguished 92% of LQTS patients from unaffected controls, while a start-of-recovery QTc cut-off of 460 ms correctly identified genotype in 80% of LQT1 and 92% of LQT2 patients. CONCLUSIONS: Genotype-specific differences exist in QT recovery after exercise. These differences can help to identify LQTS patients and distinguish LQT1 from LQT2 genotypes.

Expression of a common LQT1 mutation in five apparently unrelated families in a regional inherited arrhythmia clinic.

BACKGROUND: The Inherited Arrhythmia Clinic at the University of Western Ontario services a catchment area of 1.5 million people and follows families with inherited arrhythmia syndromes. METHODS: Patients referred for evaluation of long-QT Syndrome (LQTS) are evaluated with resting and standing ECGs, and treadmill exercise testing. Patients with findings consistent with LQTS are offered comprehensive genetic testing with screening of all first-degree relatives of genotype-positive patients. RESULTS: Among 31 probands with disease-causing LQTS mutations, 5 probands from apparently unrelated families of Irish descent were found to have an identical disease causing transmembrane mutation in KCNQ1 (Leu266Pro). Systematic screening of 33 first-degree relatives of genotype-positive individuals detected 15 unaffected and 18 asymptomatic affected family members. Symptoms in 6 patients occurred later in life than reported LQT1 populations (61 +/- 18 years, range 44-89). In this cohort, several family members presented with cardiac arrest during acute myocardial ischemia (n = 2), sudden death, unexplained drowning, and torsade de pointes during exercise testing. There was no identifiable common relative for this cohort after pedigree construction of the previous 4-7 generations. Affected patients had mild QT prolongation at rest with dramatic QT prolongation with exercise. CONCLUSIONS: Genetic testing in this LQTS population suggests a common KCNQ1 Leu266Pro founder effect, with the descendants clustering in our geographical region even though no common relative has been identified. The observations highlight the utility of genotypic and phenotypic correlation and a specialized clinic.