479 The association of QTc and QT Variability with Severity of Sleep Disordered Breathing

Introduction The apneas and hypopneas that characterize sleep-disordered breathing (SDB) are associated with QTc prolongation and increased QT variability. There have been mixed results as to whether QTc and QT variability increase with increasing SDB severity. This study assesses whether QTc prolongation and QT variability are likely to increase with increasing severity of SDB in a large multi-center cohort. Methods 200 subjects with no SDB and approximately 600 with three levels of SDB (mild, moderate, severe) were randomly selected from the Sleep Heart Health study and matched by age, gender and BMI. SDB was defined as an apnea/hypopnea index ≥5. Respiratory and electrocardiograms (ECG) signals from polysomnography studies were analyzed. Bazett’s heart rate correction was used to calculate QTc. QT variability was measured as standard deviation of QT intervals (SDQT) and short-term interval QT variability (STVQT), at 5-minute intervals. Subjects were excluded if there were missing data or low-quality ECG. Results Seven hundred and seventy-one subjects (age 68±10 years, 51% female, 92% Caucasian) were included. One hundred and sixty-five subjects had no SDB, 235 mild, 195 moderate and 176 had severe SDB. The mean (SD) QTc was 422(29), 411(26), 419 (34) and 418 (36) ms for the no SDB, mild, moderate, and severe SDB groups, respectively (p=0.017). The mean (SD) STVQT was 7 (9), 11 (16), 8 (9) and 9 (11) for the no SDB, mild, moderate severe SDB groups, respectively (p=<0.001). The mean (SD) STVQT was 3 (2), 4 (4), 4 (3) and 4(4) for the no SDB, mild, moderate severe SDB groups, respectively (p=<0.001). There was no statistically linear relationship between QT prolongation or QT variability and SBD severity. Conclusion QTc duration and QT variability were not increased with SDB severity. Support (if any) American Academy of Sleep Medicine Foundation (203-JF-18), National Institutes of Health (HL126140), University of Arizona Health Sciences Career Development Award (5299903), and University of Arizona Faculty Seed Grant (5833261)

478 The Relationship between Sleep Disordered Breathing, Markers of Ventricular Repolarization and Cardiovascular Mortality

Introduction Sleep disordered breathing (SDB) is associated with increased mortality. Obstructive apneas/hypopneas have been associated with an increase in both QTc duration and QT variability. These markers of ventricular repolarization are associated with arrhythmias and death. It is unknown whether SDB-related QTc changes are responsible for the relationship between QTc/QT variability and cardiovascular death (CVD). Methods From the Sleep Heart Health Study, we randomly selected 200 subjects in each of four groups based on overall apnea/hypopnea index: those with no SDB and those in either, mild, moderate or severe SDB at baseline, matched for gender, age and BMI. Respiratory-related channels and electrocardiograms (ECG) from each polysomnography were analyzed. QTc was calculated using Bazett’s heart rate correction. The following measures of QT variability were obtained: i) standard deviation of QT intervals (SDQT) at 1- and 5-minute intervals and ii) short-term interval QT variability (STVQT) at 5-minute intervals. Cox proportional hazards regression models were used to evaluate potential predictors of CVD. Results Twenty-nine subjects were excluded either due to missing data or low quality ECG. The 771 subjects included were 68±10 years of age, half were female. During follow-up, 220 subjects (28.5%) died of CVD among whom, 67 (30.5%) had comorbid severe SDB, 45 (20.5%) had no SDB, and the remaining CVD deaths had mild (47, 21.4%) and moderate 61 (27.7%) SDB. The CVD patients were more likely to be older(p<0.001), hypertensive (p<0.001), diabetic(p<0.001), and had increased SDQT(p<0.001), STVQT(p<0.001) and QTc (0.017). After adjusting for covariates, the presence of mild (p=0.562), moderate(p=0.439) and severe SDB (p=0.912) did not moderate the association between QTc prolongation and CVD. Additionally, mild (p=0.486), moderate(p=0.478) and severe SDB (p=0.849) did not moderate the association between SDQT and CVD. Similarly, mild (p=0.144), moderate(p=0.594) and severe SDB (p=0.508) did not moderate the association between STVQT and CVD. However, QTc, SDQT, STVQT, mild and severe SDB were individually associated with CVD (p=0.004, 0.000, 0.000, 0.014, 0.022, respectively). Conclusion SDB was not a factor in the relationship between QTc prolongation/QT variability and CVD. Support (if any) American Academy of Sleep Medicine Foundation (203-JF-18), National Institutes of Health (HL126140), University of Arizona Health Sciences Career and Development Award (5299903)

Absence of Rgs5 Influences the Spatial and Temporal Fluctuation of Cardiac Repolarization in Mice

AimsThis study investigated the contribution of the regulator of G-protein signaling 5 (Rgs5) knockout to the alteration of the action potential duration (APD) restitution and repolarizing dispersion in ventricle.Methods and ResultsThe effects of Rgs5–/– were investigated by QT variance (QTv) and heart rate variability analysis of Rgs5–/– mice. Monophasic action potential analysis was investigated in isolated Rgs5–/– heart. Rgs5–/– did not promote ventricular remodeling. The 24-h QTv and QT variability index (QTVI) of the Rgs5–/– mice were higher than those of wild-type (WT) mice (P < 0.01). In WT mice, a positive correlation was found between QTv and the standard deviation of all NN intervals (r = 0.62; P < 0.01), but not in Rgs5–/– mice (R = 0.01; P > 0.05). The absence of Rgs5 resulted in a significant prolongation of effective refractory period and APD in isolated ventricle. In addition, compared with WT mice, the knockout of Rgs5 significantly deepened the slope of the APD recovery curve at all 10 sites of the heart (P < 0.01) and increased the spatial dispersions of Smax (COV-Smax) (WT: 0.28 ± 0.03, Rgs5–/–: 0.53 ± 0.08, P < 0.01). Compared with WT heart, Rgs5–/– increased the induced S1–S2 interval at all sites of heart and widened the window of vulnerability of ventricular tachyarrhythmia (P < 0.05).ConclusionOur findings indicate that Rgs5–/– is an important regulator of ventricular tachyarrhythmia in mice by prolonging ventricular repolarization and increasing spatial dispersion in ventricle.

Simple heart rate and QT parameters during stress exercise testing to assess presence and severity of stable coronary artery disease

Aim: The relationship between QT prolongation and myocardial ischemia is well known, however not many studies have correlated corrected QT interval and heart rate recovery with the severity of coronary artery disease (CAD). Methods: This was a single-center, prospective, observational study which included 127 patients with CAD and 124 patients without CAD. Results: Corrected QT variability from peak to recovery correlated well with CAD with a p value of 0.03. Receiver operative characteristic analysis did not show any significant diagnostic accuracy with any heart rate or QT parameters for predicting the presence or severity of CAD. Conclusion: Coronary artery disease is predicted by reduced ability of the heart rate to rise from rest to peak exercise and reduced recovery of heart rate and corrected QT from peak exercise to recovery at 1 min.

Heart Rate Influence on the QT Variability Risk Factors

QT interval variability, mostly expressed by QT variability index (QTVi), has repeatedly been used in risk diagnostics. Physiologic correlates of QT variability expressions have been little researched especially when measured in short 10-second electrocardiograms (ECGs). This study investigated different QT variability indices, including QTVi and the standard deviation of QT interval durations (SDQT) in 657,287 10-second ECGs recorded in 523 healthy subjects (259 females). The indices were related to the underlying heart rate and to the 10-second standard deviation of RR intervals (SDRR). The analyses showed that both QTVi and SDQT (as well as other QT variability indices) were highly statistically significantly (p < 0.00001) influenced by heart rate and that QTVi showed poor intra-subject reproducibility (coefficient of variance approaching 200%). Furthermore, sequential analysis of regression variance showed that SDQT was more strongly related to the underlying heart rate than to SDRR, and that QTVi was influenced by the underlying heart rate and SDRR more strongly than by SDQT (p < 0.00001 for these comparisons of regression dependency). The study concludes that instead of QTVi, simpler expressions of QT interval variability, such as SDQT, appear preferable for future applications especially if multivariable combination with the underlying heart rate is used.

QT Variability Index is Correlated with Autonomic Nerve Activity in Healthy Children

The QT variability index (QTVI), which measures the instability of myocardial repolarization, is usually calculated from a single electrocardiogram (ECG) recording and can be easily applied in children. It is well known that frequency analysis of heart rate variability (HRV) can detect autonomic balance, but it is not clear whether QTVI is correlated with autonomic tone. Therefore, we evaluated the association between QTVI and HRV to elucidate whether QTVI is correlated with autonomic nerve activity. Apparently, healthy 320 children aged 0–7 years who visited Fujita Health University Hospital for heart checkup examinations were included. The RR and QT intervals of 60 continuous heart beats were measured, and the QTVI was calculated using the formula of Berger et al. Frequency analysis of HRV, including the QTVI analysis region, was conducted for 2 min and the ratio of low-frequency (LF) components to high-frequency (HF) components (LF/HF) and HF/(LF + HF) ratio was calculated as indicators of autonomic nerve activity. Then, the correlations between QTVI and these parameters were assessed. QTVI showed a significant positive correlation with LF/HF ratio (r = 0.45, p < 0.001) and negative correlation with HF/(LF + HF) ratio (r = −0.429, p < 0.001). These correlations remained after adjustment for sex and age. QTVI, which is calculated from non-invasive ECG and can detect abnormal myocardial repolarization, is significantly correlated with frequency analysis of HRV parameters. QTVI reflects autonomic nerve balance in children.

0571 Repolarization Variability Predicts Cardiovascular Death in Obstructive Sleep Apnea

Introduction Patients with untreated obstructive sleep apnea (OSA) have a 2-3—fold increased risk of cardiovascular mortality (CVD) compared with individuals without OSA. QTc prolongation and increased QT variability among OSA patients may contribute to this association. Methods Patients with OSA from the Sleep Heart Health study were identified based on polysomnography criteria and their continuous electrocardiograms (ECG) analyzed for QTc duration and QT variability. Both Fridericia’s and Bazett’s heart rate corrections were used to calculate QTc. QT variability was measured as standard deviation of QT intervals (SDQT) and normalized QT interval variance (QTVN) at 1- and 5-minute intervals and short-term interval beat-to-beat QT variability (STVQT) was measured at 5-minute intervals. Lasso with elastic-net regularization was used as the variable/covariate selection method. Cox proportional hazards regression models were used to determine predictors of CVD. Results Data from 365 patients with OSA were screened. Ninety-seven patients were excluded from analysis due to low quality ECG data (n=50) or extremely high (&gt; ln (10)) variability in QT/QTc and/or QT variability (n=12). Fifty two percent of the sample was male with mean age 65 years (±10). Fifty-six of these patients died of CVD. The mean (SD) QTc in the group that died was 411 (30) ms and 416 (34) ms compared to 406 (24) ms and 411 (25) ms using Fridericia (Cox LR p-value 0.055) and Bazett (p=0.090), respectively. Gender, age, race, diabetes, SDQT and STVQT were significant predictors for CVD. We fit models with the covariates and SDQT (at both 1 and 5 min) and STVQT as three models and demonstrate that both SDQT and STVQT are significantly associated with CVD death (p-values of 0.0048, 0.0089, and 0.0113, respectively) and all models had high area under the curve (0.8095, 0.8085, and 0.8125, respectively). Conclusion In patients with OSA, QT variability was associated with CVD. Support American Academy of Sleep Medicine Foundation