Background Asymptomatic individuals account for a majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and non-invasive SCD risk stratification tools are necessary. Methods and Results Participants from the Atherosclerosis Risk in Communities study and Cardiovascular Health Study (n=20,177; age 59.3±10.1 years; age range 44–100; 56% female; 77% white) were followed for 14.0 years (median). Five ECG markers of global electrical heterogeneity (GEH) (sum absolute QRST integral, spatial QRST angle, spatial ventricular gradient (SVG) magnitude, SVG elevation, and SVG azimuth) were measured on standard 12-lead ECGs. Cox proportional hazards and competing risks models evaluated associations between GEH ECG parameters and SCD. A SCD competing risks score was derived using demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1,000 person-years. After multivariable adjustment, baseline GEH parameters and large increases in GEH parameters over time were independently associated with SCD. Final SCD risk scores included age, sex, race, diabetes, hypertension, coronary heart disease, and stroke, and GEH parameters as continuous variables. When GEH parameters were added to clinical/demographic factors, the C-statistic increased from 0.777 to 0.790 (p=0.008), the risk score classified 10-year SCD risk as high (>5%) in 7.2% of participants, 10% of SCD victims were appropriately reclassified into a high-risk category, and only 1.4% of SCD victims were inappropriately reclassified from high- to intermediate-risk. Net reclassification index was 18.3%. Conclusions Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. Addition of GEH parameters to clinical characteristics improves SCD risk prediction.
Cardiac and respiratory rhythms reveal transient phases of phase-locking which were proposed to be an important aspect of cardiorespiratory interaction. The aim of this study was to quantify cardio-respiratory phase-locking in obstructive sleep apnea (OSA). We investigated overnight polysomnography data of 248 subjects with suspected OSA. Cardiorespiratory phase-coupling was computed from the R-R intervals of body surface ECG and respiratory rate, calculated from abdominal and thoracic sensors, using Hilbert transform. A significant reduction in phase-coupling was observed in patients with severe OSA compared to patients with no or mild OSA. Cardiorespiratory phase-coupling was also associated with sleep stages and was significantly reduced during rapid-eye-movement (REM) sleep compared to slow-wave (SW) sleep. There was, however, no effect of age and BMI on phase coupling. Our study suggests that the assessment of cardiorespiratory phase coupling may be used as an ECG based screening tool for determining the severity of OSA.
Abstract-Cardiac and respiratory rhythms are highly nonlinear and nonstationary. As a result traditional time-domain techniques are often inadequate to characterize their complex dynamics. In this article, we introduce a novel technique to investigate the interactions between R-R intervals and respiratory phases based on their joint symbolic dynamics. To evaluate the technique, electrocardiograms (ECG) and respiratory signals were recorded in 13 healthy subjects in different body postures during spontaneous and controlled breathing. Herein, the R-R time series were extracted from ECG and respiratory phases were obtained from abdomen impedance belts using the Hilbert transform. Both time series were transformed into ternary symbol vectors based on the changes between two successive R-R intervals or respiratory phases. Subsequently, words of different symbol lengths were formed and the correspondence between the two series of words was determined to quantify the interaction between cardiac and respiratory cycles. To validate our results, respiratory sinus arrhythmia (RSA) was further studied using the phase-averaged characterization of the RSA pattern. The percentage of similarity of the sequence of symbols, between the respective words of the two series determined by joint symbolic dynamics, was significantly reduced in the upright position compared to the supine position (26.4 ± 4.7 vs. 20.5 ± 5.4%, p < 0.01). Similarly, RSA was also reduced during upright posture, but the difference was less significant (0.11 ± 0.02 vs. 0.08 ± 0.01 s, p < 0.05). In conclusion, joint symbolic dynamics provides a new efficient technique for the analysis of cardiorespiratory interaction that is highly sensitive to the effects of orthostatic challenge.
Atrial fibrillation (AF) is the most common arrhythmia in adults and is associated with significant morbidity and mortality. Substantial interest has developed in the primary prevention of AF, and thus the identification of individuals at risk for developing AF. The electrocardiogram (ECG) provides a wealth of information which is of value in predicting incident AF. The PR interval and P wave indices (including P wave duration, P wave terminal force, P wave axis, and other measures of P wave morphology) are discussed with regard to their ability to predict and characterize AF risk in the general population. The predictive value of the QT interval, ECG criteria for left ventricular hypertrophy, and findings of atrial and ventricular ectopy are also discussed. Efforts are underway to develop models which predict AF incidence in the general population, however, at present little information from the ECG is included in these models. The ECG provides a great deal of information on AF risk and has the potential to contribute substantially to AF risk estimation, but more research is needed.
The single leading cause of mortality on hemodialysis is sudden cardiac death. Whether measures of electrophysiologic substrate independently associate with mortality is unknown. We examined measures of electrophysiologic substrate in a prospective cohort of 571 patients on incident hemodialysis enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease Study. A total of 358 participants completed both baseline 5-minute and 12-lead electrocardiogram recordings on a nondialysis day. Measures of electrophysiologic substrate included ventricular late potentials by the signal-averaged electrocardiogram and spatial mean QRS-T angle measured on the averaged beat recorded within a median of 106 days (interquartile range, 78-151 days) from dialysis initiation. The cohort was 59% men, and 73% were black, with a mean±SD age of 55±13 years. Transthoracic echocardiography revealed a mean±SD ejection fraction of 65.5%±12.0% and a mean±SD left ventricular mass index of 66.6±22.3 g/m During 864.6 person-years of follow-up, 77 patients died; 35 died from cardiovascular causes, of which 15 were sudden cardiac deaths. By Cox regression analysis, QRS-T angle ≥75° significantly associated with increased risk of cardiovascular mortality (hazard ratio, 2.99; 95% confidence interval, 1.31 to 6.82) and sudden cardiac death (hazard ratio, 4.52; 95% confidence interval, 1.17 to 17.40) after multivariable adjustment for demographic, cardiovascular, and dialysis factors. Abnormal signal-averaged electrocardiogram measures did not associate with mortality. In conclusion, spatial QRS-T angle but not abnormal signal-averaged electrocardiogram significantly associates with cardiovascular mortality and sudden cardiac death independent of traditional risk factors in patients starting hemodialysis.
Background ECG global electrical heterogeneity (GEH) is associated with sudden cardiac death. We hypothesized that a genome‐wide association study would identify genetic loci related to GEH.Methods and ResultsWe tested genotyped and imputed variants in black (N=3057) and white (N=10 769) participants in the ARIC (Atherosclerosis Risk in Communities) study and CHS (Cardiovascular Health Study). GEH (QRS‐T angle, sum absolute QRST integral, spatial ventricular gradient magnitude, elevation, azimuth) was measured on 12‐lead ECGs. Linear regression models were constructed with each GEH variable as an outcome, adjusted for age, sex, height, body mass index, study site, and principal components to account for ancestry. GWAS identified 10 loci that showed genome‐wide significant association with GEH in whites or joint ancestry. The strongest signal (rs7301677, near TBX3) was associated with QRS‐T angle (white standardized β+0.16 [95% CI 0.13–0.19]; P=1.5×10−26), spatial ventricular gradient elevation (+0.11 [0.08–0.14]; P=2.1×10−12), and spatial ventricular gradient magnitude (−0.12 [95% CI −0.15 to −0.09]; P=5.9×10−15). Altogether, GEH‐SNPs explained 1.1% to 1.6% of GEH variance. Loci on chromosomes 4 (near HMCN2), 5 (IGF1R), 11 (11p11.2 region cluster), and 7 (near ACTB) are novel ECG phenotype‐associated loci. Several loci significantly associated with gene expression in the left ventricle (HMCN2 locus—with HMCN2;IGF1R locus—with IGF1R), and atria (RP11‐481J2.2 locus—with expression of a long non‐coding RNA and NDRG4).ConclusionsWe identified 10 genetic loci associated with ECG GEH. Replication of GEH GWAS findings in independent cohorts is warranted. Further studies of GEH‐loci may uncover mechanisms of arrhythmogenic remodeling in response to cardiovascular risk factors.
Cardiac resynchronization therapy (CRT) reduces mortality and morbidity in selected heart failure (HF) patients, but up to one-third of patients are non-responders. Sum absolute QRST integral (SAI QRST) recently showed association with mechanical response on CRT. However, it is unknown whether SAI QRST is associated with all-cause mortality and HF hospitalizations in CRT patients. The study population included 496 patients undergoing CRT (mean age 69±10 years, 84% male, 65% left bundle branch block (LBBB), left ventricular ejection fraction 23±6%, 63% ischemic cardiomyopathy). Pre-implant digital 12-lead ECG was transformed into orthogonal XYZ ECG. SAI QRST was measured as an arithmetic sum of areas under the QRST curve on XYZ leads, and was dichotomized based on the median value (302mV*ms). All-cause mortality served as the primary endpoint. A composite of 2-year all-cause mortality, heart transplant, and HF hospitalization was a secondary endpoint. Cox regression models were adjusted for known predictors of CRT response. Patients with pre-implant low mean SAI QRST had an increased risk of both the primary (HR 1.8; 95%CI 1.01–3.2) and secondary (HR 1.6, 95% CI 1.1–2.2) endpoints following multivariable adjustment. SAI QRST was associated with secondary outcome in subgroups of patients with LBBB (HR 2.1 [95%CI 1.5-3.0]) and with non-LBBB (HR 1.7, [95%CI 1.0-2.6]). In patients undergoing CRT, pre-implant SAI QRST<302mV*ms was associated with an increased risk of all-cause mortality and HF hospitalization. After validation in another prospective cohort, SAI QRST may help to refine selection of CRT recipients.
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