Jonathan W Waks1, Colleen M Sitlani1, Elsayed Z Soliman1, Muammar Kabir1, Elyar Ghafoori1, Mary L Biggs1, Charles A Henrikson1, Nona Sotoodehnia1, Tor Biering-Sørensen1, Sunil K Agarwal1, David S Siscovick1, Wendy S Post1, Scott D Solomon1, Alfred E Buxton1, Mark E Josephson1, Larisa G Tereshchenko2. 1. From Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (J.W.W., A.E.B., M.E.J.); Cardiovascular Health Research Unit, Division of Cardiology, and Department of Epidemiology(C.M.S., M.L.B., N.S., D.S.S.)and Department of Biostatistics (M.L.B.), University of Washington, Seattle; Epidemiological Cardiology Research Center, Division of Public Health Sciences and Department of Medicine, Cardiology Section, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.); Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., E.G., C.A.H., L.G.T.); Brigham and Women's Hospital, Harvard Medical School, Boston, MA (T.B.-S., S.D.S.); Department of Epidemiology, Internal Medicine and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins School of Public Health, Baltimore, MD (S.K.A.); New York Academy of Medicine, New York (D.S.S.); and Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.). 2. From Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (J.W.W., A.E.B., M.E.J.); Cardiovascular Health Research Unit, Division of Cardiology, and Department of Epidemiology(C.M.S., M.L.B., N.S., D.S.S.)and Department of Biostatistics (M.L.B.), University of Washington, Seattle; Epidemiological Cardiology Research Center, Division of Public Health Sciences and Department of Medicine, Cardiology Section, Wake Forest School of Medicine, Winston Salem, NC (E.Z.S.); Knight Cardiovascular Institute, Oregon Health & Science University, Portland (M.K., E.G., C.A.H., L.G.T.); Brigham and Women's Hospital, Harvard Medical School, Boston, MA (T.B.-S., S.D.S.); Department of Epidemiology, Internal Medicine and Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins School of Public Health, Baltimore, MD (S.K.A.); New York Academy of Medicine, New York (D.S.S.); and Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (W.S.P., L.G.T.). tereshch@ohsu.edu.
Abstract
BACKGROUND: Asymptomatic individuals account for the majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and noninvasive SCD risk stratification tools is 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 years; 56% female; 77% white) were followed up for 14.0 years (median). Five ECG markers of global electric 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 electrocardiographic parameters and SCD. An SCD competing risks score was derived from demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1000 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 mellitus, hypertension, coronary heart disease, 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. The net reclassification index was 18.3%. CONCLUSIONS: Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. The addition of GEH parameters to clinical characteristics improves SCD risk prediction.
BACKGROUND: Asymptomatic individuals account for the majority of sudden cardiac deaths (SCDs). Development of effective, low-cost, and noninvasive SCD risk stratification tools is 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 years; 56% female; 77% white) were followed up for 14.0 years (median). Five ECG markers of global electric 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 electrocardiographic parameters and SCD. An SCD competing risks score was derived from demographics, comorbidities, and GEH parameters. SCD incidence was 1.86 per 1000 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 mellitus, hypertension, coronary heart disease, 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. The net reclassification index was 18.3%. CONCLUSIONS: Abnormal electrophysiological substrate quantified by GEH parameters is independently associated with SCD in the general population. The addition of GEH parameters to clinical characteristics improves SCD risk prediction.
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