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Lifetime sex-specific sudden cardiac death prediction using ECG global electrical heterogeneity: the atherosclerosis risk in communities (ARIC) study

Session Poster Session 6

Speaker Stacey Howell

Congress : ESC Congress 2019

  • Topic : arrhythmias and device therapy
  • Sub-topic : Ventricular Arrhythmias and SCD - Prevention
  • Session type : Poster Session
  • FP Number : P5645

Authors : S Howell (Portland,US), E Perez-Alday (Portland,US), D German (Portland,US), A Bender (Portland,US), N Rogovoy (Portland,US), K Haq (Portland,US), L Tereshchenko (Portland,US)

S Howell1 , E Perez-Alday1 , D German1 , A Bender1 , N Rogovoy1 , K Haq1 , L Tereshchenko1 , 1Oregon Health and Science University - Portland - United States of America ,


Background: Sex-based differences in sudden cardiac death (SCD) exist and screening methods for SCD are inadequate.

Purpose: To develop sex-specific lifetime risk prediction models using electrocardiographic (ECG) global electrical heterogeneity (GEH) and clinical characteristics.

Methods: Participants from the Atherosclerosis Risk in Communities study with analyzable ECGs (n=14,725; age, 54.2±5.8 yrs; 55% female, 74% white) were followed up for 24.4 years (median). Traditional ECG and GEH variables were measured on 12-lead ECGs. A Cox regression model was used to develop a prediction model. In women, the final model included race, age, coronary heart disease (CHD), stroke, hypertension, diabetes, smoking, high-density lipoprotein, albumin, uric acid, education level, heart rate, QTc, sum absolute QRST integral, spatial peak QRS-T angle. In men, the final prediction model included age, race, CHD, stroke, hypertension, diabetes, total cholesterol, physical activity, smoking, serum phosphorus, albumin, chronic kidney disease, spatial area QRS-T angle, area spatial ventricular gradient (SVG) elevation and magnitude, and peak SVG magnitude.

Results: There were a total of 530 SCDs. Our prediction models showed robust prediction of SCD in both sexes [(Harrell’s C-statistic women 0.863 (95% CI 0.845-0.882), men 0.786 (95%CI 0.786-0.803)]. In women when ECG and GEH variables were added to clinical variables, the net reclassification improved by 9% (P=0.001) (Table). In men there was no significant reclassification improvement.

Conclusions: We were the first to develop sex-specific lifetime SCD prediction models. The addition of ECG GEH to clinical variables improved SCD risk reclassification in women, but not in men. Prediction of SCD was more accurate in women as compared to men.

Lifetime SCD Risk: Clinical + ECG + GEH Variables
Women Men
<5% 5-15% >15% Total <5% 5-15% >15% Total

Lifetime SCD Risk:

Clinical Variables Only



<5% 82 14 0 96 103 16 0 119
5-15% 7 59 10 76 12 116 12 140
>15% 0 0 20 20 0 5 74 79
Total 89 73 30 192 115 137 86 338



<5% 6,956 131 2 7,089 4,411 264 0 4,675
5-15% 180 509 42 731 210 1,059 48 1,317
>15% 0 28 84 112 0 56 214 270
Total 7,136 668 128 7,932 4,621 1,379 262 6,262

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