Study population
The ARIC study is an ongoing prospective cohort study evaluating risk factors, progression, and outcomes of atherosclerosis in 15,792 participants (45% male, 74% white) enrolled in four US communities in 1987–1989. The ARIC study protocol and design have been previously described [6]. We excluded ARIC participants with absent or poor-quality ECGs due to noise, artifacts, or missing leads (n = 24), atrial fibrillation (AF) (n = 36), and ventricular pacing (n = 16) at the baseline study visit. Only participants in normal sinus rhythm were included in this study (n = 15,716). If AF or ventricular pacing were diagnosed at any time during follow-up, such participants were included for a period until AF or ventricular pacing were diagnosed on 12-lead ECG. Prevalent CVD was defined as the presence of at least one baseline prevalent condition: coronary heart disease (CHD), heart failure (HF), stroke, peripheral artery disease (PAD), atrioventricular (AV) block II-III, atrial or ventricular pacing, or Wolff-Parkinson-White ECG phenotype.
Clinical characteristics of participants
Prevalent CHD was defined as a history of myocardial infarction (MI), or coronary revascularization via coronary artery bypass surgery or percutaneous coronary intervention. Prevalent MI was defined as a self-reported history of MI and/or ECG evidence of MI as defined by the Minnesota code [7]. Prevalent AF was defined as either a self-reported and validated history of AF or a diagnosis of AF on the baseline ECG. Prevalent HF was defined as self-reported use of HF medication or evidence of symptomatic HF as defined by stage 3 of the Gothenburg criteria [8], which required the presence of specific cardiac and pulmonary symptoms in addition to medical treatment of HF. Prevalent stroke in ARIC was defined by a stroke and transient ischemic attack diagnostic algorithm, as previously described [9]. PAD was defined as the ankle-brachial index ≤0.90. Details of ankle-brachial index measurement in the ARIC study have been previously described [10].
Definition of a primary outcome: sudden cardiac death
A follow-up of ARIC participants was previously reported [11]. SCD was defined as a sudden pulseless condition in a previously stable individual without evidence of a non-cardiac cause of cardiac arrest if the cardiac arrest occurred out of the hospital or in the emergency room. To identify cases of SCD in ARIC, cases of fatal CHD that occurred by December 31, 2012 were reviewed and adjudicated by a committee of physicians in two phases, as previously described [12]. CHD deaths occurring on or before December 31, 2001 were adjudicated in the first phase. CHD deaths occurring between January 1, 2002 and December 31, 2012 were adjudicated in the second phase. Available data from death certificates, informant interviews, physician questionnaires, coroner reports, prior medical history, and hospital discharge summaries were reviewed, in addition to circumstances surrounding the event. Each event was adjudicated independently by two physicians. In cases of disagreement, a third reviewer independently reviewed the event to provide final classification. Definite, probable, or possible SCD was included in this study as a primary outcome: the strength of available evidence determined this stratification. Definite SCD included cases of witnessed SCD with definite evidence such as an available rhythm strip of life-threatening cardiac arrhythmia, or primary emergency medical services impression of cardiac arrest. Probable SCD was defined as SCD with uncertainty either due to concomitant clinical conditions that can muddle the exact cause of demise, or limited information to adjudicate an event. Possible SCDs were adjudicated only in the second phase of reviews. The strength of evidence for probable SCD was greater than the strength of evidence for possible SCD. Possible SCD included cases of death that were unwitnessed but had specified SCD on a death certificate and did not document another cause of death. Participants were censored at the time of loss to follow-up, incident AF or ventricular pacing on 12-lead ECG, or death if the cause of death was any other than SCD.
Competing mortality outcome: non-sudden cardiac death
Cases of fatal CHD were adjudicated by the ARIC Morbidity and Mortality Classification Committee, as previously described [11]. Fatal CHD that did not meet the criteria of SCD comprised the non-SCD outcome.
12 lead ECG recording
12-lead ECG was recorded according to the ARIC study protocol and manual (version 1.0; August 1987). The method and procedure for 12-lead ECG recording, as described in the ARIC manual, are outlined below. During the baseline examination, a standard supine 12-lead ECG was recorded after a 12-h fast followed by a light snack and at least 1 h after smoking or ingestion of caffeine. The standard electrocardiograph for the ARIC study was the MAC PC by Marquette Electronics, Inc. A 12-lead resting ECG was obtained consisting of 10 s of each of the leads (I, II, III, aVR, aVL, aVF, Vl-V6) simultaneously recorded. In an effort to enable longitudinal comparisons of ECGs, ARIC investigators developed and implemented a uniform procedure for electrode placement and skin preparation. The participant, stripped to the waist, was instructed to lie on the recording bed with arms relaxed at the sides. The individual was asked to avoid movements that may cause errors in marking the electrode locations. For optimal electrode/skin interface, the electrodes were placed on the skin at least 2–3 min before recording the ECG. A pen was used to mark the six chest electrode positions. The chest was wiped with a sterile alcohol prep. Left leg electrode was placed on the medial surface of the left ankle. Right leg electrode was placed on the medial surface of the right ankle. Left arm electrode was placed on the medial surface of the left wrist. Right arm electrode was placed on the medial surface of the right wrist. Electrode V1 was located in the 4th intercostal space at the right sternal border, immediately to the right of the sternum. Electrode V2 was located in the 4th intercostal space, immediately to the left of the sternal border. Next, E-point was located by finding the 5th intercostal space, and following it horizontally to the midsternal line. Location of V6 electrode was found using the chest square. V6 was located at the same level as the E point in the midaxillary line (straight down from the center of the armpit). If breast tissue was over the V6 area, V6 was placed on top of the breast. No attempt was made to move the breast. Electrode V4 was located using a flexible ruler, as a midway between E and V6. Electrode V3 was located using a flexible ruler, midway between V2 and V4. Using a flexible ruler, electrode V5 was located midway between the locations of V4 and V6. After placing the electrodes on the skin, the participant’s information was input to the MAC PC. It was required that electrodes must be on the skin for at least 3 min before taking the ECG. During the ECG recording, special attention was paid to the quality of recording. Quality control and technical troubleshooting procedures were in place to minimize errors (lead switch), noise, and artifacts. Recorded 12-lead ECGs were originally saved in the memory of the ECG machine and transmitted to a MUSE database (GE Marquette, Milwaukee, WI) within the Halifax ECG Computing Center via the phone line. Later, the MUSE database was transferred from the Halifax ECG Computing Center to the Epidemiological Cardiology Research Center (EPICARE, Wake Forest University, NC), and then to the Tereshchenko laboratory at Oregon Health & Science University.
Electrocardiogram analyses
ECG data from all five follow-up visits were analyzed. Traditional ECG intervals were reported by the 12 SL algorithm using Magellan ECG Research Workstation V2 (GE Marquette Electronics, Milwaukee, WI). QT interval was corrected for heart rate according to Bazett’s formula. We analyzed raw, digital, 10-s, 12-lead ECGs (sampling rate of 500 Hz and amplitude resolution of 1 μV). Origin and conduction path of each cardiac beat was adjudicated by the team of physicians (DG, AB, SVM, LGT), and each beat was manually labeled by investigators (CH, JAT) for subsequent automated analyses. A representative normal sinus median beat was constructed. For the development of a normal sinus median beat, sinus beats before and after premature ventricular complexes, and noisy or distorted beats were excluded. In this study, only the normal sinus median beat was used for our analysis. GEH was measured as previously described, [4, 13] in a time-coherent median beat with the identified origin of the heart vector [14]. We have provided the open-source software code at Physionet (https://physionet.org/physiotools/geh/). In addition to previously reported “mean” GEH measures, [4] in this study we measured the spatial peak vectors (Fig. 1) [13,14,15]. First, we transformed the 12-lead ECG into an orthogonal XYZ ECG, using Kors transformation [16]. Next, we constructed a time-coherent median beat, and detected the origin of the heart vector using our novel approach, as recently described [14]. Then, we performed calculations of GEH metrics using the following equations.
Spatial QRS-T angles
Spatial peak QRS-T angle was calculated as the 3-dimensional angle between the spatial peak QRS vector and the spatial peak T vector:
$$ Spatial\ peak\ QRS-T\ angle=\operatorname{arccos}\left(\frac{\overrightarrow{QRSpeak}\bullet \overrightarrow{Tpeak}}{\left| QRSpeak\right|\left| Tpeak\right|}\right) $$
(A.1)
Spatial area QRS-T angle was calculated as the 3-dimensional angle between the spatial area QRS vector and the spatial area T vector:
$$ Spatial\ area\ QRS-T\ angle=\operatorname{arccos}\left(\frac{\overrightarrow{QRSm} ean\bullet \overrightarrow{Tmean}}{\left| QRSmean\right|\left| Tmean\right|}\right) $$
(A.2)
Spatial ventricular gradient vectors:
Magnitude and direction of spatial area (Wilson’s) and peak SVG vectors were measured.
$$ \overrightarrow{SVG}V=\overrightarrow{QRSpeak}+\overrightarrow{Tpeak} $$
(A.3)
$$ Spatial\ Peak\ SVG\ Azimuth=\arctan \left(\frac{SVGV_Z\ dt}{SVGV_X\ dt}\right)\kern2em $$
(A.4)
$$ Spatial\ Peak\ SVG\ Elevation=\arctan \left(\frac{SVGV_X\ dt}{SVGV_Y\ dt}\right) $$
(A.5)
$$ SpatialPeakSVGMagnitude=\sqrt{SVG{V_X}^2+ SVG{V_Y}^2+ SVG{V_Z}^2} $$
(A.6)
$$ Spatial\ Area\ SVG\ Azimuth=\arctan \left(\frac{\int_{QRS- onset}^{T- offset}{V}_Z(t) dt}{\int_{QRS- onset}^{T- offset}{V}_X(t) dt}\right)\kern2em $$
(A.7)
$$ Spatial\ Area\ SVG\ Elevation=\arctan \left(\frac{\int_{QRS- onset}^{T- offset}{V}_X(t) dt}{\int_{QRS- onset}^{T- offset}{V}_Y(t) dt}\right) $$
(A.8)
Wilson’s (area) SVG magnitude was also calculated:
$$ \left| SVG\right|=\sqrt{{\left({\int}_{QBeg}^{TEnd}{V}_x(t) dt\right)}^2+{\left({\int}_{QBeg}^{TEnd}{V}_y(t) dt\right)}^2+{\left({\int}_{QBeg}^{TEnd}{V}_z(t) dt\right)}^2} $$
(A.9)
Statistical analysis
Time-dependent area under the receiver operating characteristic curve (ROC(t)AUC) analysis was performed to assess the predictive accuracy of a continuous biomarker in a period of 3, 6, 9 months, and 1,2,3,5,10, and 15 years, using an unadjusted survival analysis framework approach [17, 18]. We used the nearest neighbor estimator, which allows the censoring to depend on the marker and is therefore realistic. The percentage of observations included in each neighborhood was defined by the eq. 0.25* \( \Big(\sqrt[3]{n} \)), where n is the number of observations. All available five visits’ ECG data were included in time-dependent AUC analysis [4]. To satisfy the requirement for ROC analysis, and to perform internal validation of study findings, we divided the dataset into five unique (non-overlapping) partitions. In each partition, a study participant was presented not more than once, with a unique time to event defined as time from ECG recording to the time of outcome (or censoring). If a participant had five ECGs recorded at five study visits, each ECG contributed to a different partition. Those participants who had less than 5 visits/ECGs were randomly distributed across 5 partitions. Bootstrapping with 500 replications was performed to determine a 95% confidence interval (CI) of ROC(t) AUC in each partition, separately. Then, ROC(t) AUC point estimates, and lower and upper boundaries of 95%CI were averaged across 5 partitions, then presented as a final summary result. To assess the statistical power of ROC(t) AUC analysis at each time period, we compared observed 95% CI width with expected 95% CI width. Expected 95% CI width was calculated for observed sample size and observed AUC values at each time period. We summarized clinical characteristics of study participants with an SCD outcome within the first 3 months, 3–6 months, 6 months-1 year, 1–2 years, 2–5 years, and more than 5 years after ECG recording in a longitudinal dataset, reporting between-participant standard deviation (SD) for continuous variables, and between-participant frequencies for categorical variables. We then assessed whether the addition of traditional ECG metrics (heart rate, QRS, QTc) and GEH metrics to our previously identified clinical risk factors of SCD [4] (age, sex, race, diabetes, hypertension, CHD, and stroke) resulted in better predictive accuracy for SCD and non-SCD within the first 3 months, 3–6 months, 6 months-1 year, 1–2 years, 2–5 years, and more than 5 years after ECG recording. We calculated absolute integrated discrimination improvement (IDI), and net reclassification improvement (NRI) using multivariate logistic regression [19, 20]. IDI estimates improvement in average sensitivity and specificity. We estimated category-free NRI and two-category NRI for events, defining the high-risk category as a ≥ 25% risk of SCD/non-SCD within the first 3 months, 3–6 months, and 6 months-1 year after ECG recording. The high-risk category for events occurring 1–2 years, 2–5 years, and more than 5 years after ECG recording was defined as ≥10% risk of SCD/non-SCD. Statistical analysis was performed using STATA MP 15.1 (StataCorp LP, College Station, TX, USA). A P-value of < 0.05 was considered significant. PASS 2019 Power Analysis and Sample Size Software (NCSS, LLC. Kaysville, Utah, USA) was used for the calculations of the expected 95% CI width.
