Dynamic electrocardiogram changes are a novel risk marker for sudden cardiac death

Abstract

Background and aims: Electrocardiogram (ECG) abnormalities have been evaluated as static risk markers for sudden cardiac death (SCD), but the potential importance of dynamic ECG remodelling has not been investigated. In this study, the nature and prevalence of dynamic ECG remodelling were studied among individuals who eventually suffered SCD.

Methods: The study population was drawn from two prospective community-based SCD studies in Oregon (2002, discovery cohort) and California, USA (2015, validation cohort). For this present sub-study, 231 discovery cases (2015-17) and 203 validation cases (2015-21) with ≥2 archived pre-SCD ECGs were ascertained and were matched to 234 discovery and 203 validation controls based on age, sex, and duration between the ECGs. Dynamic ECG remodelling was measured as progression of a previously validated cumulative six-variable ECG electrical risk score.

Results: Oregon SCD cases displayed greater electrical risk score increase over time vs. controls [+1.06 (95% confidence interval +0.89 to +1.24) vs. -0.05 (-0.21 to +0.11); P < .001]. These findings were successfully replicated in California [+0.87 (+0.7 to +1.04) vs. -0.11 (-0.27 to 0.05); P < .001]. In multivariable models, abnormal dynamic ECG remodelling improved SCD prediction over baseline ECG, demographics, and clinical SCD risk factors in both Oregon [area under the receiver operating characteristic curve 0.770 (95% confidence interval 0.727-0.812) increased to area under the receiver operating characteristic curve 0.869 (95% confidence interval 0.837-0.902)] and California cohorts.

Conclusions: Dynamic ECG remodelling improved SCD risk prediction beyond clinical factors combined with the static ECG, with successful validation in a geographically distinct population. These findings introduce a novel concept of SCD dynamic risk and warrant further detailed investigation.

Keywords: Dynamic; ECG; General population; Risk prediction; Sudden cardiac death.

Structured Graphical Abstract

Summary of the study population, main findings, and future goals. AF, atrial fibrillation; AFL, atrial flutter; AVB, atrioventricular block; ECG, electrocardiogram; LBBB, left bundle branch abnormality; RBBB, right bundle branch abnormality; SCD, sudden cardiac death.

Figure 1

Sudden cardiac death (SCD) case selection. ECG, electrocardiogram.

Figure 2

Utility of dynamic electrocardiogram remodelling beyond baseline electrocardiogram and clinical risk factors. Receiver operating curves for the identification of sudden cardiac death cases in the discovery (Oregon) and validation (California) cohorts with logistic regression models. Clinical variables include diabetes, hypertension, chronic renal insufficiency, chronic obstructive pulmonary disease, sleep apnoea, seizure, syncope, obesity, and coronary artery disease. AUC, area under the receiver operating curve; ERS, electrical risk score.

Figure 3

Electrocardiogram remodelling in sudden cardiac death cases vs. control participants. In Oregon, 231 sudden cardiac death cases were matched to 234 controls by age, sex, and duration between two electrocardiograms. In California, 203 sudden cardiac death cases were matched to 203 controls by age, sex, and duration between two electrocardiograms. The difference in the electrical risk score progression was statistically significant between sudden cardiac death cases and controls in both discovery and validation cohorts. Electrical risk score 1 and electrical risk score 2 refer to electrocardiogram-based electrical risk scores for the oldest and the most recent electrocardiogram, respectively. ECG, electrocardiogram.

Figure 4

Changes in the prevalence of each electrical risk score component in sudden cardiac death cases. LVH, left ventricular hypertrophy; ECG1, the oldest ECG; ECG2, the most recent ECG.

Figure 5

The progression of electrical risk score within 5 years before sudden cardiac death in comparison to matched controls. In Oregon, 80 sudden cardiac death cases were matched with 104 controls by age, sex, and duration between two electrocardiograms. In California, 130 sudden cardiac death cases were matched with 162 controls by age and sex. The duration between two electrocardiograms was slightly longer in California controls than in cases (3.1 ± 1.1 vs. 2.5 ± 1.0 years; P < .001). The difference in the electrical risk score progression was statistically significant between sudden cardiac death cases and controls in both discovery and validation cohorts. The values represent the mean changes in electrical risk score over time (e.g. +0.65 means an increase of 0.65 units in the electrical risk score from the oldest electrocardiogram to the most recent electrocardiogram). ECG1, the oldest ECG; ECG2, the most recent ECG; ERS1 and ERS2, ECG-based electrical risk score for ECG1 for ECG2, respectively.

Figure 6

Mediation analysis of comorbidity effect on sudden cardiac death mediated via electrical risk score. Results are presented as effect sizes for the association of each comorbidity with sudden cardiac death. Effect sizes are estimates of the increase in the probability of sudden cardiac death comparing individuals with and without each comorbidity. hxcad, coronary artery disease; cri, chronic renal insufficiency; copd, chronic obstructive pulmonary disease; ACME, average causal mediation effect (effect of comorbidity on SCD mediated via ERS); ADE, average direct effect (direct effect of comorbidity, not explained by ERS); Total effect, =ACME + ADE (the overall effect of comorbidity on SCD).