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Dynamic predictive accuracy of electrocardiographic biomarkers of sudden cardiac death within a survival framework: the Atherosclerosis Risk in Communities (ARIC) study.

TitleDynamic predictive accuracy of electrocardiographic biomarkers of sudden cardiac death within a survival framework: the Atherosclerosis Risk in Communities (ARIC) study.
Publication TypeJournal Article
Year of Publication2019
AuthorsPerez-Alday EA, Bender A, German D, Mukundan SV, Hamilton C, Thomas JA, Li-Pershing Y
Secondary AuthorsTereshchenko LG
JournalBMC Cardiovasc Disord
Volume19
Issue1
Pagination255
Date Published2019 11 14
ISSN1471-2261
KeywordsArrhythmias, Cardiac, Death, Sudden, Cardiac, Electrocardiography, Female, Heart Conduction System, Heart Rate, Humans, Incidence, Male, Middle Aged, Predictive Value of Tests, Prognosis, Prospective Studies, Risk Assessment, Risk Factors, Time Factors, United States
Abstract

BACKGROUND: The risk of sudden cardiac death (SCD) is known to be dynamic. However, the accuracy of a dynamic SCD prediction is unknown. We aimed to measure the dynamic predictive accuracy of ECG biomarkers of SCD and competing non-sudden cardiac death (non-SCD).

METHODS: Atherosclerosis Risk In Community study participants with analyzable ECGs in sinus rhythm were included (n = 15,716; 55% female, 73% white, age 54.2 ± 5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity and traditional ECG metrics (heart rate, QRS, QTc) were measured. Adjudicated SCD was the primary outcome; non-SCD was the competing outcome. Time-dependent area under the receiver operating characteristic curve (ROC(t) AUC) analysis was performed to assess the prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years using a survival analysis framework. Reclassification improvement as compared to clinical risk factors (age, sex, race, diabetes, hypertension, coronary heart disease, stroke) was measured.

RESULTS: Over a median 24.4 y follow-up, there were 577 SCDs (incidence 1.76 (95%CI 1.63-1.91)/1000 person-years), and 829 non-SCDs [2.55 (95%CI 2.37-2.71)]. No ECG biomarkers predicted SCD within 3 months after ECG recording. Within 6 months, spatial ventricular gradient (SVG) elevation predicted SCD (AUC 0.706; 95%CI 0.526-0.886), but not a non-SCD (AUC 0.527; 95%CI 0.303-0.75). SVG elevation more accurately predicted SCD if the ECG was recorded 6 months before SCD (AUC 0.706; 95%CI 0.526-0.886) than 2 years before SCD (AUC 0.608; 95%CI 0.515-0.701). Within the first 3 months after ECG recording, only SVG azimuth improved reclassification of the risk beyond clinical risk factors: 18% of SCD events were reclassified from low or intermediate risk to a high-risk category. QRS-T angle was the strongest long-term predictor of SCD (AUC 0.710; 95%CI 0.668-0.753 for ECG recorded within 10 years before SCD).

CONCLUSION: Short-term and long-term predictive accuracy of ECG biomarkers of SCD differed, reflecting differences in transient vs. persistent SCD substrates. The dynamic predictive accuracy of ECG biomarkers should be considered for competing SCD risk scores. The distinction between markers predicting short-term and long-term events may represent the difference between markers heralding SCD (triggers or transient substrates) versus markers identifying persistent substrate.

DOI10.1186/s12872-019-1234-9
Alternate JournalBMC Cardiovasc Disord
PubMed ID31726979
PubMed Central IDPMC6854807
Grant ListR01 HL118277 / HL / NHLBI NIH HHS / United States
R56 HL118277 / HL / NHLBI NIH HHS / United States
HHSN268201700001I / HL / NHLBI NIH HHS / United States
HHSN268201700002I / HL / NHLBI NIH HHS / United States
HHSN268201700003I / HL / NHLBI NIH HHS / United States
HHSN268201700004I / HL / NHLBI NIH HHS / United States
HHSN268201700005I / HL / NHLBI NIH HHS / United States