Dynamic Predictive Accuracy of Electrocardiographic Biomarkers of Sudden Cardiac Death within a Survival Framework: The Atherosclerosis Risk in Communities (ARIC) study
| Autor: | Srini V. Mukundan, David M. German, Jason Thomas, Yin Li-Pershing, Christopher Hamilton, Aron Bender, Erick A. Perez-Alday, Larisa G. Tereshchenko |
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| Rok vydání: | 2019 |
| Předmět: |
Male
medicine.medical_specialty lcsh:Diseases of the circulatory (Cardiovascular) system congenital hereditary and neonatal diseases and abnormalities Time Factors Vectorcardiography 030204 cardiovascular system & hematology QT interval Risk Assessment Sudden cardiac death 03 medical and health sciences QRS complex Electrocardiography 0302 clinical medicine Heart Conduction System Heart Rate Predictive Value of Tests Risk Factors Internal medicine hemic and lymphatic diseases Medicine Humans Sinus rhythm 030212 general & internal medicine Global electrical heterogeneity Prospective Studies cardiovascular diseases Survival analysis Angiology Receiver operating characteristic medicine.diagnostic_test business.industry Incidence Arrhythmias Cardiac Middle Aged medicine.disease Prognosis United States Death Sudden Cardiac lcsh:RC666-701 Cardiology Female Dynamic prediction Cardiology and Cardiovascular Medicine business Research Article |
| Zdroj: | BMC Cardiovascular Disorders BMC Cardiovascular Disorders, Vol 19, Iss 1, Pp 1-19 (2019) |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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