title: ST-T wave abnormality in lead aVR and reclassification of cardiovascular risk (from the National Health and Nutrition Examination Survey-III).
abstract: Electrocardiographic lead aVR is often ignored in clinical practice. The aim of this study was to investigate whether ST-T wave amplitude in lead aVR predicts cardiovascular (CV) mortality and if this variable adds value to a traditional risk prediction model. A total of 7,928 participants enrolled in the National Health and Nutrition Examination Survey (NHANES) III with electrocardiographic data available were included. Each participant had 13.5 ± 3.8 years of follow-up. The study sample was stratified according to ST-segment amplitude and T-wave amplitude in lead aVR. ST-segment elevation (>8 μV) in lead aVR was predictive of CV mortality in the multivariate analysis when not accounting for T-wave amplitude. The finding lost significance after including T-wave amplitude in the model. A positive T wave in lead aVR (>0 mV) was the strongest multivariate predictor of CV mortality (hazard ratio 3.37, p <0.01). The addition of T-wave amplitude in lead aVR to the Framingham risk score led to a net reclassification improvement of 2.7% of subjects with CV events and 2.3% of subjects with no events (p <0.01). Furthermore, in the intermediate-risk category, 20.0% of the subjects in the CV event group and 9.1% of subjects in the no-event group were appropriately reclassified. The absolute integrated discrimination improvement was 0.012 (p <0.01), and the relative integrated discrimination improvement was 11%. In conclusion, T-wave amplitude in lead aVR independently predicts CV mortality in a cross-sectional United States population. Adding T-wave abnormalities in lead aVR to the Framingham risk score improves model discrimination and calibration with better reclassification of intermediate-risk subjects.
authors.affiliation: Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA. apurva_badheka@yahoo.com
authors.forename: Apurva O
authors.initials: AO
authors.lastname: Badheka
authors.forename: Nileshkumar J
authors.initials: NJ
authors.lastname: Patel
authors.forename: Peeyush M
authors.initials: PM
authors.lastname: Grover
authors.forename: Neeraj
authors.initials: N
authors.lastname: Shah
authors.forename: Vikas
authors.initials: V
authors.lastname: Singh
authors.forename: Abhishek
authors.initials: A
authors.lastname: Deshmukh
authors.forename: Kathan
authors.initials: K
authors.lastname: Mehta
authors.forename: Ankit
authors.initials: A
authors.lastname: Chothani
authors.forename: Michael
authors.initials: M
authors.lastname: Hoosien
authors.forename: Ankit
authors.initials: A
authors.lastname: Rathod
authors.forename: Ghanshyambhai T
authors.initials: GT
authors.lastname: Savani
authors.forename: George R
authors.initials: GR
authors.lastname: Marzouka
authors.forename: Sandeep
authors.initials: S
authors.lastname: Gupta
authors.forename: Raul D
authors.initials: RD
authors.lastname: Mitrani
authors.forename: Mauro
authors.initials: M
authors.lastname: Moscucci
authors.forename: Mauricio G
authors.initials: MG
authors.lastname: Cohen
mesh_terms: D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000453:epidemiology* / Q000503:physiopathology; D004562:Electrocardiography; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys / Q000379:methods*; D015995:Prevalence; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D015996:Survival Rate / Q000639:trends; D014481:United States / Q000453:epidemiology; D020257:Ventricular Remodeling