title: The association of spatial T wave axis deviation with incident coronary events. The ARIC cohort.
abstract: BACKGROUND
  Although current evidence suggests that the spatial T wave axis captures important information about ventricular repolarization abnormalities, there are only a few and discordant epidemiologic studies addressing the ability of the spatial T wave axis to predict coronary heart disease (CHD) occurrence.
  
  
  METHODS
  This prospective study analyzed data from 12,256 middle-aged African American and white men and women, from the Atherosclerosis Risk in Communities Study (ARIC). Following a standardized protocol, resting standard 12-lead, 10-second electrocardiograms were digitized and analyzed with the Marquette GE program. The median follow-up time was 12.1 years; incident coronary heart disease comprised fatal and non-fatal CHD events.
  
  
  RESULTS
  The incidence rate of CHD was 4.26, 4.18, 4.28 and 5.62 per 1000 person-years respectively, across the spatial T wave axis quartiles. Among women for every 10 degrees increase in the spatial T wave axis deviation, there was an estimated increase in the risk of CHD of 1.16 (95% CI 1.04-1.28). After adjustment for age, height, weight, smoking, hypertension, diabetes, QRS axis and minor T wave abnormalities, this hazard rate ratio for women fell to 1.03 (0.92-1.14). The corresponding crude and adjusted hazard ratios for men were 1.05 (95% CI 0.96-1.15) and 0.95 (0.86-1.04) respectively.
  
  
  CONCLUSIONS
  In conclusion, this prospective, population-based, bi-ethnic study of men and women free of coronary heart disease at baseline shows that spatial T wave axis deviation is not associated with incident coronary events during long-term follow up. It is doubtful that spatial T wave axis deviation would add benefit in the prediction of CHD events above and beyond the current traditional risk factors.
authors.affiliation: Department of Epidemiology, University of North Carolina at Chapel Hill, USA. vaidean@email.unc.edu
authors.forename: Georgeta D
authors.initials: GD
authors.lastname: Vaidean
authors.forename: Pentti M
authors.initials: PM
authors.lastname: Rautaharju
authors.forename: Ronald J
authors.initials: RJ
authors.lastname: Prineas
authors.forename: Eric A
authors.initials: EA
authors.lastname: Whitsel
authors.forename: Lloyd E
authors.initials: LE
authors.lastname: Chambless
authors.forename: Aaron R
authors.initials: AR
authors.lastname: Folsom
authors.forename: Wayne D
authors.initials: WD
authors.lastname: Rosamond
authors.forename: Zhu-Ming
authors.initials: ZM
authors.lastname: Zhang
authors.forename: Richard S
authors.initials: RS
authors.lastname: Crow
authors.forename: Gerardo
authors.initials: G
authors.lastname: Heiss
mesh_terms: D001741:Black or African American; D015331:Cohort Studies; D003327:Coronary Disease / Q000175:diagnosis / Q000453:epidemiology*; D004562:Electrocardiography; D005260:Female; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D015994:Incidence; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011446:Prospective Studies; D044465:White People