Computerized ST depression analysis improves prediction of all-cause and cardiovascular mortality: the strong heart study

P M Okin, R B Devereux, J A Kors, G van Herpen, R S Crow, R R Fabsitz, B V Howard
Annals of Noninvasive Electrocardiology 2001, 6 (2): 107-16

BACKGROUND: Nonspecific ST depression assessed by standard visual Minnesota coding (MC) has been demonstrated to predict risk. Although computer analysis has been applied to digital ECGs for MC, the prognostic value of computerized MC and computerized ST depression analyses have not been examined in relation to standard visual MC.

METHODS: The predictive value of nonspecific ST depression as determined by visual and computerized MC codes 4.2 or 4.3 was compared with computer-measured ST depression >or= 50 microV in 2,127 American Indian participants in the first Strong Heart Study examination. Computerized MC and ST depression were determined using separate computerized-ECG analysis programs and visual MC was performed by an experienced ECG core laboratory.

RESULTS: The prevalence of MC 4.2 or 4.3 by computer was higher than by visual analysis (6.4 vs 4.4%, P < 0.001). After mean follow-up of 3.7 +/- 0.9 years, there were 73 cardiovascular deaths and 227 deaths from all causes. In univariate Cox analyses, visual MC (relative risk [RR] 4.8, 95% confidence interval [CI] 2.6-9.1), computerized MC (RR 6.0, 95% CI 3.5-10.3), and computer-measured ST depression (RR 7.6, 95% CI 4.5-12.9) were all significant predictors of cardiovascular death. In separate multivariate Cox regression analyses that included age, sex, diabetes, HDL and LDL cholesterol, body mass index, systolic and diastolic blood pressure, microalbuminuria, smoking, and the presence of coronary heart disease, computerized MC (RR 3.0, 95% CI 1.6-5.6) and computer-measured ST depression (RR 3.1, 95% CI 1.7-5.7), but not visual MC, remained significant predictors of cardiovascular mortality. When both computerized MC and computer-measured ST depression were entered into the multivariate Cox regression, each variable provided independent risk stratification (RR 2.1, 95% CI 1.0-4.4, and RR 2.1, 95% CI 1.0-4.4, respectively). Similarly, computerized MC and computer-measured ST depression, but not visual MC, were independent predictors of all-cause mortality after controlling for standard risk factors.

CONCLUSIONS: Computer analysis of the ECG, using computerized MC and computer-measured ST depression, provides independent and additive risk stratification for cardiovascular and all-cause mortality, and improves risk stratification compared with visual MC. These findings support the use of routine computer analysis of ST depression on the rest ECG for assessment of risk and suggest that computerized MC can replace visual MC for this purpose.

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