Improved detection of echocardiographic left ventricular hypertrophy using a new electrocardiographic algorithm.

OBJECTIVES

The purpose of this study was to use the Framingham data base to devise and test an improvement in an electrocardiographic (ECG) voltage criterion for detecting left ventricular hypertrophy that is gender specific and adjusts for age and obesity.

BACKGROUND

Electrocardiographic detection of left ventricular hypertrophy has been receiving increasing attention. The "Cornell" ECG voltage, defined as the sum of voltages for the R wave of lead aVL and S wave of lead V3, has been shown to correlate strongly with echocardiographically estimated left ventricular mass. Because the magnitude of this voltage varies with both age and obesity, we have proposed a simple formula for its adjustment for these two variables.

METHODS

Using linear regression, the adjustment formula was estimated from data on 1,468 men and 1,883 women from the Framingham Heart Study cohort who were free of myocardial infarction and who had both an ECG and an echocardiogram recorded during the same clinic examination. A modified receiver operating characteristic curve method was used to compare sensitivities at the same specificity levels. The adjustment formula was estimated from one randomly chosen half of the study cohort and applied to the other half for evaluation.

RESULTS

Significant improvement in sensitivity for the detection of left ventricular hypertrophy was realized at all levels of specificity. At a specificity level of 98%, the adjustment increased the sensitivity of the Cornell voltage from 10% to 17% in men and from 12% to 22% in women. For severe hypertrophy, defined as a left ventricular mass > 3 SD above the gender-specific mean, the sensitivity increased from 23% to 38% for men and from 22% to 55% for women at a specificity level of 95%.

CONCLUSIONS

This approach can substantially enhance the utility of the ECG for the detection of left ventricular hypertrophy. If these results are validated in other population groups, this approach may prove valuable in the screening of hypertensive populations and for the monitoring of patients undergoing treatment for hypertension.