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In a prospective study on Coronary Heart Disease (CHD) orthogonal electrocardiograms (Frank) were recorded annually for ten years from 1,444 asymptomatic, middle-aged males with a mean age of 57.4 +/- 10.6 years. Cases with overt or suspected CHD were excluded. The purpose of the study was to identify risk indicators in electrocardiograms and to compare them with other known risk factors used for prediction of acute CHD events such as myocardial infarction (MI) and/or cardiac death (CD). Such acute events occurred in 88 cases. Pre-event ECGs of these acute events were compared with all others without events, using logistic regression analysis. Identified ECG risk indicators were then compared with other known risk factors such as smoking, blood pressure, cholesterol, age, weight, etc. The predictive power of the ECG, derived mainly from the ST-T complex, exceeded all others by a wide margin. The amplitude of the first 1/8 of the ST-T complex in lead x (similar to V5-V6) together with relative body weight proved best when one pre-event record was available. Prediction improved when ECG changes between two pre-event recordings were included. Precision of measurements by computer appeared essential for improvements in CHD prediction.

Correlations between 276 orthogonal electrocardiographic measurements and constitutional variables were made in 450 normal women, aged 18 to 90 years. Advancing age led to decreases in amplitudes, left QRS axis shift, rightward and superior displacement of the ST segment, and anterior shift of the T wave. QZ was absent in 1% of normal women over age 40. In the oldest subjects, Ry amplitude was 71% and RZ amplitude was 80% of the respective values in the youngest group. Whereas QRS amplitude decreases with age leveled off at the sixth decade of life, they continued to old age for ST-T measurements. Men revealed steeper age trends than women. Blacks had larger QRS amplitudes and smaller Q/R ratios than whites. Stratification of electrocardiographic criteria according to age, sex, and race appears essential for routine interpretations and for epidemiological studies where new events, such as myocardial infarcts, need to be differentiated from normal age trends.

When assessing patients' serial ECG changes, the clinician implicitly compares those changes to the limits of change expected in a healthy population. Prospective epidemiological studies, too, develop their criteria from the limits of normal serial ECG changes. Surprisingly then, few studies have reported normal limits for changes between serial ECGs taken six months or longer apart, and all are based on small samples. The present study has a large sample size: 243 white middle-aged and older males, after exclusions for heart disease. Each had at least four consecutive annual examinations with ECGs. Limits of serial variability were computed for 52 measurements. The ECG measurements included durations, amplitudes, ratios, angles and spatial magnitudes. Clinical measurements included blood pressure, cholesterol relative weight and hemoglobin. Year-to-year ECG variabilities were compared to day-to-day variabilities of the same measurements reported earlier. Year-to-year variation was virtually identical to the reported day-to-day variation in most measurements. In only two measurements was year-to-year variation over 25% greater than the reported day-to-day variation.