Researchers have developed a risk score based on demographics and automated electrocardiography (ECG) data that performs comparably to the Framingham risk score and the pooled cohort equation when assessing possible cardiovascular disease mortality.

When they added the ECG risk equation to either of the other two scores, they found a significant improvement in clinical risk classification.

Lead researcher Amit J. Shah, MD, of Emory University in Atlanta, and colleagues published their findings online in JAMA Cardiology on Aug. 3.

Although some evidence has supported the use of ECG to assess cardiovascular disease risk, the researchers noted that an ECG is not typically used in routine cardiovascular disease risk assessment or screening.

For this study, they created an ECG-based risk equation based on individuals who did not have cardiovascular disease and enrolled in the first and third NHANES (National Health and Nutrition Examination Surveys I and III). They derived the equation from using vector and interval ECG data; heart rate; frontal P, QRS and T axes; frontal QRS-T angle; and PR, QRS and QT intervals and durations.

They developed the ECG risk equation by examining the variables that were most associated with cardiovascular disease events in 3,640 participants who were 40 to 74 years old when they enrolled in NHANES I, which collected baseline data from 1971 to 1975. They then tested the equation in a cohort of participants who enrolled in NHANES III, which collected baseline data from 1988 to 1994. For the NHANES III cohort, they included 6,329 participants who were 40 70 74 years old, had good-quality ECGS, had not self-reported a history of MI, stroke or heart failure and had complete data on mortality, medical history, medication use and anthropometric measurements.

Of the 9,969 participants in both groups, 47.3 percent were men, and the mean age was 55.3 years old.

The following ECG variables were independently associated with major adverse cardiovascular events: frontal T axis, QT interval (corrected for heart rate) and heart rate.

In the NHANES I cohort, the ECG risk factors were significantly associated with major adverse cardiovascular events and cardiovascular disease death even after adjusting for risk factors such as tobacco abuse, systolic blood pressure, diabetes and total cholesterol.

When the researchers added the ECG risk equation to the Framingham risk score, the C statistic for fatal cardiovascular disease improved from 0.76 to 0.80. When they added the ECG risk equation to the American College of Cardiology-American Heart Association pooled cohort equation, the C statistic for fatal cardiovascular disease also increased from 0.76 to 0.80.

The study had a few potential limitations, according to the researchers, including that they based the causes of death in the NHANES III cohort on death certificate data, which may have led them to incorrectly classify some of the deaths. They also could not evaluate an association with nonfatal cardiovascular disease in the validation cohort because there was no data available.

In addition, they derived vector and interval data from techniques used more than 20 years ago. Further, they noted that medical history and smoking history could have been subject to recall bias. They also mentioned that clinical use of the ECG score could be limited to only settings where computerized ECG machines are available.

“We have developed and validated a simple ECG risk equation based on vector and interval measures associated with [cardiovascular disease] independently of the [Framingham risk score],” the researchers wrote. “Further testing is needed to evaluate how clinical outcomes and costs may be affected by incorporating this equation into primary prevention efforts.”