Researchers have developed a potentially useful list of predictors of atherosclerotic sudden cardiac death (SCD) to help clinicians distinguish patients who are likely to die of a heart attack from those who might survive one. Their ultimate goal is to create a risk stratification score applicable for the general population and provide interventions to prevent development of traits that contribute to SCD.
Elsayed Z. Soliman, MD, director of the Epidemiological Cardiology Research Center at Wake Forest Baptist Medical Center in Winston-Salem, N.C., and colleagues analyzed data from two large cohort studies to tease apart risk factors for SCD and the incidence rates of coronary heart disease (CHD). Their findings were published online July 20 in Heart.
Soliman et al identified clinical and electrocardiographic predictors, including hypertension, race/ethnicity, body mass index (BMI), heart rate, QTc, an abnormally inverted T-wave in any electrocardiogram (ECG) lead group and level of ST-elevation as potentially useful factors for separating SCD risk from CHD risk. They added that the results need to be validated in another cohort.
“This is an exploratory study,” Soliman told Cardiovascular Business, “to see if we can find predictors that can separate [SCD and CHD]. We came up with a list of [risk] factors that are potentially useful.”
SCD and CHD share many risk factors, making identification of SCD risk factors alone a challenge. “Most of the previous studies on predictors of SCD have ignored the competitive risk of CHD, which does not provide meaningful risk stratification of patients if definitive preventive strategies are to be implemented,” the authors noted.
The researchers overcame this hurdle by using the ARIC (Atherosclerosis Risk in Communities) study and the CHS (Cardiovascular Health Study) to obtain sufficient data to perform their investigation. The analysis included 18,497 participants from the two studies (58 percent female, 24 percent black, with a mean age of 58).
The study differed from previous research because they went beyond the definition of SCD by scouring the data to ascertain sudden death. “We needed to do some detective work,” Soliman said.
They looked at family history, medical history, circumstances of the death, timing and other factors. Two members of the research team had to concur that it was a case of SCD to be included in the study. They identified 229 definite SCD events and 2,297 CHD events.
The investigators then conducted a competing risk analysis (median follow-up time of 14 years in ARIC and 13 years in CHS) to identify ECG and clinical factors that were predictive of SCD or CHD.
The analysis included identification and selection of demographic and clinical characteristics associated with risk in both groups; an assessment of the effect of ECG variables on those risks; an analysis to determine if ECG risk predictors in each group differed; and assessments of ECG variables and clinical and demographic co-variables.
Soliman and colleagues found that hypertension and BMI, as well as being African American, were predictive of high SCD risk, although the SCD risk decreased as BMI increased from 20 to 29 and then SCD risk increased again at 29. Strong ECG predictors for SCD included increased heart rate, prolongation of QTc, the presence of an abnormally inverted T-wave in any ECG lead group and St. Jude Medical’s amplitude in leads V2, V3, II and VF.
“Including participants with prevalent CHD at baseline in the cohort showed that the greatest risk for SCD was a prior CHD event,” the authors wrote. “The risk of SCD was approximately four times higher for those with prevalent CHD compared with no evidence of CHD, adjusted for age, race/ethnicity and sex.”
The authors acknowledged that some findings may result from chance because they did not adjust for multiple comparisons in the statistical analyses. They also recognized data limitations, including the lack of more recent ECG predictors of SCD.
The researchers plan to expand their study to include other factors that may contribute to SCD. “There are other modalities of investigation that could add more variables,” said Soliman, who used genetics as an example.
“There is a lot still to be done,” he concluded. “This is groundwork for future research.”