High-risk electrocardiographic parameters are ubiquitous in patients with ischemic cardiomyopathy
Mary G Carey1, Salah S Al-Zaiti, John M Canty
1School of Nursing, University at Buffalo, Buffalo, NY 14214, USA.
Insights
Electrocardiogram (ECG) risk parameters are often unassessable in ischemic cardiomyopathy patients. However, abnormal ECG findings are common, indicating widespread cardiovascular risk in this population.
Area of Science:
- Cardiology
- Medical Diagnostics
- Biomedical Engineering
Background:
- Electrocardiogram (ECG) is used for cardiovascular risk prediction.
- Low predictive accuracy in low-risk populations is a challenge.
- Higher risk populations may improve accuracy but affect parameter prevalence and exclusions.
Purpose of the Study:
- To assess high-risk ECG parameters in ischemic cardiomyopathy.
- To determine the impact of exclusions on ECG parameter assessment.
- To evaluate the prevalence of abnormal ECG parameters in a high-risk cohort.
Main Methods:
- Analyzed 15 validated high-risk ECG parameters.
- Used data from the Prediction of Arrhythmic Events with Positron Emission Tomography (PAREPET) study (n=198).
- Applied published exclusion criteria (atrial fibrillation, pacing, prolonged QRS).
Main Results:
- Only 4 (27%) ECG parameters were assessable in all subjects.
- 42% of subjects had all 15 ECG parameters assessed.
- 97% of subjects had at least one abnormal parameter; 34% of assessable parameters were abnormal.
Conclusions:
- A significant proportion of ECG parameters are not assessable in ischemic cardiomyopathy.
- Abnormal high-risk ECG findings are ubiquitous in this population.
- Further analysis is needed to determine the predictive value of these parameters on cause-specific mortality.
Background:
The electrocardiogram (ECG) can be used to predict cardiovascular risk; however, like all risk factors with imperfect specificity, studies in low risk populations have been plagued by poor predictive accuracy. Although predictive accuracy might be improved among cohorts with a higher likelihood of cardiovascular events, this would also affect the prevalence of abnormal parameters and their exclusions.
Method:
To determine the magnitude of these changes in a cohort with ischemic cardiomyopathy we analyzed 15 previously validated high-risk parameters from the resting and ambulatory ECG in subjects enrolled in the Prediction of Arrhythmic Events with Positron Emission Tomography (PAREPET) study (n = 198).
Results:
Using the published exclusion criteria from the validation studies (i.e., atrial fibrillation, persistent pacing, prolonged QRS), only 4 high-risk ECG parameters (27%) could be evaluated in all subjects and only 42% of subjects could have all 15 ECG parameters assessed. Nevertheless, almost every subject (97%) had at least one abnormal parameter. On average, there were 3.4 ± 1.8 (range, 0-8) high-risk ECG parameters per subject among the 11.7 ± 4.5 (range, 4-15) parameters that could be assessed.
Conclusions:
Thus, 34% of all assessable parameters were abnormal. In conclusion, a significant proportion of ECG parameters cannot be assessed in patients with ischemic cardiomyopathy, but high-risk results are ubiquitous. The influence of these issues will be clarified when the results of the PAREPET study are available to actually determine the predictive value of these parameters on cause-specific mortality in a high-risk cohort.
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