Looking for prognostic information in the ST-T segment--is it really worth it?
Peter W Macfarlane1, John Norrie,
1Section of Cardiology and Exercise Medicine, Royal Infirmary, Glasgow, United Kingdom. peter.w.macfarlane@clinmed.gla.ac.uk
Insights
Electrocardiogram (ECG) findings like heart rate and T axis offer limited prognostic value for myocardial infarction risk when considering clinical data. Age and smoking history alone provide comparable predictive power to ECG combined with age.
Area of Science:
- Cardiology
- Preventive Medicine
- Medical Informatics
Background:
- The West of Scotland Coronary Prevention Study (WOSCOPS) involved 6,595 men without prior myocardial infarction.
- Participants were followed for a mean of 4.9 years, with half receiving lipid-lowering drugs and the other half a placebo.
- Baseline electrocardiograms (ECGs) were collected, offering an opportunity to assess ECG morphology as a risk marker.
Purpose of the Study:
- To evaluate the prognostic value of electrocardiographic (ECG) morphology in predicting myocardial infarction.
- To identify specific ECG parameters and clinical factors that predict fatal or non-fatal myocardial infarction.
- To develop a risk score based on significant ECG and clinical predictors.
Main Methods:
- Utilized 12-lead ECGs from the WOSCOPS cohort, processed using the Glasgow Program and automated Minnesota Coding.
- Performed univariate and multivariate logistic regression analyses to identify predictive electrocardiographic and clinical parameters.
- Focused on ST-T variables and QT dispersion, and developed a risk score incorporating significant predictors.
Main Results:
- While many ECG measures showed univariate prognostic value, only heart rate, frontal T axis, and T+ amplitude in lead I remained significant in multivariate analysis including clinical data.
- QT dispersion exceeding 44 ms was associated with increased risk (RR 1.38), but its predictive curve was poor.
- Age and smoking history alone demonstrated prognostic value comparable to ECG measures combined with age.
Conclusions:
- Electrocardiogram variables have limited independent prognostic value for myocardial infarction when considered alongside clinical data.
- Clinical factors such as age and smoking history are strong predictors of cardiovascular events.
- The prognostic utility of ECG findings must be carefully evaluated in the context of other available patient information.
Abstract:
The West of Scotland Coronary Prevention Study (WOSCOPS) provided baseline electrocardiograms (ECGs) on 6,595 men without a previous myocardial infarction who were followed for a mean of 4.9 years during which time all events, cardiovascular or otherwise, were recorded. Half of the study group was treated with a lipid lowering drug while the other half was randomly assigned to placebo. This study cohort afforded the opportunity to look at ECG morphology as a marker of risk. All 12-lead ECGs in the study were processed by the Glasgow Program and automated Minnesota Coding was also undertaken. All computer outputs were reviewed to exclude errors due to technically unsatisfactory recordings. Multiple variables were studied. Univariate and multivariate logistic regression analyses were undertaken to determine those electrocardiographic and clinical parameters of predictive value with respect to the primary endpoint of fatal or non fatal myocardial infarction. Those ST-T variables with additional prognostic value in the multivariate analysis, which included the clinical parameters, were used to develop a risk score. Although many ECG measures were of prognostic value in a univariate analysis, only rate, frontal T axis and T+ amplitude in lead I were of significance in a multivariate analysis which included clinical data. With respect to QT dispersion, while it was shown that there was an increased risk for those with QT dispersion exceeding 44 ms (RR 1.38, CI 1.02 - 1.81 P = 0.034) the receiver operating characteristic curve was virtually a straight line. The risk equation also demonstrated that there was as much prognostic value in the use of age and smoking history alone as there was in ECG plus age combined. The conclusion drawn is that the prognostic value of ECG variables has to be considered carefully in the light of other available data.
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