Improvement of automated electrocardiographic diagnosis by combination of computer interpretations of the electrocardiogram and vectorcardiogram
- PMID: 1615877
- DOI: 10.1016/0002-9149(92)91397-m
Improvement of automated electrocardiographic diagnosis by combination of computer interpretations of the electrocardiogram and vectorcardiogram
Abstract
In the international project "Common Standards for Quantitative Electrocardiography" (CSE), diagnostic results of different computer programs for the interpretation of the electrocardiogram (ECG) and of the vectorcardiogram (VCG) were combined, and it was shown that the "combined program" performs better than each program separately. Because the program MEANS (Modular ECG Analysis System) comprises 2 different classification programs--one for the ECG, the other for the VCG--this allowed investigation of whether the combined interpretations would yield a better diagnostic result than either one separately. This approach requires that a VCG always be recorded in addition to the ECG. To circumvent this complication, the VCG was reconstructed from the simultaneously recorded ECG leads. This reconstructed VCG was then interpreted by the VCG classification program, whereupon the diagnostic interpretations of the ECG and the reconstructed VCG were combined. For the validation, the CSE database of documented ECGs and VCGs (n = 1,220) was used. The combination of the ECG and VCG interpretations yielded a better diagnostic result than each interpretation program separately (total accuracy 74.2% (ECG + VCG) vs 69.8% (ECG) and 70.2% (VCG), p less than 0.001 in both cases). The results for the reconstructed VCG (total accuracy 70.5%) are comparable to those for the ECG and the VCG (p greater than 0.10 in both cases). The performance of the combined interpretations of ECG and reconstructed VCG (total accuracy 73.6%) is approximately the same as that of the combined ECG and VCG (p greater than 0.10). Thus, the performance of an ECG computer program can be improved by incorporating both ECG and VCG classificatory knowledge, using only the ECG itself.
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