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Diagnostic accuracy of computer aided electrocardiogram analysis in dogs
A H Estrada1, A Spake2, M E Kleman2
1Department of Small Animal Clinical Sciences, University of Florida, College of Veterinary Medicine, Gainesville, FL, 32610, USA.
Insights
A new computerized electrocardiogram (ECG) algorithm shows high accuracy in detecting canine arrhythmias. While effective for arrhythmias, it is less accurate for identifying all ECG anomalies, suggesting its use as a triage tool.
Area of Science:
- Veterinary Cardiology
- Biomedical Engineering
- Diagnostic Imaging
Background:
- Electrocardiograms (ECGs) are crucial for diagnosing cardiac conditions in animals.
- Accurate interpretation of ECGs requires specialized expertise, potentially leading to delays in diagnosis and treatment.
- Automated ECG analysis tools can potentially improve efficiency and accuracy in veterinary cardiology.
Purpose of the Study:
- To evaluate the diagnostic performance of a computerized ECG algorithm in dogs.
- To compare the algorithm's interpretation against a consensus panel of board-certified veterinary cardiologists.
- To determine the algorithm's utility in identifying arrhythmias and other ECG anomalies.
Main Methods:
- A retrospective cohort study involving 399 canine ECG recordings.
- ECGs were analyzed by a panel of seven veterinary cardiologists for various parameters and overall diagnosis.
- The computerized algorithm's interpretations were compared against the cardiologists' consensus findings.
Main Results:
- The algorithm demonstrated high sensitivity (99.7%) and specificity (99.5%) for detecting arrhythmias.
- For identifying any ECG anomaly, the algorithm's sensitivity was 71.3% and specificity was 35.1%.
- The algorithm excelled in arrhythmia detection but was less comprehensive for all ECG abnormalities.
Conclusions:
- The computerized ECG algorithm is a highly sensitive tool for detecting arrhythmias in dogs.
- The algorithm is not as effective in identifying all types of ECG anomalies.
- This tool can aid in the triage of ECGs within a veterinary clinical workflow, supporting cardiologists' interpretations.
Objectives:
Evaluation of a computerised electrocardiogram algorithm compared to the interpretation of a team of board-certified veterinary cardiologists.
Materials And Methods:
This was a cross-sectional retrospective cohort study. A total of 399 electronic canine electrocardiogram recordings screened from 1391 electrocardiograms were enrolled in the study. A panel of seven cardiologists, masked to patient information, evaluated electrocardiograms for the following: P-wave amplitude and duration; PR-interval; R-wave amplitude; QRS duration; heart rate; mean electrical axis; and final overall diagnosis for the detection of arrhythmia and any abnormal electrocardiogram anomaly.
Results:
The sensitivity of the electrocardiogram algorithm for detecting arrhythmias was 99.7% (95% confidence intervals, CI: 98.5 to 99.9) and the specificity was 99.5% (95% CI: 98.0 to 99.9) compared to the consensus result created by panel of cardiologists. The sensitivity of the algorithm for the detection of any electrocardiogram anomaly, including abnormal measurements, was 71.3% (95% CI: 65.5 to 76.7) and the specificity was 35.1% (95% CI: 27.0 to 43.8) compared to the panel of cardiologists.
Clinical Significance:
The electrocardiogram algorithm was shown to have high sensitivity for the detection of arrhythmias, but not all electrocardiogram anomalies. The results support the use of this algorithm as a tool to aid in the triage of the electrocardiogram workflow.
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