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The Diagnostic Accuracy of a Shock Advisory Algorithm in Automated External Defibrillators in the Presence of Real-world Artifacts.
Resuscitation 2024 March 10
BACKGROUND: The current standards for shock advisory algorithms in AEDs require performance testing on artifact-free ECGs. However, AED analysis in the real world is more challenging due to potential artifacts from various sources (e.g., patient handling, and electromagnetic interference). This retrospective data analysis reports the real-world performance and behavior of a shock advisory algorithm used in three AED models with the presence of artifacts.
METHODS: ECG rhythm analyses recorded during the use of three AED models (HS1, FRx and FR3) were reviewed. The shock recommendations made in the AEDs were compared to the expert annotations of reviewers. The effects of real-world artifacts and the handling by the algorithm were analyzed.
RESULTS: Among the 3,941 analyses, 619 were annotated as shockable rhythms, and 2,912 were non-shockable. The overall sensitivity and specificity were 97.1% (601/619), and 99.9% (2,908/2,912), respectively. Artifacts were detected by the algorithm in 23.3% (918/3,941) of the analysis periods. The algorithm performance for the analysis periods with artifacts detected was 95.2% (80/84) for sensitivity and 100.0% (687/687) for specificity. In the remaining analysis periods with no artifacts detected, the sensitivity was 97.4% (521/535), and specificity was 99.8% (2,221/2,225).
CONCLUSIONS: The performance of this shock advisory algorithm during real-world resuscitations with or without artifacts, exceeded AHA recommendations and the requirements in international standards. The high sensitivity and specificity demonstrate the effectiveness and safety of this algorithm in all three AED models.
METHODS: ECG rhythm analyses recorded during the use of three AED models (HS1, FRx and FR3) were reviewed. The shock recommendations made in the AEDs were compared to the expert annotations of reviewers. The effects of real-world artifacts and the handling by the algorithm were analyzed.
RESULTS: Among the 3,941 analyses, 619 were annotated as shockable rhythms, and 2,912 were non-shockable. The overall sensitivity and specificity were 97.1% (601/619), and 99.9% (2,908/2,912), respectively. Artifacts were detected by the algorithm in 23.3% (918/3,941) of the analysis periods. The algorithm performance for the analysis periods with artifacts detected was 95.2% (80/84) for sensitivity and 100.0% (687/687) for specificity. In the remaining analysis periods with no artifacts detected, the sensitivity was 97.4% (521/535), and specificity was 99.8% (2,221/2,225).
CONCLUSIONS: The performance of this shock advisory algorithm during real-world resuscitations with or without artifacts, exceeded AHA recommendations and the requirements in international standards. The high sensitivity and specificity demonstrate the effectiveness and safety of this algorithm in all three AED models.
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