The performance of a new shock advisory algorithm to reduce interruptions during CPR

Area of Science:

• Emergency Medicine
• Cardiology
• Medical Technology

Background:

• Cardiopulmonary resuscitation (CPR) effectiveness is often limited by interruptions in chest compressions (CCs) for rhythm analysis.
• Accurate and timely rhythm identification is crucial for determining the need for defibrillation during cardiac arrest (CA).

Purpose of the Study:

• To introduce and evaluate a novel algorithm, the Analysis Through CPR (ATC), for rhythm analysis during CCs.
• To enhance CPR efficiency by minimizing the duration of CC interruptions.

Main Methods:

• A two-step ATC algorithm was applied to ECG data from 166 cardiac arrest patients.
• The algorithm analyzed ECG segments during CCs and, if necessary, during a compression-free period.
• Algorithm performance was compared against expert physician annotations for sensitivity and specificity.

Main Results:

• The ATC algorithm achieved a sensitivity of 93.6% and specificity of 99.5% after the two-step analysis.
• 70.5% of ventricular fibrillation (VF) rhythms were identified by the end of CCs, with 93.6% identified after the compression-free analysis.
• The algorithm demonstrated high accuracy in identifying non-shockable rhythms (99.8% specificity at CC end, 99.5% after analysis).

Conclusions:

• The ATC algorithm offers a potential strategy to significantly reduce CC interruptions during rhythm analysis.
• This approach can improve the overall efficiency and effectiveness of CPR in cardiac arrest management.