Abstract
Background: Quality of cardiopulmonary resuscitation (CPR) is an important determinant of survival from cardiac arrest. The use of feedback devices is encouraged by current resuscitation guidelines as it helps rescuers to improve quality of CPR performance. Aim: To determine the feasibility of a generic algorithm for feedback related to chest compression (CC) rate using the transthoracic impedance (TTI) signal recorded through the defibrillation pads. Methods: We analysed 180 episodes collected equally from three different emergency services, each one using a unique defibrillator model. The new algorithm computed the CC-rate every 2. s by analysing the TTI signal in the frequency domain. The obtained CC-rate values were compared with the gold standard, computed using the compression force or the ECG and TTI signals when the force was not recorded. The accuracy of the CC-rate, the proportion of alarms of inadequate CC-rate, chest compression fraction (CCF) and the mean CC-rate per episode were calculated. Results: Intervals with CCs were detected with a mean sensitivity and a mean positive predictive value per episode of 96.3% and 97.0%, respectively. Estimated CC-rate had an error below 10% in 95.8% of the time. Mean percentage of accurate alarms per episode was 98.2%. No statistical differences were found between the gold standard and the estimated values for any of the computed metrics. Conclusion: We developed an accurate algorithm to calculate and provide feedback on CC-rate using the TTI signal. This could be integrated into automated external defibrillators and help improve the quality of CPR in basic-life-support settings.
Original language | English (US) |
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Pages (from-to) | 82-88 |
Number of pages | 7 |
Journal | Resuscitation |
Volume | 93 |
DOIs | |
State | Published - Aug 1 2015 |
Keywords
- Automated external defibrillator
- Basic life support
- CPR quality
- Chest compression
- Transthoracic impedance
ASJC Scopus subject areas
- Emergency Medicine
- Emergency
- Cardiology and Cardiovascular Medicine