Why the study?
AMSA can guide CPR and defibrillation timing, but artifacts currently limit reliable calculation to chest compression pauses.
Does a signal quality-based artifact suppression method accurately estimate AMSA during chest compressions in out-of-hospital cardiac arrest patients?
Observational (n=512)
Does a signal quality-based artifact suppression method accurately estimate AMSA during chest compressions in out-of-hospital cardiac arrest patients?
Answers are grounded in this paper and cite their sources.
A novel signal quality-based artifact suppression method allows for reliable and continuous estimation of AMSA during cardiopulmonary resuscitation without needing to pause chest compressions.
Background: Amplitude spectrum area (AMSA) calculated from ventricular fibrillation (VF) can be used to monitor the effectiveness of chest compression (CC) and optimize the timing of defibrillation. However, reliable AMSA can only be obtained during CC pause because of artifacts. In this study, we sought to develop a method for estimating AMSA during cardiopulmonary resuscitation (CPR) using only the electrocardiogram (ECG) waveform.Methods: Intervals of 8 seconds ECG and CC-related references, including 4 seconds during CC and an adjacent 4 seconds without CC, were collected before 1,008 defibrillation shocks from 512 out-of-hospital cardiac arrest patients. Signal quality was analyzed based on the irregularity of autocorrelation of VF. If signal quality index (SQI) was high, AMSA would be calculated from the original signal. Otherwise, CC-related artifacts would be constructed and suppressed using the least mean square filter from VF before calculation of AMSA. The algorithm was optimized using 480 training shocks and evaluated using 528 independent testing shocks.Results: Overall, CC resulted in lower SQI [0.15 (0.04–0.61) with CC vs. 0.75 (0.61–0.83) without CC, P<0.01] and higher AMSA [11.2 (7.7–16.2) with CC vs. 7.2 (4.9–10.6) mVHz without CC, P<0.01] values. The predictive accuracy (49.2% vs. 66.5%, P<0.01) and area under the receiver operating characteristic curve (AUC) (0.647 vs. 0.734, P<0.01) were significantly decreased during CC. Using the proposed method, the estimated AMSA was 7.1 (5.0–15.2) mVHz, the predictive accuracy was 67.0% and the AUC was 0.713, which were all comparable with those calculated without CC.Conclusions: Using the signal quality-based artifact suppression method, AMSA can be reliably estimated and continuously monitored during CPR.
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Zuo et al. (2021) conducted an observational in Out-of-hospital cardiac arrest (n=512). Signal quality-based artifact suppression method vs. AMSA calculated without chest compressions was evaluated on Predictive accuracy.
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