Abstract 12827: Detection of Spontaneous Pulse Using Acceleration Signals Acquired From CPR Feedback Sensor in Porcine Model of Cardiac Arrest

Abstract

Background: Reliable detection of return of spontaneous circulation (ROSC) without long interruptions of chest compressions is part of high-quality cardiopulmonary resuscitation (CPR) and routinely done by checking pulsation of carotid or femoral arteries. The purpose of the current study was to investigate whether acceleration signals acquired from a CPR feedback sensor can be used to distinguish perfusing rhythm from pulseless electrical activity (PEA) in a porcine model of cardiac arrest. Methods: The experimental data were collected from 50 male adult pigs with prolonged cardiac arrest and CPR. ECG, arterial blood pressure and acceleration signals were synchronously recorded at a sample rate of 300 Hz. The acceleration signal (ACC) was acquired from an accelerometer-based CPR sensor that was placed on the surface of the animal’s chest over the heart. During chest compression pauses 3-second segments of signals were extracted. ROSC was defined as systolic arterial pressure (SAP) >60 mmHg and pulse pressure (PP) >10 mmHg in the presence of an organized rhythm. ACC was pre-processed using a narrow band-pass filter with the center frequency from 0.5 to 7.5Hz. Cross-correlation function was calculated between ECG and filtered ACC to obtain the peak correlation coefficient (CCp). Area under the receiver operating characteristic curve (AUC) was used to evaluate the ability of CCp to detect ROSC. Results: A total of 216 segments were obtained with 63 in perfusing rhythm and 153 in PEA. The filtered ACC tracings (ACC’) in perfusing rhythm showed periodic oscillations synchronized with R waves, but no periodic oscillations were observed for PEA. Compared with PEA, heart rate (159.0±50.7 vs. 86.0±44.9 bpm, p <0.01), SAP (143.3±38.3 vs. 18.9±13.3 mmHg, p <0.01), pulse pressure (42.3±14.5 vs. 5.6±8.3 mmHg, p <0.01) and CCp (0.443±0.171 vs. 0.096±0.085, p <0.01) were significantly higher for perfusing rhythm. The AUC was 0.95 when CCp was used to differentiate ROSC from PEA. Using a cut-off threshold of 0.244, the sensitivity and specificity were 90.5% respectively. Conclusions: In this animal model, the acceleration signals acquired from a CPR feedback sensor can be used to distinguish perfusing rhythm from PEA.