Journal of Clinical Monitoring and Computing | 2021

Assessment of a new volumetric capnography-derived parameter to reflect compression quality and to predict return of spontaneous circulation during cardiopulmonary resuscitation in a porcine model

 
 
 
 
 
 
 
 
 

Abstract


We aimed to evaluate a volumetric capnography (Vcap)-derived parameter, the volume of CO 2 eliminated per minute and per kg body weight (VCO 2 /kg), as an indicator of the quality of chest compression (CC) and to predict the return to spontaneous circulation (ROSC) under stable ventilation status. Twelve male domestic pigs were utilized for the randomized crossover study. After 4\xa0min of untreated ventricular fibrillation (VF), mechanical cardiopulmonary resuscitation and ventilation were administered. Following 5-min washout periods, each animal underwent two sessions of experiments: three types of CC quality for 5\xa0min stages in the first session, followed by advanced life support, consecutively in two sessions. Different CC quality had a significant effect on the partial pressure of end-tidal carbon dioxide (PetCO 2 ), VCO 2 /kg, aortic pressure (mean), aortic systolic pressure, aortic diastolic pressure, right atrial pressure (mean), and carotid blood flow (P\u2009<\u20090.05). With the improvement in CC quality, the values of PetCO 2 and VCO 2 /kg also increased, and the difference between the groups was statistically significant (P\u2009<\u20090.05). The Spearman rank test revealed a significant correlation between the Vcap-derived parameters and hemodynamics. PetCO 2 and VCO 2 /kg have similar capabilities for discriminating survivors from non-survivors, and the area under the curve for both was 0.97. VCO 2 /kg had similar performance as PetCO 2 in reflecting the quality of CC and prediction of achieving ROSC under stable ventilation status in a porcine model of VF-related cardiac arrest. However, VCO 2 /kg requires a longer time to achieve a stable state after adjusting for quality of CC than PetCO 2 .

Volume None
Pages 1-9
DOI 10.1007/s10877-020-00637-1
Language English
Journal Journal of Clinical Monitoring and Computing

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