Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest.

Abstract

Unsuccessful defibrillation shocks adversely affect survival from out-of-hospital cardiac arrest (OHCA). Ventricular fibrillation (VF) waveform analysis is the tool-of-choice for the non-invasive prediction of shock success, but surrogate markers of perfusion like end-tidal CO₂ (EtCO₂) could improve the prediction. The aim of this study was to evaluate EtCO₂ as predictor of shock success, both individually and in combination with VF-waveform analysis. In total 514 shocks from 214 OHCA patients (75 first shocks) were analysed. For each shock three predictors of defibrillation success were automatically calculated from the device files: two VF-waveform features, amplitude spectrum area (AMSA) and fuzzy entropy (FuzzyEn), and the median EtCO₂ (MEtCO₂) in the minute before the shock. Sensitivity, specificity, receiver operating characteristic (ROC) curves and area under the curve (AUC) were calculated, for each predictor individually and for the combination of MEtCO₂ and VF-waveform predictors. Separate analyses were done for first shocks and all shocks. MEtCO₂ in first shocks was significantly higher for successful than for unsuccessful shocks (31mmHg/25mmHg, p<0.05), but differences were not significant for all shocks (32mmHg/29mmHg, p>0.05). MEtCO₂ predicted shock success with an AUC of 0.66 for first shocks, but was not a predictor for all shocks (AUC 0.54). AMSA and FuzzyEn presented AUCs of 0.76 and 0.77 for first shocks, and 0.75 and 0.75 for all shocks. For first shocks, adding MEtCO₂ improved the AUC of AMSA and FuzzyEn to 0.79 and 0.83, respectively. MEtCO₂ predicted defibrillation success only for first shocks. Adding MEtCO₂ to VF-waveform analysis in first shocks improved prediction of shock success. VF-waveform features and MEtCO₂ were automatically calculated from the device files, so these methods could be introduced in current defibrillators adding only new software.