TY - JOUR
T1 - Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest
AU - Chicote, Beatriz
AU - Aramendi, Elisabete
AU - Irusta, Unai
AU - Owens, Pamela
AU - Daya, Mohamud
AU - Idris, Ahamed
N1 - Funding Information:
Dr. Daya has received grant support from the US NIH and has served as an unpaid consultant for Philips Healthcare.
Funding Information:
This work received financial support from the Spanish Ministerio de Economía y Competitividad , project TEC2015-64678-R , jointly with the Fondo Europeo de Desarrollo Regional (FEDER), from the University of the Basque Country via Ayuda a Grupos de Investigación GIU17/03 and the grant PIF15/190 , and also was partially supported by NIH grant HL 077887 (AHÍ).
Funding Information:
This work received financial support from the Spanish Ministerio de Economía y Competitividad, project TEC2015-64678-R, jointly with the Fondo Europeo de Desarrollo Regional (FEDER), from the University of the Basque Country via Ayuda a Grupos de Investigación GIU17/03 and the grant PIF15/190, and also was partially supported by NIH grant HL 077887 (AHÍ).
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/5
Y1 - 2019/5
N2 - Background and aim: 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 CO 2 (EtCO 2 ) could improve the prediction. The aim of this study was to evaluate EtCO 2 as predictor of shock success, both individually and in combination with VF-waveform analysis. Materials and methods: 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 EtCO 2 (MEtCO 2 ) 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 MEtCO 2 and VF-waveform predictors. Separate analyses were done for first shocks and all shocks. Results: MEtCO 2 in first shocks was significantly higher for successful than for unsuccessful shocks (31 mmHg/25 mmHg, p < 0.05), but differences were not significant for all shocks (32 mmHg/29 mmHg, p > 0.05). MEtCO 2 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 MEtCO 2 improved the AUC of AMSA and FuzzyEn to 0.79 and 0.83, respectively. Conclusions: MEtCO 2 predicted defibrillation success only for first shocks. Adding MEtCO 2 to VF-waveform analysis in first shocks improved prediction of shock success. VF-waveform features and MEtCO 2 were automatically calculated from the device files, so these methods could be introduced in current defibrillators adding only new software.
AB - Background and aim: 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 CO 2 (EtCO 2 ) could improve the prediction. The aim of this study was to evaluate EtCO 2 as predictor of shock success, both individually and in combination with VF-waveform analysis. Materials and methods: 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 EtCO 2 (MEtCO 2 ) 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 MEtCO 2 and VF-waveform predictors. Separate analyses were done for first shocks and all shocks. Results: MEtCO 2 in first shocks was significantly higher for successful than for unsuccessful shocks (31 mmHg/25 mmHg, p < 0.05), but differences were not significant for all shocks (32 mmHg/29 mmHg, p > 0.05). MEtCO 2 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 MEtCO 2 improved the AUC of AMSA and FuzzyEn to 0.79 and 0.83, respectively. Conclusions: MEtCO 2 predicted defibrillation success only for first shocks. Adding MEtCO 2 to VF-waveform analysis in first shocks improved prediction of shock success. VF-waveform features and MEtCO 2 were automatically calculated from the device files, so these methods could be introduced in current defibrillators adding only new software.
KW - Amplitude spectrum area (AMSA)
KW - End-tidal CO (EtCO )
KW - Fuzzy entropy
KW - Out-of-hospital cardiac arrest
KW - Shock outcome prediction
KW - Ventricular fibrillation
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U2 - 10.1016/j.resuscitation.2019.02.028
DO - 10.1016/j.resuscitation.2019.02.028
M3 - Article
C2 - 30836170
AN - SCOPUS:85063113545
SN - 0300-9572
VL - 138
SP - 74
EP - 81
JO - Resuscitation
JF - Resuscitation
ER -