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

Beatriz Chicote; Elisabete Aramendi; Unai Irusta; Pamela Owens; Mohamud Daya; Ahamed Idris

doi:10.1016/j.resuscitation.2019.02.028

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

Beatriz Chicote
, Elisabete Aramendi
, Unai Irusta
, Pamela Owens
, Mohamud Daya
, Ahamed Idris

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	74-81
Number of pages	8
Journal	Resuscitation
Volume	138
DOIs	https://doi.org/10.1016/j.resuscitation.2019.02.028
State	Published - May 1 2019

Funding

Dr. Idris receives research grants from the US National Institutes of Health (NIH) and serves as an unpaid volunteer on the American Heart Association National Emergency Cardiovascular Care Committee and the HeartSine, Inc. Clinical Advisory. 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). 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).

Funders	Funder number
Author National Institutes of Health National Institutes of Health National Institutes of Health National Institutes of Health The Bev Hartig Huntington's Disease Foundation National Institutes of Health
National Institute of Health National Heart, Lung, and Blood Institute	U01HL077887
Ministerio de Economía y Competitividad	TEC2015-64678-R
Euskal Herriko Unibertsitatea	PIF15/190, GIU17/03
European Regional Development Fund/European Social Fund FIS
Norges Idrettshøgskole

Keywords

Amplitude spectrum area (AMSA)
End-tidal CO (EtCO )
Fuzzy entropy
Out-of-hospital cardiac arrest
Shock outcome prediction
Ventricular fibrillation

ASJC Scopus subject areas

Emergency Medicine
Emergency
Cardiology and Cardiovascular Medicine

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10.1016/j.resuscitation.2019.02.028

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@article{7b04b29c78774e5b8f0ba5ded39bf30b,

title = "Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest",

abstract = " 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.",

keywords = "Amplitude spectrum area (AMSA), End-tidal CO (EtCO ), Fuzzy entropy, Out-of-hospital cardiac arrest, Shock outcome prediction, Ventricular fibrillation",

author = "Beatriz Chicote and Elisabete Aramendi and Unai Irusta and Pamela Owens and Mohamud Daya and Ahamed Idris",

note = "Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",

year = "2019",

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doi = "10.1016/j.resuscitation.2019.02.028",

language = "English (US)",

volume = "138",

pages = "74--81",

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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

PY - 2019/5/1

Y1 - 2019/5/1

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

Abstract

Funding

Keywords

ASJC Scopus subject areas

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