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

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

Research output: Contribution to journalArticle

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 languageEnglish (US)
Pages (from-to)74-81
Number of pages8
JournalResuscitation
Volume138
DOIs
StatePublished - May 1 2019
Externally publishedYes

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Capnography
Out-of-Hospital Cardiac Arrest
Shock
Ventricular Fibrillation
Area Under Curve
Entropy
Carbon Monoxide

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

Cite this

Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest. / Chicote, Beatriz; Aramendi, Elisabete; Irusta, Unai; Owens, Pamela; Daya, Mohamud; Idris, Ahamed H.

In: Resuscitation, Vol. 138, 01.05.2019, p. 74-81.

Research output: Contribution to journalArticle

Chicote, Beatriz ; Aramendi, Elisabete ; Irusta, Unai ; Owens, Pamela ; Daya, Mohamud ; Idris, Ahamed H. / Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest. In: Resuscitation. 2019 ; Vol. 138. pp. 74-81.
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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.",
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AU - Chicote, Beatriz

AU - Aramendi, Elisabete

AU - Irusta, Unai

AU - Owens, Pamela

AU - Daya, Mohamud

AU - Idris, Ahamed H

PY - 2019/5/1

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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.

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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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