Enhancement of capnogram waveform in the presence of chest compression artefact during cardiopulmonary resuscitation

Sofía Ruiz de Gauna, Mikel Leturiondo, J. Julio Gutiérrez, Jesus M. Ruiz, Digna M. González-Otero, James K. Russell, Mohamud Ramzan Daya

Research output: Contribution to journalArticle

Abstract

Background: Current resuscitation guidelines emphasize the use of waveform capnography to help guide rescuers during cardiopulmonary resuscitation (CPR). However, chest compressions often cause oscillations in the capnogram, impeding its reliable interpretation, either visual or automated. The aim of the study was to design an algorithm to enhance waveform capnography by suppressing the chest compression artefact. Methods: Monitor-defibrillator recordings from 202 patients in out-of-hospital cardiac arrest were analysed. Capnograms were classified according to the morphology of the artefact. Ventilations were annotated using the transthoracic impedance signal acquired through defibrillation pads. The suppression algorithm is designed to operate in real-time, locating distorted intervals and restoring the envelope of the capnogram. We evaluated the improvement in automated ventilation detection, estimation of ventilation rate, and detection of excessive ventilation rates (over-ventilation) using the capnograms before and after artefact suppression. Results: A total of 44 267 ventilations were annotated. After artefact suppression, sensitivity (Se) and positive predictive value (PPV) of the ventilation detector increased from 91.9/89.5% to 98.0/97.3% in the distorted episodes (83/202). Improvement was most noticeable for high-amplitude artefact, for which Se/PPV raised from 77.6/73.5% to 97.1/96.1%. Estimation of ventilation rate and detection of over-ventilation also upgraded. The suppression algorithm had minimal impact in non-distorted data. Conclusion: Ventilation detection based on waveform capnography improved after chest compression artefact suppression. Moreover, the algorithm enhances the capnogram tracing, potentially improving its clinical interpretation during CPR. Prospective research in clinical settings is needed to understand the feasibility and utility of the method.

Original languageEnglish (US)
Pages (from-to)53-58
Number of pages6
JournalResuscitation
Volume133
DOIs
StatePublished - Dec 1 2018

Fingerprint

Cardiopulmonary Resuscitation
Artifacts
Ventilation
Thorax
Capnography
Impedance Cardiography
Out-of-Hospital Cardiac Arrest
Defibrillators
Resuscitation
Guidelines

Keywords

  • Advanced life support
  • Cardiopulmonary resuscitation
  • Chest compression artefact
  • Chest compressions
  • Ventilation
  • Waveform capnography

ASJC Scopus subject areas

  • Emergency Medicine
  • Emergency
  • Cardiology and Cardiovascular Medicine

Cite this

Ruiz de Gauna, S., Leturiondo, M., Gutiérrez, J. J., Ruiz, J. M., González-Otero, D. M., Russell, J. K., & Daya, M. R. (2018). Enhancement of capnogram waveform in the presence of chest compression artefact during cardiopulmonary resuscitation. Resuscitation, 133, 53-58. https://doi.org/10.1016/j.resuscitation.2018.09.024

Enhancement of capnogram waveform in the presence of chest compression artefact during cardiopulmonary resuscitation. / Ruiz de Gauna, Sofía; Leturiondo, Mikel; Gutiérrez, J. Julio; Ruiz, Jesus M.; González-Otero, Digna M.; Russell, James K.; Daya, Mohamud Ramzan.

In: Resuscitation, Vol. 133, 01.12.2018, p. 53-58.

Research output: Contribution to journalArticle

Ruiz de Gauna, Sofía ; Leturiondo, Mikel ; Gutiérrez, J. Julio ; Ruiz, Jesus M. ; González-Otero, Digna M. ; Russell, James K. ; Daya, Mohamud Ramzan. / Enhancement of capnogram waveform in the presence of chest compression artefact during cardiopulmonary resuscitation. In: Resuscitation. 2018 ; Vol. 133. pp. 53-58.
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abstract = "Background: Current resuscitation guidelines emphasize the use of waveform capnography to help guide rescuers during cardiopulmonary resuscitation (CPR). However, chest compressions often cause oscillations in the capnogram, impeding its reliable interpretation, either visual or automated. The aim of the study was to design an algorithm to enhance waveform capnography by suppressing the chest compression artefact. Methods: Monitor-defibrillator recordings from 202 patients in out-of-hospital cardiac arrest were analysed. Capnograms were classified according to the morphology of the artefact. Ventilations were annotated using the transthoracic impedance signal acquired through defibrillation pads. The suppression algorithm is designed to operate in real-time, locating distorted intervals and restoring the envelope of the capnogram. We evaluated the improvement in automated ventilation detection, estimation of ventilation rate, and detection of excessive ventilation rates (over-ventilation) using the capnograms before and after artefact suppression. Results: A total of 44 267 ventilations were annotated. After artefact suppression, sensitivity (Se) and positive predictive value (PPV) of the ventilation detector increased from 91.9/89.5{\%} to 98.0/97.3{\%} in the distorted episodes (83/202). Improvement was most noticeable for high-amplitude artefact, for which Se/PPV raised from 77.6/73.5{\%} to 97.1/96.1{\%}. Estimation of ventilation rate and detection of over-ventilation also upgraded. The suppression algorithm had minimal impact in non-distorted data. Conclusion: Ventilation detection based on waveform capnography improved after chest compression artefact suppression. Moreover, the algorithm enhances the capnogram tracing, potentially improving its clinical interpretation during CPR. Prospective research in clinical settings is needed to understand the feasibility and utility of the method.",
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AU - Leturiondo, Mikel

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AU - Ruiz, Jesus M.

AU - González-Otero, Digna M.

AU - Russell, James K.

AU - Daya, Mohamud Ramzan

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AB - Background: Current resuscitation guidelines emphasize the use of waveform capnography to help guide rescuers during cardiopulmonary resuscitation (CPR). However, chest compressions often cause oscillations in the capnogram, impeding its reliable interpretation, either visual or automated. The aim of the study was to design an algorithm to enhance waveform capnography by suppressing the chest compression artefact. Methods: Monitor-defibrillator recordings from 202 patients in out-of-hospital cardiac arrest were analysed. Capnograms were classified according to the morphology of the artefact. Ventilations were annotated using the transthoracic impedance signal acquired through defibrillation pads. The suppression algorithm is designed to operate in real-time, locating distorted intervals and restoring the envelope of the capnogram. We evaluated the improvement in automated ventilation detection, estimation of ventilation rate, and detection of excessive ventilation rates (over-ventilation) using the capnograms before and after artefact suppression. Results: A total of 44 267 ventilations were annotated. After artefact suppression, sensitivity (Se) and positive predictive value (PPV) of the ventilation detector increased from 91.9/89.5% to 98.0/97.3% in the distorted episodes (83/202). Improvement was most noticeable for high-amplitude artefact, for which Se/PPV raised from 77.6/73.5% to 97.1/96.1%. Estimation of ventilation rate and detection of over-ventilation also upgraded. The suppression algorithm had minimal impact in non-distorted data. Conclusion: Ventilation detection based on waveform capnography improved after chest compression artefact suppression. Moreover, the algorithm enhances the capnogram tracing, potentially improving its clinical interpretation during CPR. Prospective research in clinical settings is needed to understand the feasibility and utility of the method.

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