Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation

Aim:The rates of chest compressions (CCs) and ventilations are both important metrics to monitor the quality of cardiopulmonary resuscitation (CPR). Capnography permits monitoring ventilation, but the CCs provided during CPR corrupt the capnogram and compromise the accuracy of automatic ventilation...

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Autores: Aramendi Ecenarro, Elisabete, Elola Artano, Andoni, Alonso González, Erik, Irusta Zarandona, Unai, Daya, Mohamud Ramzan, Russell, James Knox, Hubner, Pia, Sterz, Fritz
Tipo de documento: artigo
Data de publicação:2017
País:España
Recursos:Universidad del País Vasco
Repositório:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/64798
Acesso em linha:http://hdl.handle.net/10810/64798
Access Level:Acceso aberto
Palavra-chave:ventilation monitoring
cardiopulmonary resuscitation
hyperventilation
capnography
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spelling Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitationAramendi Ecenarro, ElisabeteElola Artano, AndoniAlonso González, ErikIrusta Zarandona, UnaiDaya, Mohamud RamzanRussell, James KnoxHubner, PiaSterz, Fritzventilation monitoringcardiopulmonary resuscitationhyperventilationcapnographyAim:The rates of chest compressions (CCs) and ventilations are both important metrics to monitor the quality of cardiopulmonary resuscitation (CPR). Capnography permits monitoring ventilation, but the CCs provided during CPR corrupt the capnogram and compromise the accuracy of automatic ventilation detectors. The aim of this study was to evaluate the feasibility of an automatic algorithm based on the capnogram to detect ventilations and provide feedback on ventilation rate during CPR, specifically addressing intervals where CCs are delivered. Methods:The dataset used to develop and test the algorithm contained in-hospital and out-of-hospital cardiac arrest episodes. The method relies on adaptive thresholding to detect ventilations in the first derivative of the capnogram. The performance of the detector was reported in terms of sensitivity (SE) and Positive Predictive Value (PPV). The overall performance was reported in terms of the rate error and errors in the hyperventilation alarms. Results were given separately for the intervals with CCs. Results: A total of 83 episodes were considered, resulting in 4880 min and 46,740 ventilations (8741 during CCs). The method showed an overall SE/PPV above 99% and 97% respectively, even in intervals with CCs. The error for the ventilation rate was below 1.8 min−1 in any group, and >99% of the ventilation alarms were correctly detected. Conclusion: A method to provide accurate feedback on ventilation rate using only the capnogram is proposed. Its accuracy was proven even in intervals where canpography signal was severely corrupted by CCs. This algorithm could be integrated into monitor/defibrillators to provide reliable feedback on ventilation rate during CPR.This work received financial support from the Ministerio de Economía y Competitividad of Spain and FEDER through the projects TEC2012-31928 and TEC2015-64678-R, and from the University of the Basque Country (UPV/EHU) through the unit UFI11/16. The Medical University of Vienna received support in the form of a grant and the equipment used from Philips Healthcare, Bothell, WA, USA.Elsevier202420242017info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/64798reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoInglésinfo:eu-repo/grantAgreement/MINECO/TEC2012-31928/info:eu-repo/grantAgreement/MINECO/TEC2015-64678-R/https://www.sciencedirect.com/science/article/pii/S0300957216304725info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/3.0/es/© 2016 Elsevier Ireland Ltd. under Atribución-NoComercial-SinDerivadasoai:addi.ehu.eus:10810/647982026-06-18T09:23:17Z
dc.title.none.fl_str_mv Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
title Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
spellingShingle Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
Aramendi Ecenarro, Elisabete
ventilation monitoring
cardiopulmonary resuscitation
hyperventilation
capnography
title_short Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
title_full Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
title_fullStr Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
title_full_unstemmed Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
title_sort Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation
dc.creator.none.fl_str_mv Aramendi Ecenarro, Elisabete
Elola Artano, Andoni
Alonso González, Erik
Irusta Zarandona, Unai
Daya, Mohamud Ramzan
Russell, James Knox
Hubner, Pia
Sterz, Fritz
author Aramendi Ecenarro, Elisabete
author_facet Aramendi Ecenarro, Elisabete
Elola Artano, Andoni
Alonso González, Erik
Irusta Zarandona, Unai
Daya, Mohamud Ramzan
Russell, James Knox
Hubner, Pia
Sterz, Fritz
author_role author
author2 Elola Artano, Andoni
Alonso González, Erik
Irusta Zarandona, Unai
Daya, Mohamud Ramzan
Russell, James Knox
Hubner, Pia
Sterz, Fritz
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ventilation monitoring
cardiopulmonary resuscitation
hyperventilation
capnography
topic ventilation monitoring
cardiopulmonary resuscitation
hyperventilation
capnography
description Aim:The rates of chest compressions (CCs) and ventilations are both important metrics to monitor the quality of cardiopulmonary resuscitation (CPR). Capnography permits monitoring ventilation, but the CCs provided during CPR corrupt the capnogram and compromise the accuracy of automatic ventilation detectors. The aim of this study was to evaluate the feasibility of an automatic algorithm based on the capnogram to detect ventilations and provide feedback on ventilation rate during CPR, specifically addressing intervals where CCs are delivered. Methods:The dataset used to develop and test the algorithm contained in-hospital and out-of-hospital cardiac arrest episodes. The method relies on adaptive thresholding to detect ventilations in the first derivative of the capnogram. The performance of the detector was reported in terms of sensitivity (SE) and Positive Predictive Value (PPV). The overall performance was reported in terms of the rate error and errors in the hyperventilation alarms. Results were given separately for the intervals with CCs. Results: A total of 83 episodes were considered, resulting in 4880 min and 46,740 ventilations (8741 during CCs). The method showed an overall SE/PPV above 99% and 97% respectively, even in intervals with CCs. The error for the ventilation rate was below 1.8 min−1 in any group, and >99% of the ventilation alarms were correctly detected. Conclusion: A method to provide accurate feedback on ventilation rate using only the capnogram is proposed. Its accuracy was proven even in intervals where canpography signal was severely corrupted by CCs. This algorithm could be integrated into monitor/defibrillators to provide reliable feedback on ventilation rate during CPR.
publishDate 2017
dc.date.none.fl_str_mv 2017
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/64798
url http://hdl.handle.net/10810/64798
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MINECO/TEC2012-31928/
info:eu-repo/grantAgreement/MINECO/TEC2015-64678-R/
https://www.sciencedirect.com/science/article/pii/S0300957216304725
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
© 2016 Elsevier Ireland Ltd. under Atribución-NoComercial-SinDerivadas
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/3.0/es/
© 2016 Elsevier Ireland Ltd. under Atribución-NoComercial-SinDerivadas
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869415101420797952
score 15.300724

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