BACKGROUND: Capnography has been proposed as a method for monitoring the ventilation rate during cardiopulmonary resuscitation (CPR). A high incidence (above 70%) of capnograms distorted by chest compression induced oscillations has been previously reported in out-of-hospital (OOH) CPR. The aim of the study was to better characterize the chest compression artefact and to evaluate its influence on the performance of a capnogram-based ventilation detector during OOH CPR. METHODS: Data from the MRx monitor-defibrillator were extracted from OOH cardiac arrest episodes. For each episode, presence of chest compression artefact was annotated in the capnogram. Concurrent compression depth and transthoracic impedance signals were used to identify chest compressions and to annotate ventilations, respectively. We designed a capnogram-based ventilation detection algorithm and tested its performance with clean and distorted episodes. RESULTS: Data were collected from 232 episodes comprising 52 654 ventilations, with a mean (±SD) of 227 (±118) per episode. Overall, 42% of the capnograms were distorted. Presence of chest compression artefact degraded algorithm performance in terms of ventilation detection, estimation of ventilation rate, and the ability to detect hyperventilation. CONCLUSION: Capnogram-based ventilation detection during CPR using our algorithm was compromised by the presence of chest compression artefact. In particular, artefact spanning from the plateau to the baseline strongly degraded ventilation detection, and caused a high number of false hyperventilation alarms. Further research is needed to reduce the impact of chest compression artefact on capnographic ventilation monitoring.
BACKGROUND: Capnography has been proposed as a method for monitoring the ventilation rate during cardiopulmonary resuscitation (CPR). A high incidence (above 70%) of capnograms distorted by chest compression induced oscillations has been previously reported in out-of-hospital (OOH) CPR. The aim of the study was to better characterize the chest compression artefact and to evaluate its influence on the performance of a capnogram-based ventilation detector during OOH CPR. METHODS: Data from the MRx monitor-defibrillator were extracted from OOHcardiac arrest episodes. For each episode, presence of chest compression artefact was annotated in the capnogram. Concurrent compression depth and transthoracic impedance signals were used to identify chest compressions and to annotate ventilations, respectively. We designed a capnogram-based ventilation detection algorithm and tested its performance with clean and distorted episodes. RESULTS: Data were collected from 232 episodes comprising 52 654 ventilations, with a mean (±SD) of 227 (±118) per episode. Overall, 42% of the capnograms were distorted. Presence of chest compression artefact degraded algorithm performance in terms of ventilation detection, estimation of ventilation rate, and the ability to detect hyperventilation. CONCLUSION: Capnogram-based ventilation detection during CPR using our algorithm was compromised by the presence of chest compression artefact. In particular, artefact spanning from the plateau to the baseline strongly degraded ventilation detection, and caused a high number of false hyperventilation alarms. Further research is needed to reduce the impact of chest compression artefact on capnographic ventilation monitoring.
Authors: Robert M Sutton; Ron W Reeder; William P Landis; Kathleen L Meert; Andrew R Yates; Ryan W Morgan; John T Berger; Christopher J Newth; Joseph A Carcillo; Patrick S McQuillen; Rick E Harrison; Frank W Moler; Murray M Pollack; Todd C Carpenter; Daniel A Notterman; Richard Holubkov; J Michael Dean; Vinay M Nadkarni; Robert A Berg Journal: Crit Care Med Date: 2019-11 Impact factor: 7.598
Authors: Jose Julio Gutiérrez; Jesus María Ruiz; Sofía Ruiz de Gauna; Digna María González-Otero; Mikel Leturiondo; James Knox Russell; Carlos Corcuera; Juan Francisco Urtusagasti; Mohamud Ramzan Daya Journal: PLoS One Date: 2020-02-05 Impact factor: 3.240
Authors: Jose Julio Gutiérrez; Mikel Leturiondo; Sofía Ruiz de Gauna; Jesus María Ruiz; Luis Alberto Leturiondo; Digna María González-Otero; Dana Zive; James Knox Russell; Mohamud Daya Journal: PLoS One Date: 2018-08-02 Impact factor: 3.240