3 research outputs found

    Monitoring Chest Compression Rate in Automated External Defibrillators Using the Autocorrelation of the Transthoracic Impedance

    Get PDF
    Aim High-quality chest compressions is challenging for bystanders and first responders to out-of-hospital cardiac arrest (OHCA). Long compression pauses and compression rates higher than recommended are common and detrimental to survival. Our aim was to design a simple and low computational cost algorithm for feedback on compression rate using the transthoracic impedance (TI) acquired by automated external defibrillators (AEDs). Methods ECG and TI signals from AED recordings of 242 OHCA patients treated by basic life support (BLS) ambulances were retrospectively analyzed. Beginning and end of chest compression series and each individual compression were annotated. The algorithm computed a biased estimate of the autocorrelation of the TI signal in consecutive non-overlapping 2-s analysis windows to detect the presence of chest compressions and estimate compression rate. Results A total of 237 episodes were included in the study, with a median (IQR) duration of 10 (6-16) min. The algorithm performed with a global sensitivity in the detection of chest compressions of 98.7%, positive predictive value of 98.7%, specificity of 97.1%, and negative predictive value of 97.1% (validation subset including 207 episodes). The unsigned error in the estimation of compression rate was 1.7 (1.3-2.9) compressions per minute. Conclusion Our algorithm is accurate and robust for real-time guidance on chest compression rate using AEDs. The algorithm is simple and easy to implement with minimal software modifications. Deployment of AEDs with this capability could potentially contribute to enhancing the quality of chest compressions in the first minutes from collapse.The Basque Government provided support in the form of a grant for research groups (IT1087-16) for authors Sofia Ruiz de Gauna, Jesus Maria Ruiz, and Jose Julio Gutierrez. The Spanish Ministry of Economy, Industry and Competitiveness provided support in the form of a grant for research projects (RTI2018-094396-BI00) for authors Sofia Ruiz de Gauna, Jesus Maria Ruiz, and Jose Julio Gutierrez; and in the form of the program Torres Quevedo (PTQ-16-08201) for author Digna Maria Gonzalez-Otero. The University of the Basque Country (UPV/EHU) provided support in the form of a grant for collaboration between research groups and companies (US18/30) for authors Sofia Ruiz de Gauna, Jesus Maria Ruiz, and Jose Julio Gutierrez. Bexen Cardio, a Spanish medical device manufacturer, provided support in the form of a salary for author Digna Mara Gonzalez-Otero. None of the above funding organizations had any additional role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of each author is articulated in the Author Contributions section. Authors Daniel Alonso, Carlos Corcuera, and Juan Francisco Urtusagasti received no funding for this work

    Modeling the impact of ventilations on the capnogram in out-of-hospital cardiac arrest

    Get PDF
    Aim Current resuscitation guidelines recommend waveform capnography as an indirect indicator of perfusion during cardiopulmonary resuscitation (CPR). Chest compressions (CCs) and ventilations during CPR have opposing effects on the exhaled carbon dioxide (CO2) concentration, which need to be better characterized. The purpose of this study was to model the impact of ventilations in the exhaled CO2 measured from capnograms collected during out-of-hospital cardiac arrest (OHCA) resuscitation. Methods We retrospectively analyzed OHCA monitor-defibrillator files with concurrent capnogram, compression depth, transthoracic impedance and ECG signals. Segments with CC pauses, two or more ventilations, and with no pulse-generating rhythm were selected. Thus, only ventilations should have caused the decrease in CO2 concentration. The variation in the exhaled CO2 concentration with each ventilation was modeled with an exponential decay function using non-linear-least-squares curve fitting. Results Out of the original 1002 OHCA dataset (one per patient), 377 episodes had the required signals, and 196 segments from 96 patients met the inclusion criteria. Airway type was endotracheal tube in 64.8% of the segments, supraglottic King LT-D (TM) in 30.1%, and unknown in 5.1%. Median (IQR) decay factor of the exhaled CO2 concentration was 10.0% (7.8 - 12.9) with R-2 = 0.98(0.95 - 0.99). Differences in decay factor with airway type were not statistically significant (p = 0.17). From these results, we propose a model for estimating the contribution of CCs to the end-tidal CO2 level between consecutive ventilations and for estimating the end-tidal CO2 variation as a function of ventilation rate. Conclusion We have modeled the decrease in exhaled CO2 concentration with ventilations during chest compression pauses in CPR. This finding allowed us to hypothesize a mathematical model for explaining the effect of chest compressions on ETCO2 compensating for the influence of ventilation rate during CPR. However, further work is required to confirm the validity of this model during ongoing chest compressions.The Basque Government provided support in the form of a grant for research groups (IT1087-16) for authors Jose Julio Gutierrez, Jesus Maria Ruiz, Sofia Ruiz de Gauna, and Mikel Leturiondo; and in the form of a predoctoral grant (PRE-2017-2-0201) for author Mikel Leturiondo (https://www.euskadi.eus).The Spanish Ministry of Economy, Industry and Competitiveness provided support in the form of a grant for research projects (RTI2018-094396-B-I00) for authors Jose Julio Gutierrez, Jesus Maria Ruiz, Sofia Ruiz de Gauna, and Mikel Leturiondo; and in the form of the program Torres Quevedo (PTQ-16-08201) for author Digna Maria Gonzalez-Otero (http://www.ciencia.gob.es/).Bexen Cardio, a Spanish medical device manufacturer, provided support in the form of a salary for author Digna Mari ' a Gonza ' lez-Otero. None of the above funders had any additional role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of each author is articulated in the "author contributions" section. Authors James Knox Russell, Carlos Corcuera, Juan Francisco Urtusagasti, and Mohamud Ramzan Daya received no funding for this work

    Assessment of the evolution of end-tidal carbon dioxide within chest compression pauses to detect restoration of spontaneous circulation.

    Get PDF
    BackgroundMeasurement of end-tidal CO2 (ETCO2) can help to monitor circulation during cardiopulmonary resuscitation (CPR). However, early detection of restoration of spontaneous circulation (ROSC) during CPR using waveform capnography remains a challenge. The aim of the study was to investigate if the assessment of ETCO2 variation during chest compression pauses could allow for ROSC detection. We hypothesized that a decay in ETCO2 during a compression pause indicates no ROSC while a constant or increasing ETCO2 indicates ROSC.MethodsWe conducted a retrospective analysis of adult out-of-hospital cardiac arrest (OHCA) episodes treated by the advanced life support (ALS). Continuous chest compressions and ventilations were provided manually. Segments of capnography signal during pauses in chest compressions were selected, including at least three ventilations and with durations less than 20 s. Segments were classified as ROSC or non-ROSC according to case chart annotation and examination of the ECG and transthoracic impedance signals. The percentage variation of ETCO2 between consecutive ventilations was computed and its average value, ΔETavg, was used as a single feature to discriminate between ROSC and non-ROSC segments.ResultsA total of 384 segments (130 ROSC, 254 non-ROSC) from 205 OHCA patients (30.7% female, median age 66) were analyzed. Median (IQR) duration was 16.3 (12.9,18.1) s. ΔETavg was 0.0 (-0.7, 0.9)% for ROSC segments and -11.0 (-14.1, -8.0)% for non-ROSC segments (p ConclusionAverage percent variation of ETCO2 during pauses in chest compressions allowed for ROSC discrimination. This metric could help confirm ROSC during compression pauses in ALS settings
    corecore