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Modeling the impact of ventilations on the capnogram in out-of-hospital cardiac arrest
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 (CO(2)) concentration, which need to be bett...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7001922/ https://www.ncbi.nlm.nih.gov/pubmed/32023298 http://dx.doi.org/10.1371/journal.pone.0228395 |
Sumario: | 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 (CO(2)) concentration, which need to be better characterized. The purpose of this study was to model the impact of ventilations in the exhaled CO(2) 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 CO(2) concentration. The variation in the exhaled CO(2) 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(™) in 30.1%, and unknown in 5.1%. Median (IQR) decay factor of the exhaled CO(2) 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 CO(2) level between consecutive ventilations and for estimating the end-tidal CO(2) variation as a function of ventilation rate. CONCLUSION: We have modeled the decrease in exhaled CO(2) 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 ETCO(2) 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. |
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