Evidence map›Paper›PMID 32023298›Full record

ArticlePloS one2020

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

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

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
  2. [Adult advanced life support].Notfall & rettungsmedizin · 2021
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Jose Julio GutiérrezDepartment of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao, Bizkaia, Spain.
Jesus María RuizDepartment of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao, Bizkaia, Spain.
Sofía Ruiz de GaunaDepartment of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao, Bizkaia, Spain.ORCID 0000-0002-0414-0946
Digna María González-OteroDepartment of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao, Bizkaia, Spain.
Mikel LeturiondoDepartment of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao, Bizkaia, Spain.
James Knox RussellDepartment of Emergency Medicine, Oregon Health & Science University (OHSU), Portland, Oregon, United States of America.
Carlos CorcueraEmergentziak-Osakidetza, Basque Country Health System, Basque Country, Spain.
Juan Francisco UrtusagastiEmergentziak-Osakidetza, Basque Country Health System, Basque Country, Spain.
Mohamud Ramzan DayaDepartment of Emergency Medicine, Oregon Health & Science University (OHSU), Portland, Oregon, United States of America.
University of the Basque Country · ESOregon Health & Science University · USOsakidetza · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimCurrent 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.

methodsWe 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.

resultsOut 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 CO2 concentration was 10.0% (7.8 - 12.9) with R2 = 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.

conclusionWe 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.

Indexed as

Models, TheoreticalMonitoring, PhysiologicAlgorithmsCapnographyCarbon DioxideCardiography, ImpedanceCardiopulmonary ResuscitationExhalationHumansOut-of-Hospital Cardiac ArrestRespiratory RateRetrospective StudiesVentilationCarbon Dioxide

Identifiers

PMID32023298
PMCPMC7001922
OpenAlexW3005381516

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.