Evidence map›Paper›PMID 31809278›Full record

ArticleCritical care medicine2020

Mechanical Ventilation Redistributes Blood to Poorly Ventilated Areas in Experimental Lung Injury.

John N Cronin, Douglas C Crockett, Andrew D Farmery, Göran Hedenstierna, Anders Larsson, Luigi Camporota, Federico Formenti

Open access · hybridAbstract read
In one paragraph

Article in Critical care medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.1field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 37 citations in OpenAlex.

  1. Observational
  2. Review
  3. Lung aeration, ventilation, and perfusion imaging.Current opinion in critical care · 2022
    Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Bedside monitoring of lung volume available for gas exchange.Intensive care medicine experimental · 2021
    Article
  9. Low PEEP Mechanical Ventilation and PaOSN comprehensive clinical medicine · 2021
    Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

John N CroninCentre for Human and Applied Physiological Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.
Douglas C CrockettNuffield Division of Anaesthetics, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Andrew D FarmeryNuffield Division of Anaesthetics, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Göran HedenstiernaHedenstierna Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
Anders LarssonHedenstierna Laboratory, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Luigi CamporotaCentre for Human and Applied Physiological Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.
Federico FormentiCentre for Human and Applied Physiological Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.
King's College London · GBUniversity of Oxford · GBUppsala University · SE

Funding

Medical Research Council MC_PC_17164Wellcome TrustWellcome Trust HMRXGK00
6 · The paper itself

Abstract

objectivesDetermine the intra-tidal regional gas and blood volume distributions at different levels of atelectasis in experimental lung injury. Test the hypotheses that pulmonary aeration and blood volume matching is reduced during inspiration in the setting of minimal tidal recruitment/derecruitment and that this mismatching is an important determinant of hypoxemia.

designPreclinical study.

settingResearch laboratory. SUBJECTS: Seven anesthetized pigs 28.7 kg (SD, 2.1 kg).

interventionsAll animals received a saline-lavage surfactant depletion lung injury model. Positive end-expiratory pressure was varied between 0 and 20 cm H2O to induce different levels of atelectasis. MEASUREMENTS AND MAIN

resultsDynamic dual-energy CT images of a juxtadiaphragmatic slice were obtained, gas and blood volume fractions within three gravitational regions calculated and normalized to lung tissue mass (normalized gas volume and normalized blood volume, respectively). Ventilatory conditions were grouped based upon the fractional atelectatic mass in expiration (< 20%, 20-40%, and ≥ 40%). Tidal recruitment/derecruitment with fractional atelectatic mass in expiration greater than or equal to 40% was less than 7% of lung mass. In this group, inspiration-related increase in normalized gas volume was greater in the nondependent (818 µL/g [95% CI, 729-908 µL/g]) than the dependent region (149 µL/g [120-178 µL/g]). Normalized blood volume decreased in inspiration in the nondependent region (29 µL/g [12-46 µL/g]) and increased in the dependent region (39 µL/g [30-48 µL/g]). Inspiration-related changes in normalized gas volume and normalized blood volume were negatively correlated in fractional atelectatic mass in expiration greater than or equal to 40% and 20-40% groups (r = 0.56 and 0.40), but not in fractional atelectatic mass in expiration less than 20% group (r = 0.01). Both the increase in normalized blood volume in the dependent region and fractional atelectatic mass in expiration negatively correlated with PaO2/FIO2 ratio (ρ = -0.77 and -0.93, respectively).

conclusionsIn experimental atelectasis with minimal tidal recruitment/derecruitment, mechanical inspiratory breaths redistributed blood volume away from well-ventilated areas, worsening PaO2/FIO2.

Indexed as

AlgorithmsAnimalsDisease Models, AnimalLung InjuryPositive-Pressure RespirationPulmonary AtelectasisPulmonary CirculationRespiration, ArtificialRespiratory MechanicsSwineTidal Volume

Identifiers

PMID31809278
PMCPMC7017942
OpenAlexW2991241499

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.