Evidence map›Paper›PMID 35833958›Full record

ReviewIntensive care medicine2022

Imaging the acute respiratory distress syndrome: past, present and future.

Laurent Bitker, Daniel Talmor, Jean-Christophe Richard

Open access · bronzeAbstract readReview
In one paragraph

Review in Intensive care medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
7.8field-weighted citation impact, top 2% 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

32 citing papers in PubMed, 57 citations in OpenAlex.

  1. ARDS management in trauma patients.Intensive care medicine · 2026
    Review
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  13. Observational
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  19. [Artificial intelligence in intensive care medicine].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2024
    Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Laurent BitkerService de Médecine Intensive - Réanimation, Hôpital de la Croix Rousse, Hospices Civils de Lyon, 103 Grande Rue de la Croix Rousse, 69317, Lyon Cedex 04, France. laurent.bitker@chu-lyon.fr.ORCID http://orcid.org/0000-0002-4698-053X
Daniel TalmorDepartment of Anaesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Jean-Christophe RichardService de Médecine Intensive - Réanimation, Hôpital de la Croix Rousse, Hospices Civils de Lyon, 103 Grande Rue de la Croix Rousse, 69317, Lyon Cedex 04, France.
Université Claude Bernard Lyon 1 · FRBeth Israel Deaconess Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In patients with the acute respiratory distress syndrome (ARDS), lung imaging is a fundamental tool in the study of the morphological and mechanistic features of the lungs. Chest computed tomography studies led to major advances in the understanding of ARDS physiology. They allowed the in vivo study of the syndrome's lung features in relation with its impact on respiratory physiology and physiology, but also explored the lungs' response to mechanical ventilation, be it alveolar recruitment or ventilator-induced lung injuries. Coupled with positron emission tomography, morphological findings were put in relation with ventilation, perfusion or acute lung inflammation. Lung imaging has always been central in the care of patients with ARDS, with modern point-of-care tools such as electrical impedance tomography or lung ultrasounds guiding clinical reasoning beyond macro-respiratory mechanics. Finally, artificial intelligence and machine learning now assist imaging post-processing software, which allows real-time analysis of quantitative parameters that describe the syndrome's complexity. This narrative review aims to draw a didactic and comprehensive picture of how modern imaging techniques improved our understanding of the syndrome, and have the potential to help the clinician guide ventilatory treatment and refine patient prognostication.

Indexed as

Respiratory Distress SyndromeVentilator-Induced Lung InjuryArtificial IntelligenceHumansLungRespiration, ArtificialTomography, X-Ray ComputedAcute respiratory distress syndromeComputed tomographyElectrical impedance tomographyLung ultrasoundsPositron emission tomographyVentilator-induced lung injuries

Identifiers

PMID35833958
PMCPMC9281340
OpenAlexW4285388342

What OpenQuestion holds

Textmetadata
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.