Evidence map›Paper›PMID 41882477›Full record

ReviewIntensive care medicine experimental2026

Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography.

Roberta Garberi, Matthieu Jabaudon, Sam Bayat, Sarah E Gerard, Aurora Magliocca, Mariangela Pellegrini, Alberto Bravin, Lorraine B Ware, John J Marini, Yi Xin and 3 more

Abstract readReview
In one paragraph

Review in Intensive care medicine experimental, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. ARDS management in trauma patients.Intensive care medicine · 2026
    Review
  2. Review
  3. Article
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

13 authors.

Roberta GarberiSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.ORCID http://orcid.org/0009-0006-6137-8295
Matthieu JabaudonDepartment of Perioperative Medicine, CHU Clermont-Ferrand and iGReD, CNRS, INSERM, Université Clermont Auvergne, Clermont-Ferrand, France.ORCID http://orcid.org/0000-0002-8121-1680
Sam BayatDepartment of Pulmonology & Physiology, Grenoble University Hospital, Grenoble, France.ORCID http://orcid.org/0000-0002-8565-0293
Sarah E GerardRoy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, USA.ORCID http://orcid.org/0000-0001-8101-3150
Aurora MaglioccaDepartment of Pathophysiology and Transplantation, University of Milan, Milan, Italy.ORCID http://orcid.org/0000-0002-3908-3857
Mariangela PellegriniIntensive Care Unit, Department of Anaesthesia, Operation and Intensive Care, Uppsala University Hospital, Uppsala, Sweden.ORCID http://orcid.org/0000-0001-5668-7399
Alberto BravinDipartimento Di Fisica, Università Degli Studi Di Milano-Bicocca, Milan, Italy.ORCID http://orcid.org/0000-0001-6868-2755
Lorraine B WareDepartment of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID http://orcid.org/0000-0002-9429-4702
John J MariniDivision of Pulmonary and Critical Care Medicine, Regions Hospital, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0002-9851-2076
Yi XinAnesthesia Center for Critical Care Research, Department of Anesthesiology, Critical Care and Pain Medicine, Mass General Brigham and Harvard Medical School, Boston, MA, USA.
John G LaffeyRegenerative Medicine Institute at CÚRAM Centre for Research in Medical Devices, Biomedical Sciences Building, and Discipline of Anaesthesia, School of Medicine, National University of Ireland Galway, Galway, Ireland.ORCID http://orcid.org/0000-0002-1246-9573
Maurizio CeredaAnesthesia Center for Critical Care Research, Department of Anesthesiology, Critical Care and Pain Medicine, Mass General Brigham and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-2435-7413
Emanuele RezoagliSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy. emanuele.rezoagli@unimib.it.ORCID http://orcid.org/0000-0002-4506-7212

Funding

University of Milano-Bicocca Institutional funds
6 · The paper itself

Abstract

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome rather than a single disease. Patients who meet the same diagnostic criteria may differ in lung morphology, mechanical properties, biological injury, and clinical course. Current classifications rely largely on the severity of hypoxemia and do not capture this variability, limiting prognostic stratification and individualized treatment. This heterogeneity has clinical consequences. Supportive interventions such as positive end-expiratory pressure (PEEP), prone positioning, and recruitment maneuvers are broadly applied, yet their effects vary substantially among patients. Increasing evidence indicates that these differences are partly explained by variation in lung structure, regional aeration, recruitability, and perfusion. Recent international guidelines have identified phenotyping as a priority in ARDS and have highlighted lung morphology as a relevant source of prognostic enrichment and treatment effect heterogeneity. Computed tomography (CT) provides regional, three-dimensional information on lung injury that is not accessible through bedside physiological measurements. It allows evaluation of aeration loss, lung density, lung weight, and perfusion abnormalities. CT has been used to describe key aspects of lung injury in ARDS and to identify imaging patterns associated with lung mechanics, gas exchange, and response to ventilatory settings. Quantitative and dual-energy CT, together with computational methods, allow a more detailed description of these patterns. This review examines the role of CT in characterizing heterogeneity in ARDS, summarizes qualitative, semi-quantitative, and quantitative approaches, and discusses their clinical relevance and limitations, as well as future directions.

Indexed as

Acute respiratory distress syndrome (ARDS)Artificial Intelligence (AI)CT-based subphenotypingQuantitative computed tomography (qCT)Ventilation–perfusion mismatch

Identifiers

PMID41882477
PMCPMC13018537

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.