Evidence map›Paper›PMID 42866601›Full record

ReviewJournal of inflammation research2026

Electrical Impedance Tomography-Informed Regional Functional Phenotypes in Sepsis-Associated Acute Respiratory Distress Syndrome.

Hangbo Hu, Jin Qian, Hongsheng Deng, Kun Chen, Xinyong Liu

Abstract readReview
In one paragraph

Review in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Hangbo HuDepartment of Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China.
Jin QianDepartment of Nursing, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China.
Hongsheng DengDepartment of Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China.ORCID 0000-0003-1325-5160
Kun ChenDepartment of Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China.
Xinyong LiuDepartment of Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People's Republic of China.ORCID 0000-0001-9524-1998

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis-associated acute respiratory distress syndrome (SA-ARDS) is a heterogeneous syndrome in which systemic inflammation, vascular dysfunction, altered fluid balance, chest-wall loading, and respiratory effort may produce regional abnormalities not captured by global respiratory variables. Electrical impedance tomography (EIT) provides continuous bedside assessment of regional ventilation and, increasingly, regional perfusion. This review summarizes EIT-derived measures relevant to SA-ARDS and examines how key sepsis-associated mechanisms may influence regional ventilation, perfusion, and mechanics. Six candidate functional patterns are proposed: collapse-shunt dominance, overdistension-dead-space dominance, perfusion-defect dominance, diffuse low aeration with limited recruitability, abdominal pressure-diaphragm interaction, and effort-related regional asynchrony. These patterns are neither mutually exclusive nor specific to SA-ARDS and may evolve over time.

Indexed as

electrical impedance tomographyfunctional phenotypingregional perfusionregional ventilationsepsis-associated acute respiratory distress syndromeventilation-perfusion mismatch

Identifiers

PMID42866601
PMCPMC13657080

What OpenQuestion holds

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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.