Evidence map›Paper›PMID 33816161›Full record

ArticleQuantitative imaging in medicine and surgery2021

Lung regions identified with CT improve the value of global inhomogeneity index measured with electrical impedance tomography.

Lin Yang, Meng Dai, Knut Möller, Inéz Frerichs, Andy Adler, Feng Fu, Zhanqi Zhao

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 25 citations in OpenAlex.

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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

7 authors at 4 institutions in 3 countries.

Lin YangDepartment of Aerospace Medicine, Fourth Military Medical University, Xi'an, China.
Meng DaiDepartment of Biomedical Engineering, Fourth Military Medical University, Xi'an, China.
Knut MöllerInstitute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany.
Inéz FrerichsDepartment of Anaesthesiology and Intensive Care Medicine, University Medical Centre of Schleswig-Holstein Campus Kiel, Germany.
Andy AdlerDepartment of Systems and Computer Engineering, Carleton University, Ottawa, Canada.
Feng FuDepartment of Biomedical Engineering, Fourth Military Medical University, Xi'an, China.
Zhanqi ZhaoDepartment of Biomedical Engineering, Fourth Military Medical University, Xi'an, China.
Air Force Medical University · CNCarleton University · CAFurtwangen University · DEUniversity of Lübeck · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe global inhomogeneity (

methodsEIT measurements were performed at the level of the fifth intercostal space in six patients with acute respiratory distress syndrome. The thorax and lungs were segmented automatically from serial individual CT scans. The anatomically derived lung regions were calculated in EIT images from simulating a homogeneous ventilation distribution in a finite element model. The conventional approach (

resultsAs expected, the conventional

conclusionsThe proposed

Indexed as

acute respiratory distress syndrome (ARDS)CT segmentationelectrical impedance tomographyGlobal inhomogeneity indexventilation heterogeneity

Identifiers

PMID33816161
PMCPMC7930666
OpenAlexW3111298879

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.