Evidence map›Paper›PMID 38620949›Full record

ArticleIFAC-PapersOnLine2021

Detection of Different COVID-19 Pneumonia Phenotypes with Estimated Alveolar Collapse and Overdistention by Bedside Electrical Impedance Tomography.

Rongqing Chen, András Lovas, Balázs Benyó, Knut Möller

Open access · diamondAbstract read
In one paragraph

Article in IFAC-PapersOnLine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 46% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

4 authors at 3 institutions in 2 countries.

Rongqing ChenInstitute of Technical Medicine, Furtwangen University, Jakob-Kienzle-Str. 17, VS-Schwenningen, Germany.
András LovasKiskunhalas Semmelweis Hospital, Department of Anaesthesiology and Intensive Therapy, H-6400, Dr. Monszpart L. u. 1, Hungary.
Balázs BenyóDepartment of Control Engineering and Information Technology, Budapest University of Technology and Economics, 1117 Budapest, Magyar tudósok krt. 2, Hungary.
Knut MöllerInstitute of Technical Medicine, Furtwangen University, Jakob-Kienzle-Str. 17, VS-Schwenningen, Germany.
Furtwangen University · DEBudapest University of Technology and Economics · HUSemmelweis University · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 induced acute respiratory distress syndrome (ARDS) could have two different phenotypes, which was reported to have different response and outcome to the typical ARDS positive end-expiration pressure (PEEP) treatment. The identification of the different phenotypes in terms of the recruitability can help improve the patient outcome. In this contribution we conducted alveolar overdistention and collapse analysis with the long term electrical impedance tomography monitoring data on two severe COVID-19 pneumonia patients. The result showed different patient reactions to the PEEP trial, revealed the progressive change in the patient status, and indicted a possible phenotype transition in one patient. It might suggest that EIT can be a practical tool to identify phenotypes and to provide progressive information of COVID-19 pneumonia.

Indexed as

biomedical imaging systemsclinical variablescontrol of voluntary movementsdecision support systems for the control of physiologicallocomotionrespiration

Identifiers

PMID38620949
PMCPMC8562158
OpenAlexW3210242909

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.