Evidence map›Paper›PMID 35665323›Full record

ArticleFrontiers in medicine2022

Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography.

András Lovas, Rongqing Chen, Tamás Molnár, Balázs Benyó, Ákos Szlávecz, Fatime Hawchar, Sabine Krüger-Ziolek, Knut Möller

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04360837 (PEEP Incremental and Decremental Alveolar Recruitment of Critically Ill COVID-19 Patients Under Electric Impedance Tomography), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 34% 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.

NCT04360837 nacompletednot on this map

PEEP Incremental and Decremental Alveolar Recruitment of Critically Ill COVID-19 Patients Under Electric Impedance Tomography (EIT)

TypeinterventionalSponsorSzeged UniversityRan2020 to 2020Enrolled2ConditionsCOVID-19, Virus, Pneumonia, AtelectasisArmsalveolar recruitment
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Observational
  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

8 authors at 4 institutions in 2 countries.

András LovasDepartment of Anesthesiology and Intensive Therapy, Kiskunhalas Semmelweis Hospital, Kiskunhalas, Hungary.
Rongqing ChenInstitute of Technical Medicine, Furtwangen University, VS-Schwenningen, Germany.
Tamás MolnárDepartment of Anesthesiology and Intensive Therapy, University of Szeged, Szeged, Hungary.
Balázs BenyóDepartment of Control Engineering and Information Technology, Budapest University of Technology and Economics, Budapest, Hungary.
Ákos SzláveczDepartment of Control Engineering and Information Technology, Budapest University of Technology and Economics, Budapest, Hungary.
Fatime HawcharDepartment of Anesthesiology and Intensive Therapy, University of Szeged, Szeged, Hungary.
Sabine Krüger-ZiolekInstitute of Technical Medicine, Furtwangen University, VS-Schwenningen, Germany.
Knut MöllerInstitute of Technical Medicine, Furtwangen University, VS-Schwenningen, Germany.
Furtwangen University · DEBudapest University of Technology and Economics · HUUniversity of Szeged · HUSemmelweis University · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Coronavirus disease-2019 (COVID-19) pneumonia has different phenotypes. Selecting the patient individualized and optimal respirator settings for the ventilated patient is a challenging process. Electric impedance tomography (EIT) is a real-time, radiation-free functional imaging technique that can aid clinicians in differentiating the "low" (L-) and "high" (H-) phenotypes of COVID-19 pneumonia described previously. Methods: Two patients ("A" and "B") underwent a stepwise positive end-expiratory pressure (PEEP) recruitment by 3 cmH Results: Patients "A" and "B" had a 7- and 12-day long trial, respectively. At the daily baseline, patient "A" had significantly higher compliance: mean ± Conclusion: Patient "B" was recognized as H-phenotype with high elastance, low compliance, higher recruitability, and low ventilation-to-perfusion ratio; meanwhile patient "A" was identified as the L-phenotype with low elastance, high compliance, and lower recruitability. Observation by EIT was not just able to differentiate the two phenotypes, but it also could follow the transition from L- to H-type within patient "A." Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT04360837.

Indexed as

acute lung injurycomplianceCoronavirus-COVID-19electric impedance tomographyrecruitment maneuver

Identifiers

PMID35665323
PMCPMC9161711
OpenAlexW4280587031

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.