Evidence map›Paper›PMID 34453622›Full record

ArticleAnnals of intensive care2021

Three broad classifications of acute respiratory failure etiologies based on regional ventilation and perfusion by electrical impedance tomography: a hypothesis-generating study.

Huaiwu He, Yi Chi, Yun Long, Siyi Yuan, Rui Zhang, Yingying Yang, Inéz Frerichs, Knut Möller, Feng Fu, Zhanqi Zhao

2 registry-linked trialsOpen access · goldAbstract read
In one paragraph

Article in Annals of intensive care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
5.7field-weighted citation impact, top 3% 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.

NCT04081142 completednot on this map

Application of Indicator Based-EIT Method Assess Lung Regional Perfusion for Critically Ill Patients in ICU

TypeobservationalSponsorYun LongRan2018 to 2020Enrolled119ConditionsRespiratory Failure, Hypoxemia, ARDS, Human
NCT05781802 unknown statusnot on this mapstarted 2023, after this paper: background citation

Assessment of V/Q Matching During Pressure Support Ventilation With Electrical Impedance Tomography

TypeobservationalSponsorAzienda Ospedaliera Universitaria Policlinico Paolo Giaccone PalermoRan2023 to 2024Enrolled15ConditionsAcute Respiratory Failure, ARDS, Electrical Impedance TomographyArmsLevel of pressure support
3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 59 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

10 authors at 3 institutions in 2 countries.

Huaiwu HeDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Yi ChiDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Yun LongDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China. iculong_yun@163.com.ORCID http://orcid.org/0000-0002-9196-4651
Siyi YuanDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Rui ZhangDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Yingying YangDepartment of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Inéz FrerichsDepartment of Anesthesiology and Intensive Care Medicine, University Medical Center of Schleswig-Holstein Campus Kiel, Kiel, Germany.
Knut MöllerInstitute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany.
Feng FuDepartment of Biomedical Engineering, Fourth Military Medical University, 169 Changle Xi Rd, Xi'an, China.
Zhanqi ZhaoInstitute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany. zhanqi.zhao@hs-furtwangen.de.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNFurtwangen University · DEAir Force Medical University · CN

Funding

CAMS Innovation Fund for Medical Sciences(NO. CAMS Innovation Fund for Medical Sciences 2020-I2M-C&T-B-042
6 · The paper itself

Abstract

backgroundThe aim of this study was to validate whether regional ventilation and perfusion data measured by electrical impedance tomography (EIT) with saline bolus could discriminate three broad acute respiratory failure (ARF) etiologies.

methodsPerfusion image was generated from EIT-based impedance-time curves caused by 10 ml 10% NaCl injection during a respiratory hold. Ventilation image was captured before the breath holding period under regular mechanical ventilation. DeadSpace

resultsA total of 108 ICU patients were prospectively included: 93 with ARF and 15 without as a control. PaO

conclusionsOur study showed that it was feasible to characterize three broad etiologies of ARF with EIT-based regional ventilation and perfusion. Further study is required to validate clinical applicability of this method. Trial registration clinicaltrials, NCT04081142. Registered 9 September 2019-retrospectively registered, https://clinicaltrials.gov/show/NCT04081142 .

Indexed as

Acute respiratory failureElectrical impedance tomographyLung perfusionLung ventilationV/Q

Identifiers

PMID34453622
PMCPMC8401348
OpenAlexW3195258822

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.