Evidence map›Paper›PMID 41158153›Full record

ArticleEClinicalMedicine2025

Recommendations for lung ventilation and perfusion assessment with chest electrical impedance tomography in critically ill adult patients: an international evidence-based and expert Delphi consensus study.

Huaiwu He, Zhanqi Zhao, Tobias Becher, Giacomo Bellani, Takeshi Yoshida, Marcelo B P Amato, Yun Long, Inéz Frerichs, REspiratory and Critical Care medicine EIT study (RECCE) group

Registry-linked trialAbstract read
In one paragraph

Article in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07793565 (A Randomized Controlled Trial of Early EIT-Guided PEEP Titration on Pulmonary Physiology in Moderate-to-Severe ARDS Patients Undergoing Prone Positioning), which is not on this map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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.

NCT07793565 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

A Randomized Controlled Trial of Early EIT-Guided PEEP Titration on Pulmonary Physiology in Moderate-to-Severe ARDS Patients Undergoing Prone Positioning

TypeinterventionalSponsorXIE MINRan2026 to 2027Enrolled40ConditionsAcute Respiratory Distress Syndrome (ARDS)ArmsEIT-Guided PEEP Titration Group, ARDSNet/PEEP-FiO₂ Table
3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Observational
  5. Article
  6. Review
  7. Article
  8. Article
  9. Observational
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
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

9 authors.

Huaiwu HeState Key Laboratory of Complex Severe and Rare Diseases, Department of Critical Care Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Zhanqi ZhaoState Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Department of Critical Care Medicine, Guangzhou Medical University, Guangzhou, China.
Tobias BecherDepartment of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany.
Giacomo BellaniCentre for Medical Sciences - CISMed, University of Trento, Trento, Italy.
Takeshi YoshidaDepartment of Anesthesiology and Intensive Care Medicine, Osaka University Graduate School of Medicine, Suita, Japan.
Marcelo B P AmatoDivisao de Pneumologia, Instituto do Coracao, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, SP, Brazil.
Yun LongState Key Laboratory of Complex Severe and Rare Diseases, Department of Critical Care Medicine, 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 Schleswig-Holstein, Campus Kiel, Kiel, Germany.
REspiratory and Critical Care medicine EIT study (RECCE) group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electrical impedance tomography (EIT) is a non-invasive, radiation-free imaging technique that allows for monitoring of lung ventilation and perfusion at the bedside. However, there is a lack of evidence-based and international expert consensus statement of EIT clinical applications in adult critically ill patients. The purpose of this study was to provide evidence-based and expert consensus recommendations for lung ventilation and perfusion assessment with chest EIT in adult critically ill patients. Methods: A English literature search was conducted of MEDLINE, EMBASE, Web of Science and Cochrane Library databases between January 1, 1990, and J March 22, 2024. Eligible literature included systematic reviews, meta-analyses, cohort/clinical trials, case reports and review articles that focused on chest EIT application for lung ventilation and perfusion in adult population. The animal studies were excluded. An international global panel of intensivists, physicians, biomedical engineers with expertise in the field of EIT clinical applications, guideline methodologists and biostatisticians, was convened. The Oxford Centre of Evidence Based Medicine's Levels of Evidence method was used to rate the quality of evidence and the strength of recommendations. Subsequently, with a Delphi process (two online surveys at June 3 and September 13, 2024), a group of expanded global experts from 12 different countries developed recommendations. We defined a strong consensus as agreement of >95% experts, consensus as agreement of 75-95% experts and no consensus as agreement<75%. The study is registered with PREPARE, PREPARE-2024CN166. Findings: The final 14 questions generated a total of 11,159 abstracts, of which 242 publications were identified relevant to develop 87 recommendations. The 87 statements focused on data acquisition and analysis, clinical application, and future perspectives were developed and modified. Twenty experts in the expanded group completed the survey in the first round, and eighteen experts in the expanded group completed the survey in the second round. At the end of the Delphi process, 15 recommendations were identified as strong consensus, 70 recommendations as consensus, and two recommendations did not reach consensus. The statements with strong consensus were focused on data acquisition, analysis, training and interpretation, assessment of posture effect on lung ventilation, lung perfusion and ventilation/perfusion match, and the statements without agreement were focused on regional ventilation delay ratio, perfusion assessment with heart-beat related EIT signal. Recommendations were mostly based on moderate quality of evidence (3/87 was A grade, 47/87 was B grade, 37/87 was C-D grade of recommendation). Interpretation: Our study provides evidence-based recommendations with high consensus for using chest EIT for lung ventilation and perfusion in adult critically ill patients. Evidence and expert consensus supports the application of EIT in the detection of dynamic pulmonary abnormalities and inhomogeneities, which may significantly influence clinical management and final diagnosis. High quality evidence is urgently needed for the development of EIT guidelines in the future. Funding: National High-Level Hospital Clinical Research Funding, National Key Research and Development Program, National Natural Science Foundation of China, Peking Union Medical College Hospital Talent Cultivation Program Category C.

Indexed as

Chest electrical impedance tomographyCritically ill patientEvidence-basedLung perfusionLung ventilation

Identifiers

PMID41158153
PMCPMC12555788

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.