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.
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.
What it found
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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.
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.
A Randomized Controlled Trial of Early EIT-Guided PEEP Titration on Pulmonary Physiology in Moderate-to-Severe ARDS Patients Undergoing Prone Positioning
Who cites it
19 citing papers in PubMed.
- Visual feedback using electrical impedance tomography during inhalation therapy for chronic obstructive lung disease: a pilot study.Scientific reports · 2026Trial
- Lung perfusion estimation by saline-contrast EIT without breath hold: a randomized cross-over trial.Critical care (London, England) · 2026Trial
- Pulsation is not perfusion: methodological concerns in EIT-based pulmonary embolism diagnosis.Critical care (London, England) · 2026Article
- Safety and Feasibility of Bedside Electrical Impedance Tomography With Hypertonic Saline Contrast for Assessing Pulmonary Perfusion in Mechanically Ventilated Children With Acute Respiratory Distress Syndrome: A Pilot Study.Critical care explorations · 2026Observational
- From physiological innovation to clinical precision: defining the right target for diaphragm neurostimulation.Journal of thoracic disease · 2026Article
- Clinical applications of electrical impedance tomography in pediatric subjects.Pediatric research · 2026Review
- Frequency-domain band-pass filtering enhanced pulsation method for pulmonary embolism diagnosis and risk stratification: a two-center retrospective study.Critical care (London, England) · 2026Article
- Interpreting wasted ventilation in EIT assessment of pulmonary embolism: ventilation-weighted high-V/Q burden versus perfusion-defect burden.Critical care (London, England) · 2026Article
- Electrical impedance tomography-derived flow index during spontaneous breathing trial stratifies the risk of reintubation within 48 h after extubation.Critical care (London, England) · 2026Observational
- Thoracic electrical impedance tomography from technological promise to clinical reality: the Chinese experience.Journal of thoracic disease · 2026Review
- Setting PEEP in patients with COVID-19-related ARDS: a physiological comparison between methods.Intensive care medicine experimental · 2026Article
- EIT-guided end-expiratory pressure individualization in robotic surgery with high PEEP ventilation: a prospective observational study.BMC anesthesiology · 2026Article
- Ventilation/perfusion mismatch measured by electrical impedance tomography at the bedside: potentialities and challenges.Intensive care medicine · 2026Review
- Diagnostic accuracy and cost-efficiency of ChatGPT in EIT-based pendelluft detection for mechanically ventilated patients: a multicenter study.Respiratory research · 2026Article
- Effects of two ventilator-weaning methods on lung volume and ventilation distribution by electrical impedance tomography in post-cardiac surgery patients: a prospective cohort study.Journal of intensive care · 2026Article
- EIT-based ventilation phenotypes of left-to-right asymmetry and ventral-to-dorsal center in PEEP titration in ARDS.Respiratory research · 2026Article
- A Novel Mixed Stimulation Pattern for Balanced Pulmonary EIT Imaging Performance.Bioengineering (Basel, Switzerland) · 2026Article
- Personalized positive-end expiratory pressure using electrical impedance tomography in ARDS patients: a systematic review and meta-analysis.Annals of intensive care · 2026Review
- Bedside detection and monitoring of pulmonary embolism using electrical impedance tomography.Frontiers in physiology · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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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.