Electrical impedance tomography monitoring in adult ICU patients: state-of-the-art, recommendations for standardized acquisition, processing, and clinical use, and future directions
Bibliographic record
Abstract
Abstract Electrical impedance tomography (EIT) is an emerging technology for the non-invasive monitoring of regional distribution of ventilation and perfusion, offering real-time and continuous data that can greatly enhance our understanding and management of various respiratory conditions and lung perfusion. Its application may be especially beneficial for critically ill mechanically ventilated patients. Despite its potential, clear evidence of clinical benefits is still lacking, in part due to a lack of standardization and transparent reporting, which is essential for ensuring reproducible research and enhancing the use of EIT for personalized mechanical ventilation. This report is the result of a four-day expert meeting where we aimed to promote the consistent and reliable use of EIT, facilitating its integration into both clinical practice and research, focusing on the adult intensive care patient. We discuss the state-of-the-art regarding EIT acquisition and processing, applications during controlled ventilation and spontaneous breathing, ventilation-perfusion assessment, and novel future directions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".