EXpert consensus On Diaphragm UltraSonography in the critically ill (EXODUS): a Delphi consensus statement on the measurement of diaphragm ultrasound-derived parameters in a critical care setting
Bibliographic record
Abstract
BACKGROUND: Diaphragm ultrasonography is rapidly evolving in both critical care and research. Nevertheless, methodologically robust guidelines on its methodology and acquiring expertise do not, or only partially, exist. Therefore, we set out to provide consensus-based statements towards a universal measurement protocol for diaphragm ultrasonography and establish key areas for research. METHODS: To formulate a robust expert consensus statement, between November 2020 and May 2021, a two-round, anonymous and online survey-based Delphi study among experts in the field was performed. Based on the literature review, the following domains were chosen: "Anatomy and physiology", "Transducer Settings", "Ventilator Impact", "Learning and expertise", "Daily practice" and "Future directions". Agreement of ≥ 68% (≥ 10 panelists) was needed to reach consensus on a question. RESULTS: Of 18 panelists invited, 14 agreed to participate in the survey. After two rounds, the survey included 117 questions of which 42 questions were designed to collect arguments and opinions and 75 questions aimed at reaching consensus. Of these, 46 (61%) consensus was reached. In both rounds, the response rate was 100%. Among others, there was agreement on measuring thickness between the pleura and peritoneum, using > 10% decrease in thickness as cut-off for atrophy and using 40 examinations as minimum training to use diaphragm ultrasonography in clinical practice. In addition, key areas for research were established. CONCLUSION: This expert consensus statement presents the first set of consensus-based statements on diaphragm ultrasonography methodology. They serve to ensure high-quality and homogenous measurements in daily clinical practice and in research. In addition, important gaps in current knowledge and thereby key areas for research are established. Trial registration The study was pre-registered on the Open Science Framework with registration digital object identifier https://doi.org/10.17605/OSF.IO/HM8UG .
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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 | 0.337 | 0.256 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".