Detection of pulmonary oedema by electrical impedance tomography: validation of previously proposed approaches in a clinical setting
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to evaluate two previously proposed approaches based on electrical impedance tomography (EIT) to assess pulmonary oedema at the bedside. APPROACH: Fourteen patients with acute respiratory distress syndrome were included and examined prospectively. Patients were rotated laterally along their longitudinal axis from supine to 45-degree left and right tilt to induce a gravity-dependent redistribution of pulmonary oedema. After a 20 min equilibration period at each of the three positions, 2 min EIT data were recorded and analyzed. Left-to-right lung and anterior-to-posterior ventilation ratios were calculated for each posture. The slopes of the regression lines in all three postures were then determined. The same examination was performed on the consecutive day. The EIT-derived parameters were compared with transcardiopulmonary thermodilution measurements. MAIN RESULTS: The correlations between the EIT and transcardiopulmonary thermodilution parameters were low (correlation coefficients r < 0.4) and not significant regardless of the examination days. SIGNIFICANCE: Despite previous clinical and experimental observations, left-to-right and anterior-to-posterior ventilation ratios derived from EIT examinations after postural changes did not reflect total extravascular lung water in our study population. CLINICAL TRIAL REGISTRATION: NCT02870894 Registered 17 AUG 2016 (https://clinicaltrials.gov).
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".