Comparison of electrical impedance tomography and spirometry-based measures of airflow in healthy adult horses
Bibliographic record
Abstract
Electrical impedance tomography (EIT) is a non-invasive diagnostic tool for evaluating lung function. The objective of this study was to compare respiratory flow variables calculated from thoracic EIT measurements with corresponding spirometry variables. Ten healthy research horses were sedated and instrumented with spirometry via facemask and a single-plane EIT electrode belt around the thorax. Horses were exposed to sequentially increasing volumes of apparatus dead space between 1,000 and 8,500 mL, in 5–7 steps, to induce carbon dioxide rebreathing, until clinical hyperpnea or a tidal volume of 150% baseline was reached. A 2-min stabilization period followed by 2 minutes of data collection occurred at each timepoint. Peak inspiratory and expiratory flow, inspiratory and expiratory time, and expiratory nadir flow, defined as the lowest expiratory flow between the deceleration of flow of the first passive phase of expiration and the acceleration of flow of the second active phase of expiration were evaluated with EIT and spirometry. Breathing pattern was assessed based on the total impedance curve. Bland-Altman analysis was used to evaluate the agreement where perfect agreement was indicated by a ratio of EIT:spirometry of 1.0. The mean ratio (bias; expressed as a percentage difference from perfect agreement) and the 95% confidence interval of the bias are reported. There was good agreement between EIT-derived and spirometry-derived peak inspiratory [−15% (−46–32)] and expiratory [10% (−32–20)] flows and inspiratory [−6% (−25–18)] and expiratory [5% (−9–20)] times. Agreement for nadir flows was poor [−22% (−87–369)]. Sedated horses intermittently exhibited Cheyne-Stokes variant respiration, and a breath pattern with incomplete expiration in between breaths (crown-likebreaths). Electrical impedance tomography can quantify airflow changes over increasing tidal volumes and changing breathing pattern when compared with spirometry in standing sedated horses.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".