Evaluation of B‐lines with 2 point‐of‐care lung ultrasound protocols in cats with radiographically normal lungs
Bibliographic record
Abstract
OBJECTIVE: To compare 2 point-of-care lung ultrasound (LUS) protocols for quantification of B-lines in cats without evidence of respiratory disease based on history, physical examination, and thoracic radiography. DESIGN: Prospective observational study. SETTING: Single center, veterinary teaching hospital. ANIMALS: Fifty-seven cats without respiratory disease based on history, physical examination, and thoracic radiographs. INTERVENTIONS: All cats had 2 point-of-care LUS protocols performed bilaterally: a regional protocol (veterinary bedside lung ultrasound evaluation [VetBLUE]) and a more comprehensive vertical sweeping (VS) protocol. The total number of B-lines per cat, number of sites with B-lines, and maximal number of B-lines at each site were recorded and compared. MEASUREMENTS AND MAIN RESULTS: Ten cats (18%) had at least 1 B-line identified with VetBLUE, versus 29 (51%) with VS. Comparing protocols, VS had a statistically higher total number of B-lines per cat, higher number of sites with B-lines, and higher maximal number of B-lines per site. B-lines that were too numerous to count were identified at a single location in 1 cat with VetBLUE and 2 cats with VS. A maximum of 3 B-lines were identified at all other positive sites regardless of the protocol used. On average, it took 1.79 times longer to complete VS bilaterally compared to VetBLUE (median [interquartile range]: 140 [33] and 78 [14] s, respectively) (P = 0.001). CONCLUSIONS: This study demonstrates it is not uncommon to identify a single or even multiple B-lines in 1 or several sites on LUS in cats deemed to be clinically free of respiratory pathology-essential knowledge when using LUS as a screening test and to monitor intrathoracic lesions. In cats asymptomatic for respiratory disease, VS generally identifies more B-lines than VetBLUE, likely because it assesses a larger lung surface area. The sonographic identification of B-lines should be interpreted considering the LUS protocol used, history, and other diagnostics to determine their clinical significance.
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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 | 0.015 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".