Veterinary‐focused assessment with sonography for trauma‐airway, breathing, circulation, disability and exposure: a prospective observational study in 64 canine trauma patients
Bibliographic record
Abstract
OBJECTIVE: To describe the technique and findings of the 'veterinary focused assessment with sonography for trauma-airway, breathing, circulation, disability and exposure' protocol in dogs suffering from trauma. MATERIALS AND METHODS: Prospective observational study on a new point-of-care ultrasound protocol on 64 dogs suffering from trauma and comparison of findings with radiology. RESULTS: Comparison of the results of this new ultrasound protocol for trauma patients with radiography findings for pneumothorax, pleural effusion, alveolar-interstitial syndrome and abdominal effusion revealed positive agreement of 89, 83, 100 and 87% and negative agreement of 76, 83, 76 and 92%, respectively. Novel findings of the 'veterinary focused assessment with sonography for trauma-airway, breathing, circulation, disability and exposure' exam, which were not previously reported for dogs undergoing focused assessment with sonography for trauma, included alveolar-interstitial syndrome (suggestive of pulmonary contusions), diaphragmatic hernia, retroperitoneal effusion and tracheal injury. Our new technique may also help identify increased intracranial pressure via changes in optic nerve sheath diameter and haemodynamic instability through the evaluation of the caudal vena cava and cardiac function. CLINICAL SIGNIFICANCE: The described ultrasound examination protocol can be rapidly performed on dogs suffering from trauma during resuscitation and it may detect injuries previously undetectable using other veterinary point-of-care ultrasound protocols.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".