Lung lobe torsion in association with a pulmonary papillary carcinoma in a dog
Bibliographic record
Abstract
Lung lobe torsion (LLT) is an uncommon condition in dogs reported to be most commonly idiopathic or secondary to trauma, pleural effusion, lung lobectomy or thoracic neoplasia. Carcinomas are the most common primary lung tumours in dogs, but only a few cases have been reported in association with LLT in veterinary medicine. This case describes an adult male neutered Labrador, which presented with lethargy, weight loss and pleural effusion. Computed tomography (CT), cytology of the lung, thoracocentesis and fluid analysis were performed. CT revealed pleural effusion and torsion of the left cranial lung lobe with no evidence of a pulmonary mass or metastatic disease. Thoracotomy and left cranial lung lobectomy were performed. Intraoperatively there was no macroscopic evidence of pulmonary neoplasia. Histopathology of the lobar tissue confirmed grade 2 pulmonary papillary carcinoma. It is possible that early detection and surgical management might help to prevent the morbidity and mortality associated with LLT. However, as in this case, the underlying cause for the LLT will ultimately determine the patient's prognosis. The final diagnosis of papillary carcinoma in this case, was only made via histopathological assessment of the pulmonary tissue as it was unclear on the advanced imaging and macroscopic intraoperative evaluation of the lungs. This case highlights the importance of considering pulmonary neoplasia as a differential for LLT even in the absence of a macroscopic mass, and therefore the value of performing histopathology on the excised lung tissue.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".