Surgical correction of left auricular aneurysm herniation through a pericardial defect in a dog with atrial fibrillation and mitral valve disease
Bibliographic record
Abstract
Abstract Pericardial defect is a rare condition, with risk of cardiac chamber strangulation or incarceration. Surgical correction is recommended when clinical signs are unmanageable and to decrease the risk of thromboemboli. A 15‐year‐old, 4.1‐kg, spayed female Shih Tzu dog presented to the hospital with a 6‐month history of weakness and syncope episodes. The dog had been diagnosed with degenerative mitral valve disease 9 years earlier. Thoracic radiographs, echocardiography and computed tomography indicated a left auricular herniation through a pericardial defect. Clinical signs were temporarily controlled with pimobendan, benazepril and clopidogrel, until the syncope episodes returned along with atrial fibrillation (unresponsive to oral digoxin). Surgical correction (auriculectomy and partial pericardiectomy) was performed via thoracotomy. Atrial fibrillation reverted to normal sinus rhythm following surgery and recovery was uneventful. The patient survived, arrhythmia‐free, for 25 months postoperatively. Syncope episodes never resolved.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".