Open heart closure of an atrial septal defect by use of an atrial septal occluder in a dog
Bibliographic record
Abstract
CASE DESCRIPTION: A 3-year-old sexually intact male Standard Poodle was admitted to the veterinary teaching hospital for transcatheter closure of a large atrial septal defect (ASD). CLINICAL FINDINGS: The dog had exercise intolerance and was thin. Findings on physical examination were within normal limits with the exception of a left base systolic heart murmur (grade 5/6). The dog was not receiving any medications. Echocardiography and thoracic radiography confirmed the diagnosis of ASD and revealed compensatory changes consistent with a large left to right shunting ASD. Results of serum biochemical analysis and CBC were within reference range limits. TREATMENT AND OUTCOME: Transcatheter ASD closure with an atrial septal occluder (ASO) was performed and failed. An open heart surgical approach under cardiopulmonary bypass was declined by the dog's owners. The dog underwent a novel hybrid approach involving active device fixation under temporary inflow occlusion after transatrial device deployment. The dog recovered with some manageable postoperative complications. As of the last follow-up examination, the dog had 10 months of event-free survival. CLINICAL RELEVANCE: Transcatheter closure by use of an ASO and open heart patch repair with cardiopulmonary bypass to surgically treat dogs with ASD has been reported. Transcatheter closure is not possible in dogs with large ASD. The novel hybrid procedure reported herein represented a viable alternative to euthanasia.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 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".