Long-term outcome and quality of life of dogs that developed neurologic signs after surgical treatment of a congenital portosystemic shunt: 50 cases (2005–2020)
Bibliographic record
Abstract
OBJECTIVE: To determine survival time and quality of life of dogs that developed postattenuation neurologic signs (PANS) after surgical treatment of a single congenital portosystemic shunt and survived at least 30 days and identify whether neurologic signs present at the time of discharge would resolve or reoccur. ANIMALS: 50 client-owned dogs. PROCEDURES: Medical records were retrospectively reviewed, and follow-up data relating to neurologic signs and seizure activity were obtained. Owners were asked to complete a questionnaire related to the presence of neurologic signs, including seizures, and their dog's quality of life. RESULTS: Thirty of the 50 (60%) dogs had postattenuation seizures with or without other nonseizure neurologic signs, and 20 (40%) had neurologic signs other than seizures. Neurologic signs had fully resolved by the time of discharge in 24 (48%) dogs. Signs resolved in 18 of the remaining 26 (69%) dogs that still had PANS other than seizures at the time of discharge. Seizures reoccurred in 15 of the 30 dogs that had postattenuation seizures. Twenty-seven of 33 (82%) owners graded their dog's long-term (> 30 days after surgery) quality-of-life as high. Forty-five (90%) dogs survived > 6 months. Most (29/43 [67%]) neurologic signs (other than seizures) present at the time of hospital discharge resolved. CLINICAL RELEVANCE: Findings highlighted that survival times of > 6 months and a high QOL can be achieved in most dogs with PANS that survive at least 30 days. Most neurologic signs other than seizures resolved within 1 month postoperatively. Half of the dogs with postattenuation seizures had a reoccurrence.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".