Risk factors for postoperative complications following bilateral closed anal sacculectomy in the dog
Bibliographic record
Abstract
OBJECTIVES: To report the complication rate for bilateral closed anal sacculectomy in the dog and to evaluate potential risk factors for the development of postoperative complications. To identify breed groups at risk of requiring anal sacculectomy. METHODS: A retrospective review of medical records of dogs undergoing bilateral closed anal sacculectomy between 2003 and 2013. RESULTS: Sixty-two dogs were included in the study of which 32·3% developed mild and self-limiting complications including 14·5% dogs that experienced postoperative defaecatory complications. No dog developed permanent faecal incontinence. Dogs less than 15 kg bodyweight were more likely to develop postoperative complications. Dogs that used gel to distend the anal sac were more likely to have postoperative complications than those that did not. Previous abscess formation, recurrent disease and pretreatment with antibiotics had no significant effect on postoperative complication rates. Cavalier King Charles spaniels and Labrador-type dogs were over-represented within this study population. CLINICAL SIGNIFICANCE: Anal sacculectomy is a safe procedure with a relatively high rate of short-term but self-limiting, minor, postoperative complications. Smaller (<15 kg) dogs are more likely to experience postoperative complications but the risk of permanent faecal incontinence is low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".