Analysis of risk factors associated with complications following mandibulectomy and maxillectomy in dogs
Bibliographic record
Abstract
OBJECTIVE: To provide information about complication rates and the risk factors for complications with mandibulectomy and maxillectomy procedures in dogs. ANIMALS: 459 client-owned dogs that underwent a mandibulectomy or maxillectomy between January 1, 2007, and January 1, 2018. PROCEDURES: Inclusion criteria included a complete medical record that contained an anesthesia record, surgical report, available histopathology results, and results of CBC and serum biochemical analysis before surgery. A minimum follow-up of 90 days after surgery was required. RESULTS: 271 complications occurred in 171 of 459 (37.3%) dogs. Eighteen complications were not given a severity description. Of the remaining 253 complications, most were considered minor (157/253 [62.1%]). Multivariable logistic regression analysis revealed that only increased surgical time had a significant (OR, 1.36; 95% CI, 1.12 to 1.54) association with the occurrence of ≥ 1 complication. For each additional hour of surgery, the odds of complications increased by 36%. Preoperative radiation therapy or chemotherapy increased the odds of incisional dehiscence or oral fistula formation (OR, 3.0; 95% CI, 1.3 to 7.2). Additionally, undergoing maxillectomy, compared with mandibulectomy, increased the odds of incisional dehiscence or oral fistula formation (OR, 1.8; 95% CI, 1.1 to 3.1). Two hundred forty-four of 271 (90.0%) complications occurred in the perioperative period (0 to 3 months after surgery). CONCLUSIONS AND CLINICAL RELEVANCE: Compared with mandibulectomy, performing maxillectomy increased the risk for incisional dehiscence or oral fistula formation. Mandibulectomy and maxillectomy had a moderate risk for a complication.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".