Perioperative Administration of Antimicrobials During Tibial Plateau Leveling Osteotomy
Bibliographic record
Abstract
OBJECTIVE: To evaluate perioperative antimicrobial administration during tibial plateau leveling osteotomy (TPLO) in dogs at the Ontario Veterinary College Health Sciences Centre. STUDY DESIGN: Retrospective case series. ANIMALS: Dogs (n = 184) that had TPLO (n = 226). METHODS: Medical records were reviewed and data collected included timing and dosage of pre, intra, and postoperative antimicrobial administration, method of stifle inspection, duration of surgery, duration of anesthesia, development of surgical site infection (SSI), microbiological investigation, implant removal, and possible comorbidities. Univariable analysis was conducted, followed by stepwise forward logistic regression to determine factors associated with SSI. RESULTS: Of the 225 cases administered perioperative antimicrobials, 96 (42.5%) received appropriate perioperative antimicrobial prophylaxis based on target times for preoperative and intraoperative dosing. Postoperative antimicrobials were administered to 54 (23.9%) of cases. Surgical site infection was documented in 30 (13.3%) cases. Staphylococcus pseudintermedius was isolated from 15/17 (88.2%) SSI from which a bacterium was isolated, with 6/15 (40%) being methicillin-resistant Staphylococcus pseudintermedius (MRSP). Postoperative administration of antimicrobials was protective for SSI (OR 0.1367; P = .0001; 95% CI = 0.021, 0.50). Duration of anesthesia time was associated with the likelihood of development of SSI (OR = 1.0094; P = .001; 95% CI = 1.00, 1.02). CONCLUSION: Current practices for administration of antimicrobial prophylaxis during TPLO can be improved. There was no association between timing of antibiotic administration that was inconsistent with the target and development of SSI. Further study into risk factors of TPLO SSI is required.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".