Contributing factors to surgical site infection after tibial plateau leveling osteotomy: A follow‐up retrospective study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To identify factors associated with surgical site infection (SSI) after tibial plateau leveling osteotomy (TPLO). STUDY DESIGN: Retrospective case series. ANIMALS: Dogs (n = 541) that underwent TPLO (n = 659). METHODS: Medical records of dogs that underwent TPLO from 2011-2018 were reviewed. Data collected included perioperative and postoperative antimicrobial administration, stifle inspection, duration of surgery and anesthesia, comorbidities, and development of SSI including timing, microbiological investigation, and implant removal. Referring veterinarians were contacted for all dogs without a recorded return visit. Risk factors for SSI were assessed by using a multivariable logistic regression model built by using a stepwise approach. RESULTS: Surgical site infection was documented in 71 of 659 (11%) TPLO, with methicillin-resistant Staphylococcus pseudintermedius accounting for 20 of 71 (28%) infections. Protective factors against SSI included administration of postoperative antimicrobials (odds ratio [OR] 0.263; 95% CI = 0.157, 0.442) and timing of preoperative antimicrobial administration. Preoperative antimicrobial timing was protective against SSI when it was administered more than 60 minutes before the first incision compared with administration within 30 minutes (OR 0.275; 95% CI = 0.112, 0.676) or within 60 minutes (OR 0.419; 95% CI = 0.189, 0.929) of the first incision. CONCLUSION: Early administration of perioperative antimicrobials and postoperative antimicrobial administration were protective against SSI after TPLO. CLINICAL SIGNIFICANCE: Antimicrobials can influence the risk of SSI after TPLO. Perioperative and postoperative antimicrobial administration timing should be considered to reduce SSI.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it