Evaluation of conjunctival graft procedures and factors that lead to graft complications in canine cases
Bibliographic record
Abstract
PURPOSE: To describe the complications of conjunctival graft surgery occurring in cases at a referral ophthalmic service and evaluate factors that lead to occurrence of complications in canine cases. METHODS: A retrospective case-control study was completed using data from the Veterinary Medical Center at the Western College of Veterinary Medicine, Saskatoon, Canada, between May 2015 and March 2020. Case records from dogs that underwent conjunctival pedicle graft surgery and subsequently either did or did not develop a conjunctival graft complication were reviewed. RESULTS: One hundred and six dogs undergoing conjunctival graft surgeries were identified. Sixteen conjunctival graft complications occurred, of which, eight led to negative outcomes. Univariable analysis comparing canine eyes that developed complications to control eyes revealed potential (p ≤ .05) differences between the groups in post-operative fluoroquinolone use, Streptococcus canis isolation, intraoperative intravenous cefazolin use, corneal stromal white cell infiltrate, and mean ulcer diameter. The use of intraoperative cefazolin could not be effectively evaluated with available data; however, no dogs (n = 22) receiving intraoperative cefazolin developed complications. Multivariable analysis revealed that dogs that were treated with a second-generation fluoroquinolone and that had S. canis isolated had higher odds of experiencing complications than dogs that were not treated with a second-generation fluoroquinolone and that were S. canis negative (Odds ratio = 64.7 [95% CI 6.3-669], p < .0001). CONCLUSIONS: Streptococcus species played a role in conjunctival graft complications in our study. Empiric selection of second-generation fluoroquinolone monotherapy may need reconsideration given the frequent isolation of Streptococcus spp. from canine ulcers. The use of intraoperative cefazolin may be associated with a lower complication rate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".