Cotton‐tip debridement, scalpel blade debridement, and superficial grid keratotomy for treatment of spontaneous chronic corneal epithelial defects (SCCED): A retrospective evaluation of 308 cases
Bibliographic record
Abstract
PURPOSE: To evaluate the clinical course and outcome of canine SCCEDs treated with a combination of cotton-tip debridement (CTD), scalpel blade debridement (SBD), and superficial grid keratotomy (SGK). METHODS: Medical records of dogs diagnosed with SCCED and treated by the same diplomate (FJO) from 2011 to 2019 were reviewed. Age, breed, sex, affected eye, time of onset before treatment, previous procedures performed, time to healing, need for a second treatment, and complications were reported. RESULTS: A total of 308 eyes (291 dogs) met the inclusion criteria and were included in the study. All dogs received the same treatment (CTD + SBD + SGK) and the same topical medication (tobramycin 0.3% solution and sodium chloride 5% ointment). All eyes healed. Mean age at presentation was 9 years and 6 months (114.4 ± SD 28.0 months), and Boxer was the most common breed (93/308; 30.2%). Mean corneal healing time was 11.5 days (±SD 6.6). Complications occurred in 15/308 (4.9%) eyes. The three main complications observed were infected epithelial ulcer, infected stromal ulcer, and melting corneal ulcer, and 7/15 (46.7%) of the complications were diagnosed in Boston Terrier. Healing occurred after one treatment in 299/308 (97.1%) eyes, and the remaining cases needed a second treatment. CONCLUSIONS: CTD + SBD + SGK is an inexpensive and efficient treatment for SCCED in dogs. Boston Terrier may be at higher risk of developing complications following this procedure.
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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 | 0.001 | 0.001 |
| 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".