Retinal detachment and glaucoma in the Boston Terrier and Shih Tzu following phacoemulsification (135 patients): 2000–2014
Bibliographic record
Abstract
OBJECTIVES: To report the cumulative incidence of retinal detachment (RD) and glaucoma following phacoemulsification in Boston Terriers and Shih Tzu in the southeastern United States over a 14-year period and investigate the potential predisposing risk factors. METHODS: Medical records of 83 Shih Tzu and 52 Boston Terriers that underwent phacoemulsification between 2000 and 2014, with or without intraocular lens placement, were reviewed. For a comparison population, phacoemulsification data from 45 Labrador Retrievers, 73 Schnauzers, and 159 Bichon Frises were evaluated. Information collected included signalment, concurrent systemic diseases, preoperative findings, surgical details, postoperative complications, and duration of follow-up. Percentages of patients to develop RD and glaucoma were assessed, as well as potential risk factors. Minimum of 3 months of follow-up after surgery was required for inclusion. RESULTS: Retinal detachment occurred in 7.7% (7/91 eyes) and 8.9% (11/123 eyes) and glaucoma occurred in 38.0% (35/91 eyes) and 29.3% (36/123 eyes) of Boston Terriers and Shih Tzu, respectively. Mean follow-up time was 804 days. Neither Boston Terriers nor Shih Tzu were at increased risk for RD or glaucoma when compared to the other breeds, and no significant risk factors for either breed were identified in the final multivariate analysis. CONCLUSIONS: The cumulative incidence of RD in Boston Terrier and Shih Tzu reported here was in agreement with previously reported nonbreed specific percentages (2.7-8.4%). The cumulative incidence of glaucoma in this population of Boston Terriers and Shih Tzu was higher than previously reported nonbreed specific percentages (5.1-18.8%).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".