A decade of surgical eye removals in Ontario: a clinical-pathological study
Bibliographic record
Abstract
OBJECTIVE: To assess patient demographics, clinical indications, and pathologic causes of surgically removed eyes over a decade in Ontario (Canada) and to identify areas of ocular disease management needing more attention. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: The surgically removed eyes of 713 consecutive mainly adult patients from 2004 to 2013. METHODS: Demographic, clinical, and pathologic data were collected on all eyes received by the University of Toronto Ophthalmic Pathology Laboratory from 2004 to 2013. RESULTS: Of the 713 eyes removed, enucleations accounted for 60% of cases, eviscerations for 39% of cases, and exenteration for 1% of cases. The most common clinical indications for surgical eye removal were blind painful eye (37%), neoplasm (35%), and trauma (6%). The leading pathologic causes of eye removal were neoplasm (36%), glaucoma (21%), infection or inflammation (17%), and trauma (16%). Glaucoma-related findings were the most common pathologic findings observed (38%), regardless of the primary cause. CONCLUSIONS: A blind painful eye and neoplasms were the most commonly documented indications prior to removal of the eye. Common pathologies included glaucoma, neoplasms, infection/inflammation, and trauma. However, regardless of the primary cause, glaucoma-related pathologies were the most common pathologic findings. Refractory eye disease and pain continue to be important reasons for removal of eyes among patients in Ontario. More effective and targeted management strategies are needed to reduce the need for this radical eye surgery of last resort.
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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 | 0.001 | 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".