Use of Transcorneal Iris Photocoagulation to Facilitate Sector Iridectomy of Pigmented Iridal Tumors: A Case Series of Five Eyes (Three Dogs and One Cat)—Clinical Findings, Surgical Technique, Complications, and Outcome
Bibliographic record
Abstract
OBJECTIVE: To describe the use of transcorneal iris photocoagulation (TCIP) to improve intraocular visualization of intended incision lines, reduce hemorrhage, and facilitate excision of pigmented iridal tumors in four canine eyes and one feline eye. MATERIALS AND METHODS: A Rhodesian Ridgeback (treated bilaterally), a German Shepherd, a Labrador Retriever, and a Scottish Fold underwent sector iridectomy due to rapidly growing, pigmented, raised, iridal tumors affecting 1/4-1/3 of the iris circumference (3- to 4-clock hours). A diode laser was used to delineate the intended sector iridectomy incision lines, approximately 1-2 mm away from the grossly visible tumor margins, with the aim of improving visualization to achieve tumor-free margins and reduce tissue handling/trauma. RESULTS: All iridal tumors were removed en bloc with tumor-free margins on histopathology. The most common histologic diagnosis was iris melanocytoma (3/5 eyes). The most common intra- and postoperative complications included hyphema and fibrin clot formation (5/5), posterior synechia formation of iris wound margins (5/5 eyes), and photophobia (3/5 eyes). Two eyes required intracameral tissue plasminogen activator (tPA) injections within 2 weeks of surgery. The follow-up period for all operated eyes ranged from 5 to 14 months. Vision was retained in all eyes, with no grossly apparent tumor regrowth within the follow-up times included for each case in the present series. CONCLUSIONS: The use of TCIP to delineate intended incision lines improved intraocular visualization of sector iridectomy surgical margins in this case series. While hyphema and fibrin clot formation still occurred, they were successfully managed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".