A Stepwise Approach to the Surgical Management of Hemorrhagic Choroidal Detachments
Bibliographic record
Abstract
Purpose: This work describes a stepwise surgical approach to draining choroidal detachments and 2 cases for which this approach was used. Methods: The first step involves insertion of an anterior chamber maintainer and a nonvalved 23- or 25-gauge trocar cannula at the highest peak of hemorrhagic choroidal detachment (as determined using B-scan ultrasonography), 6 to 8 mm from and angled 20° to 30° toward the limbus. The second step involves removal of the trocar to expose the sclerotomy. Alternatively, the second step can be insertion of a second trocar. The third step involves the creation of a small focal peritomy around the preexisting sclerotomy and enlargement of the preexisting sclerotomy into a radial sclerotomy. Progression between steps only occurs if prior steps did not provide adequate drainage. Results: Two cases of appositional hemorrhagic choroidal detachments in hypotonic eyes were successfully resolved by this stepwise approach. In case 1, a choroidal detachment developed after a corneal ulcer perforation. The hemorrhagic choroidal detachment in case 1 was resolved with steps 1 and 2, and an unnecessary scleral cutdown was avoided. In case 2, a choroidal detachment developed after a trabeculectomy. The detachment in case 2 required progression to step 3, extension of the trocar insertion site into a radial sclerotomy. Conclusions: This stepwise approach should be considered to reduce excessive manipulation of the globe and conjunctiva in hemorrhagic and serous choroidal detachments that warrant surgical intervention.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".