Multiple XEN Gel Stents for Refractory Pediatric Glaucoma
Bibliographic record
Abstract
Although trabeculotomy and goniotomy are currently the mainstay of surgical management for congenital glaucoma, XEN Gel Stent (Allergan) implantation and other microinvasive glaucoma surgery technologies may offer the advantage of having a lower risk of postoperative complications than conventional techniques. A 10-year-old boy presented with aphakic glaucoma in his left eye secondary to previous cataract surgery. Intraocular pressure (IOP) in the left eye at initial presentation was 31 mm Hg with maximal tolerated medical therapy. Surgical history included tube shunt, shunt revision, and subsequent shunt removal. Shunt surgery and revision had been unsuccessful at achieving target IOP. The patient underwent two treatments of micro-pulse transscleral laser therapy that failed to achieve target IOP. At this time, an open conjunctiva ab externo superior XEN Gel Stent (Allergan) was implanted. Within 1 month of surgery, conjunctival dehiscence and contraction occurred. Following this, ab interno inferonasal air–ophthalmic viscosurgical device XEN Gel Stent implantation was performed. In the 6 months following the second XEN Gel Stent, IOP in the left eye was stable at 6 to 8 mm Hg. This report describes the effective use of a XEN Gel Stent implant in the management of congenital glaucoma, while also highlighting a complication. Further studies are required to determine the comparative outcomes of this technique with conventional surgical management. [ J Pediatr Ophthalmol Strabismus . 2022;59(1):e11–e14.]
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".