Current review of Excimer laser Trabeculostomy
Bibliographic record
Abstract
BACKGROUND: Excimer laser trabeculostomy (ELT) is a microinvasive glaucoma surgery (MIGS) that creates multiple laser channels through the trabecular meshwork using a cold laser system, which minimizes tissue fibrosis and aids in bypassing the main area of resistance to aqueous outflow. The purpose of this review is to evaluate the current body of evidence surrounding ELT in terms of efficacy and review the safety profile of the procedure. MAIN TEXT: Studies screened had to show clear inclusion and exclusion criteria as well as well-defined outcome measures. PubMed, MEDLINE, EMBASE and the Cochrane Controlled Trial Database were searched. Preferred Reporting Items of Systematic Reviews (PRISMA) guidelines were used to assess for study quality and for any bias. Sixty-four articles were initially identified with 18 meeting preliminary screening criteria. Ultimately, 8 studies met inclusion criteria and 2 additional non-referenced publications were also included: 1 randomized control trial, 4 prospective case series and 5 retrospective studies. Overall studies showed moderate intraocular pressure (IOP) lowering of between 20% and 40% from baseline without medication washout and mostly a decrease in glaucoma medications with few complications. CONCLUSION: Current literature shows a significant IOP-lowering effect of ELT with a favorable safety-profile in standalone cases or combined with cataract surgery. Limitations to these studies are the lack of controls and washout IOP. Overall, ELT is an attractive MIGS option that does not require any residual device remaining in the angle.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".