Effectiveness of laser therapy among patients with open-angle glaucoma: a systematic review and meta-analysis study
Bibliographic record
Abstract
This study aims to evaluate the efficacy of selective laser trabeculoplasty in improving the intraocular pressure in patients diagnosed with open-angle glaucoma. A comprehensive search was performed across electronic databases, including PubMed, Scopus, and Web of Science, until June 2024, using keywords related to "selective laser trabeculoplasty" and "open-angle glaucoma." Studies were chosen based on set eligibility criteria. Data extraction was carried out by two independent reviewers, and statistical analyses were performed using a random-effects model to calculate the pooled mean differences in IOP reduction and overall success rates. The initial search yielded 3111 articles, with 23 studies included in the systematic review and 22 in the meta-analysis. The pooled MD in IOP reduction between the SLT and control groups was -1.44 mm Hg (95% CI: -2.19 to -0.70, p < 0.01). Subgroup analyses revealed a MD of -0.76 mm Hg (95% CI: -1.31 to -0.21, p < 0.01) when comparing SLT to medication, and -0.42 mm Hg (95% CI: -0.64 to -0.19, p < 0.01) when comparing 180-degree SLT to 360-degree SLT. The pooled success rate favored SLT with an odds ratio (OR) of 0.71 (95% CI: 0.51 to 0.99, p = 0.05). There was significant heterogeneity among the studies (I² = 71%). SLT is effective in lowering IOP in OAG patients, demonstrating significant efficacy compared to medication and different SLT protocols. The findings underscore SLT's potential as a reliable treatment option. However, the observed heterogeneity underscores the necessity for standardized protocols in future research to improve comparability and verify SLT's long-term effectiveness.
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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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".