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Record W4403638754 · doi:10.4081/ejtm.2024.12931

Effectiveness of laser therapy among patients with open-angle glaucoma: a systematic review and meta-analysis study

2024· review· en· W4403638754 on OpenAlexaff
Behzad Safarpour Lima, Shima Sayanjali

Bibliographic record

VenueEuropean Journal of Translational Myology · 2024
Typereview
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsPrism Eye Institute
Fundersnot available
KeywordsGlaucomaMedicineMeta-analysisIntraocular pressureOdds ratioOphthalmologyInternal medicineOpen angle glaucomaSubgroup analysisWeb of scienceRandom effects model

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.590
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.047
GPT teacher head0.332
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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