Efficacy and Safety of Selective Laser Trabeculoplasty among Ethiopian Glaucoma Patients
Bibliographic record
Abstract
BACKGROUND: Selective laser trabeculoplasty (SLT) is a safe and effective treatment modality for lowering intraocular pressure (IOP). PURPOSE: To determine the efficacy and safety of SLT among Ethiopian patients with primary open-angle glaucoma (POAG), pseudoexfoliation glaucoma (PXG), and ocular hypertension (OHT). METHOD: A prospective, nonrandomized interventional study was conducted at Menelik II Hospital, Ethiopia. Patients on antiglaucoma medication with uncontrolled IOP and those patients treated for the first time with 360 degrees of SLT were included. Success was defined as an IOP lowering of > 20% from baseline without repeat treatment. RESULT: A total of 95 eyes of 61 patients with a diagnosis of OAG and OHT were enrolled. The diagnosis was POAG in 55 (57.9%) eyes, PXG in 22 (23.2%) eyes, and OHT in 18 (18.9%) eyes. Seventy (73.7%) eyes were on medications, and 25 (26.3%) eyes were treated with laser as primary therapy. The mean (SD) baseline IOP and medication were 24.3 ± 2.5 mmHg and 1.29 ± 1.01, respectively. The one-year mean (SD) IOP reduction was 6.7 ± 4.2 mmHg and medication reduction was 0.26 ± 1.34. The overall IOP reduction at 12 months was 27.6%, and the success rate was 60%. The mean IOP (SD) reduction for patients who were treated for the first time with laser and on antiglaucoma medication was 6.5 ± 3.1 mmHg and 6.8 ± 2.8 mmHg, respectively. Post-SLT, patients experienced transient ocular pain, brow ache, headache, and/or blurring of vision in 31.6%, anterior chamber reaction in 36.8%, and IOP spike ≥ 6 mmHg in 11.6%. CONCLUSION: SLT is an effective and safe treatment modality for OHT, POAG, and PXG among Ethiopian patients either as a first-line treatment or as an adjunct to topical glaucoma treatment.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".