Standard of Care for First-line Therapy in Newly Diagnosed Glaucoma and Update on SLT from the LiGHT Trial
Bibliographic record
Abstract
Glaucoma is a progressive, multifactorial disease marked by ganglion cell loss, optic nerve damage and progressive vision loss, which can result in blindness if not treated. Glaucoma accounts for 11% of registrations for blindness. The disease is closely linked to increased intraocular pressure (IOP) and reducing this pressure is the sole available treatment to slow disease progression. The epidemiology of glaucoma presents a significant public health challenge, with primary open‑angle glaucoma (POAG) being the most common form, affecting approximately 2–3% of adults over the age of forty. Many patients can be initially managed with medications; however, the treatment has significant limitations. Issues such as complications, side effects, adherence, nonresponse, reduced effectiveness over time (tachyphylaxis), and financial costs pose challenges to controlling IOP with eye drops. The global burden of glaucoma is expected to increase as the population ages, highlighting the urgency for effective management strategies. The landmark LiGHT (Laser in Glaucoma and Ocular Hypertension) trial, published in 2019, with an initial 36 months of follow-up, later extended to 72 months of follow‑up, has conceptually influenced the management of POAG and Ocular hypertension (OHT). By demonstrating the efficacy and safety of selective laser trabeculoplasty (SLT), a “dropless” and “knifeless” alternative as a first-line treatment option, the LiGHT trial challenged the conventional treatment paradigm. The six-year results further consolidate SLT’s role as a fundamental treatment option, indicating its long-term effectiveness and durability in managing glaucoma, potentially redefining standard care protocols.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".