Cenegermin for the treatment of dry eye disease
Bibliographic record
Abstract
Dry eye disease (DED) is the most common ocular surface disorder affecting millions of people worldwide. Due to its chronic nature, the management of DED still represents a challenge in the ophthalmic practice. Nerve growth factor (NGF), which is expressed along with its high-affinity TrkA receptor on the ocular surface complex, has been widely studied for the treatment of neurotrophic keratopathy, and a novel recombinant human NGF (rhNGF) has recently received full market authorization in this setting. Since NGF has shown in both in vitro and in vivo studies to promote corneal healing, to enhance conjunctival epithelium differentiation and mucin secretion, and to stimulate tear film production and functionality, it could provide potential benefits also in patients with DED. A recent phase II clinical trial has assessed the role of rhNGF in DED patients, demonstrating significant improvements of DED signs and symptoms after 4 weeks of treatment. Further clinical evidence will be provided by the 2 ongoing phase III clinical trials. This review aims at comprehensively illustrating the rationale of use along with the efficacy and safety profile of topical NGF in patients with DED.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".