Treatment of ocular rosacea: a systematic review
Bibliographic record
Abstract
Rosacea is a common chronic skin disease distributed primarily around the central face. Ocular manifestations of rosacea are poorly studied, and estimates of prevalence vary widely, ranging from 6% to 72% in the rosacea population. Treatment options for ocular rosacea include lid hygiene, topical and oral antibiotics, cyclosporine ophthalmic emulsion, oral vitamin A derivatives, and intense pulsed light; however, a direct comparison of treatment methods for ocular rosacea is lacking. This review aims to compare treatment efficacy and adverse events for different treatment modalities in ocular rosacea. We performed a systematic review by searching Cochrane, MEDLINE and Embase. Title, abstract, full text screening, and data extraction were done in duplicate. Sixty-six articles met the inclusion criteria, representing a total of 1,275 patients. The most effective treatment modalities were topical antimicrobials and oral antibiotics, which achieved complete or partial response in 91% (n = 82/90) and 89% (n = 525/580) of patients respectively, followed by intense pulsed light (89%, n = 97/109 partial response), cyclosporine ophthalmic emulsion (87% n = 40/46), and lid hygiene (65%, n = 67/105). Combination treatments achieved a complete or partial response in 90% (n = 69/77). Results suggest that topical antimicrobials, oral antibiotics, intense pulsed light. and cyclosporine were the most efficacious single modality treatments.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".