Eyelid Margin and Meibomian Gland Characteristics and Symptoms in Lens Wearers
Bibliographic record
Abstract
PURPOSE: To describe the lid margin characteristics of contact lens wearers and relate them to comfort during lens wear. METHODS: Three study sites enrolled habitual contact lens wearers. Subjects completed the Comfort domain of the Contact Lens User Experience (CLUE) questionnaire, and each eye was graded for the presence of mucocutaneous junction (MCJ) displacement, lid margin irregularity, and lid margin vascularity. Examiners counted the number of meibomian gland (MG) orifices in the central centimeter of the lower eyelid and the number of those that showed pouting/plugging and vascular invasion. MG expressibility was graded according to the Shimazaki schema. Subjects were grouped based on presence/absence of each characteristic, total number of orifices (≥5 vs. <5), and expressibility (grade 0 vs. >0). Descriptive statistics are reported. A linear model was used to assess the fixed effect of each characteristic on combined CLUE score and each CLUE statement, if the effect on combined CLUE score showed p < 0.10. RESULTS: The study included 203 subjects (67.5% female) with mean age (±SD) of 30.3 ± 9.6 years. The most commonly observed characteristics were orifice pouting/plugging, compromised MG expressibility, and lid margin vascularity (35.0, 30.3, and 20.4%, respectively). MCJ displacement and MG expressibility had an effect on the combined CLUE score such that individual CLUE statements were analyzed (p = 0.01 and p = 0.06, respectively). MCJ displacement had an effect on comfort upon insertion (p = 0.01), comfort after 5 minutes (p = 0.03), end-of-day comfort (p = 0.01), and ability to maintain ocular moisture (p = 0.030). MG expressibility had a significant effect on general comfort (p = 0.01), comfort throughout the day (p = 0.02), and the ability to maintain ocular moisture (p = 0.02). CONCLUSIONS: MCJ displacement and MG expressibility have an effect on contact lens comfort.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".