Case-Control Pilot Study of Soft Contact Lens Wearers With Corneal Infiltrative Events and Healthy Controls
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to assess risk factors associated with soft contact lens (SCL)-related corneal infiltrative events (CIEs). METHODS: This was a single-visit, case-control study conducted at five academic centers in North America. Cases were defined as current SCL wearers with a symptomatic CIE. For each case, three age- and sex-matched controls were enrolled. Subjects completed the Contact Lens Risk Survey (CLRS), a standardized scripted medical interview, supplied a recent health history, and underwent an ocular examination. Microbial culturing of the ocular surface, SCL, and lens storage case was conducted for all cases and one of the three matched controls. Univariate and multivariate logistic regression modeling were used to assess the risk of developing a CIE. RESULTS: Thirty cases and 90 controls 13 to 31 years of age completed the study. Corneal infiltrative event diagnosis included contact lens-associated red eye, infiltrative keratitis, and contact lens peripheral ulcer. Subjects with symptomatic CIEs were more likely to harbor substantial levels of gram-negative bioburden on the ocular surface and contact lens. Significant risk factors for developing a CIE were overnight wear of SCLs, use of multipurpose solution, rinsing SCLs with water, lens storage case older than 6 months, previous "red eye" event, use of ocular drops in the past week, and illness during the past week. CONCLUSIONS: This pilot study demonstrated feasibility of enrolling a representative pool of SCL wearers with an untreated, symptomatic CIE and assessing CIE risk factors by using standardized methods. A larger sample size is needed to determine relationships between patient-reported behaviors and exposures, microbial bioburden, and CIE development.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".