Atopy and keratoconus: a multivariate analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND/AIMS: The primary goal of this study was to determine if atopy is a risk factor for keratoconus. Other potential risk factors were also studied and included age, sex, race, eye rubbing, mitral valve prolapse, handedness, collagen vascular disease, ocular trauma, pigmentary retinopathy, Marfan's syndrome, Down's syndrome, and a history of contact lens wear. METHODS: A case-control study was designed (n=120) with incident cases assembled from the years 1985-99. Controls were chosen from the same person-time experience as cases and were picked from a source population with multiple outcomes ensuring that none was knowingly related to any of the potential exposures being studied. Atopy was defined based on the UK working group 1994 definition (at least 4/6 criteria = complete, 3/6 criteria = incomplete, and at least 1/6 criteria = partial). Keratoconus was defined based on clinical criteria and previously published I-S values. Multiple logistic regression was used in the analysis to obtain the odds ratios as the measure of association. RESULTS: In the univariate associations, there was an association between keratoconus and atopy as well as eye rubbing and family history of keratoconus. However, in the multivariate analysis, only eye rubbing was still a significant predictor of keratoconus (odds ratio = 6.31 p = 0.001). CONCLUSIONS: This study supports the hypothesis that the most significant cause of keratoconus is eye rubbing. Atopy may contribute to keratoconus but most probably via eye rubbing associated with the itch of atopy. No other variable measured was significantly associated with the aetiology of keratoconus.
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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) | 0.006 | 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 it