Multicenter Testing of a Risk Assessment Survey for Soft Contact Lens Wearers With Adverse Events: A Contact Lens Assessment in Youth Study
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
PURPOSE: To test the ability of responses to the Contact Lens Assessment in Youth (CLAY) Contact Lens Risk Survey (CLRS) to differentiate behaviors among participants with serious and significant (S&S) contact lens-related corneal inflammatory events, those with other events (non-S&S), and healthy controls matched for age, gender, and soft contact lens (SCL) wear frequency. METHODS: The CLRS was self-administered electronically to SCL wearers presenting for acute clinical care at 11 clinical sites. Each participant completed the CLRS before their examination. The clinician, masked to CLRS responses, submitted a diagnosis for each participant that was used to classify the event as S&S or non-S&S. Multivariate logistic regression analyses were used to compare responses. RESULTS: Comparison of responses from 96 participants with S&S, 68 with non-S&S, and 207 controls showed that patients with S&S were more likely (always or fairly often) to report overnight wear versus patients with non-S&S (adjusted odds ratio [aOR], 5.2; 95% confidence interval [CI], 1.4-18.7) and versus controls (aOR, 5.8; CI, 2.2-15.2). Patients with S&S were more likely to purchase SCLs on the internet versus non-S&S (aOR, 4.9; CI, 1.6-15.1) and versus controls (aOR, 2.8; CI, 1.4-5.9). The use of two-week replacement lenses compared with daily disposables was significantly higher among patients with S&S than those with non-S&S (aOR, 4.3; CI, 1.5-12.0). Patients with S&S were less likely to regularly discard leftover solution compared with controls (aOR, 2.5; CI, 1.1-5.6). CONCLUSIONS: The CLRS is a clinical survey tool that can be used to identify risky behaviors and exposures directly associated with an increased risk of S&S events.
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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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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