Investigating the role of inflammation in keratoconus: A retrospective analysis of 551 eyes
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: Keratoconus (KCN), classically defined as a noninflammatory corneal ectasia, was recently associated with chronic inflammation. This study aimed to further evaluate the association between inflammation and KCN severity by assessing patient tear films. METHODS: Retrospective chart review of consecutive patients (July 2016-February 2020) referred to a tertiary KCN centre. Using tomography Kmax values, the worst-eyes of patients with a diagnosis of KCN and tear film test results were included. Eyes were stratified as matrix metalloproteinase-9 (MMP9) positive or negative and analyzed using independent t and Pearson chi-squared tests. A p-value ≤ 0.05 was considered significant. RESULTS: Snellen and Kmax was 60.1 Diopters. MMP9 positive eyes had a higher Kmax (p = 0.048), and were more likely from patients who were male (p < 0.001), had a paediatric history of asthma (p = 0.042), and used glasses (p = 0.041). MMP9 negative eyes more likely corresponded to soft contact lens users (p = 0.012). No other significant differences were found in risk factors, topography, tomography, and tear film osmolarity. CONCLUSION: MMP9 positive keratoconic eyes had significantly higher Kmax readings which may correlate with increased disease severity, supporting an association between keratoconus and inflammation. Further research is warranted to evaluate the role of targeted therapy and contact lens use on MMP9 levels in keratoconic eyes and whether disease progression is affected.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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