Association between diabetes and keratoconus—a systematic review and meta-analysis
Bibliographic record
Abstract
Purpose To assess the association between diabetes mellitus and keratoconus. Methods PubMed, Google Scholar, Web of Science, and Scopus databases were searched for literature on the association between diabetes and keratoconus. The last literature search was conducted on April 4, 2021. A secondary form of the literature search was conducted by manually scanning the reference list of retrieved eligible articles. Included studies were cohort, case-control, or cross-sectional study design that used odds ratio or risk ratio to evaluate the relationship between keratoconus and diabetes. Egger's test was used to assess the presence of publication bias. The quality of eligible studies was assessed using the Newcastle-Ottawa Scale. Results Nine studies (six case-control and three cohort studies) published between 2000 and 2021 were included. The total number of keratoconus patients and controls were 27,311 and 53,732. respectively. Meta-analysis revealed no significant association between diabetes mellitus and keratoconus; the pooled odds ratio was 0.87 (95% confidence interval: 0.66–1.14; p = 0.314). There was significant heterogeneity ( Q (df = 7) = 33.36, p < 0.001; I 2 = 79.01, p < 0.001). Age of participants ( p < 0.0001), study design ( p < 0.001), and sample size ( p = 0.024) were significant sources of heterogeneity. There was no evidence of publication bias. Conclusion The current meta-analysis revealed no significant association between diabetes mellitus and keratoconus. Well-designed longitudinal prospective studies are, however, needed to investigate any association between diabetes mellitus and keratoconus.
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How this classification was reachedexpand
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".