Association between asthma and dry eye disease: a meta-analysis based on observational studies
Bibliographic record
Abstract
OBJECTIVE: This study aimed to systematically review the relationship between dry eye disease (DED) and asthma based on published population-based studies. DATA SOURCES: PubMed, EMBASE and ISI Web of Science from their inception were searched up to October 2019. STUDY SELECTION: Observational studies addressing the association between asthma and DED will be eligible. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently conducted the data extraction and quality assessment. We used a random-effects model for all analyses. Subgroup analysis according to ethnicity was performed to test the influence of ethnicity on the association. MAIN OUTCOMES AND MEASURES: Six independent studies (a total of 45 215 patients with asthma and 232 864 control subjects) were included in this review and had an average of seven stars by the Newcastle-Ottawa Scale. Our current findings suggest that the prevalence of DED was higher in the asthma group than in the control group (Z=7.42, p<0.00001; OR 1.29, 95% CI 1.20 to 1.38). In the subgroup analysis by ethnicity, Australian, Caucasian and Asian patients with asthma showed an increased risk of DED.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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) | 0.001 | 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".