Dry eye disease and psychiatric disorders: A systematic review and meta-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
The association between dry eye disease (DED) and psychiatric conditions is a highly researched topic. This work reviews the literature on this relationship, examining the prevalence and correlations of depression and anxiety with dry eye signs and symptoms. A comprehensive literature search of MEDLINE, EMBASE, PsycINFO, and gray literature was conducted, with keywords for dry eye and mood disorders, depression, anxiety, and suicide. Eligible studies underwent quality assessment using the Newcastle-Ottawa Scale. Meta-analysis was performed using STATA 15.0. Fixed- and random-effects models were computed based on the presence of heterogeneity. Thirty-two studies were included, with 31 reporting on depression and 19 on anxiety. Meta-analysis results found a depression prevalence of 40% (CI: [0.29, 0.52]) in DED patients, with 1.81 times higher odds of prevalence compared to controls (CI: [1.61, 2.02]). Prevalence of anxiety was 39% (CI: [0.15, 0.64]), with 2.32 times higher odds of prevalence compared to controls (CI: [1.67, 3.23]). Depression scores were significantly higher in patients with DED in all studies. Anxiety scores were significantly higher in DED patients in studies using all scales except the Hospital Anxiety and Depression Scale-Anxiety Subscale. DED symptom scores were significantly associated with depression (ES = 0.43; CI: [0.31, 0.55]) and anxiety (ES = 0.41; CI: [0.32, 0.50]) scores. In conclusion, depression and anxiety are more prevalent and severe in DED patients and are correlated with dry eye symptoms but not signs. These findings highlight the interrelationship between these disorders and have important implications for providing appropriate care to these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| 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) | 0.000 | 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