Depression among keratoconus patients: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Keratoconus (KC) is a chronic corneal disease that typically presents in early adulthood, and may potentially result in poor mental health in affected individuals. The evidence regarding the association of depression with KC is controversial. Hence, we investigated the association between depression and KC via a systematic review and meta-analysis. Methods Five electronic medical databases (PubMed, Scopus, PsycINFO, Web of Science, and CINAHL Complete) were systematically queried for English-language records from their inception to January 8, 2024. We include observational studies that measured the risk of depression or compared depression scores in KC patients in comparison to healthy ones. The Newcastle–Ottawa Quality Assessment Scale was utilized to assess bias risk in the included studies. Random-effect modeling was applied for meta-analysis (STATA-17). Results Out of the 159 documents retrieved, seven articles were deemed relevant after screening. An analysis involving 83 KC patients and 3,186 controls indicated that KC participants had significantly higher depression scores [SMD: 0.71 [0.31, 1.11]; p < 0.01, I2: 52.7%]. However, a meta-analysis of four studies comparing depression rates in KC patients (n = 23,838) to control groups (n = 73,482) found no increased risk of depression among KC patients compared to controls [OR: 1.13 [0.66, 1.94]; p = 0.65, I2: 95.35%]. Conclusion While KC patients exhibit significantly higher depression scores compared to controls, a meta-analysis indicates no increased overall risk of depression among KC patients. These findings highlight the complexity of the relationship between keratoconus and mental health, warranting further investigation. Systematic review registration PROSPERO, identifier, CRD42024502247, available at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024502247 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".