Ocular complications in psoriatic patients: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: To assess the prevalence of ocular findings in patients with psoriasis and compare the odds of developing these conditions between the psoriatic and control population through a systematic review and meta-analysis. METHODS: A comprehensive literature search was conducted using PubMed, Embase, Cochrane, and Web of Science databases to identify studies reporting ocular findings in psoriasis patients. Inclusion criteria encompassed cross-sectional, case-control, cohort studies, case series, and case studies. Data extraction and quality assessment followed PRISMA guidelines. The Newcastle-Ottawa Scale evaluated the risk of bias. Heterogeneity was assessed using Cochran's Q-test and I² statistics, with a random-effects model applied where significant heterogeneity was present. RESULTS: 30 studies comprising 131,687 patients (13,788 with psoriasis and 117,899 controls) were included. The relative likelihood of ocular findings in psoriasis patients showed to be increased in conjunctival hyperemia (OR = 7.38; 95% CI: 2.47-22.04), conjunctivitis (OR = 4.63; 95% CI: 1.42-15.08), dry eye (OR = 3.47; 95% CI: 2.06-5.83), and meibomian gland dysfunction (OR = 7.13; 95% CI: 2.14-23.72) compared to controls. In contrast, blepharitis, cataracts, episcleritis, glaucoma, pinguecula, pterygium, and uveitis did not differ significantly between the two groups. CONCLUSIONS: Psoriasis patients are at increased risk for certain ocular conditions, particularly conjunctival hyperemia, conjunctivitis, dry eye, and meibomian gland dysfunction. Further research is needed to understand the underlying mechanisms and to develop targeted management strategies.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".