Prevalence and risk of nonalcoholic fatty liver disease among adult psoriatic patients: A systematic review, meta-analysis, and trial sequential analysis
Bibliographic record
Abstract
BACKGROUND: This systematic review and meta-analysis aimed to report the evaluation of the prevalence and risk of nonalcoholic fatty liver disease (NAFLD) among adult psoriatic patients in a systematic review and meta-analysis. METHODS: A comprehensive search was conducted across 4 databases of PubMed, Scopus, Cochrane Library, and Web of Science to collect relevant studies until November 30, 2023, without any restrictions for finding observational studies. The comprehensive meta-analysis version 3.0 software was used to calculate effect sizes, showing the event rate (ER), odds ratio (OR), and a 95% confidence interval (CI) to evaluate NAFLD risk or prevalence in psoriatic patients and controls or psoriatic patients alone. The quality scoring was performed by 1 author based on the Newcastle-Ottawa Scale tool. Publication bias, meta-regression analysis, and sensitivity analyses were performed. Additionally, Trial Sequential Analysis (TSA) was performed using TSA software. RESULTS: A total of 581 records were identified among the databases and electronic sources. At last, 41 studies involving 607,781 individuals were included in the meta-analysis. The pooled ER of NAFLD among psoriatic patients was 29.5% (95%CI: 19.6%-41.7%) and I2 = 99.79%. The pooled OR of NAFLD in psoriatic patients compared to controls was 1.685 (95%CI: 1.382-2.055; P < .001) and I2 = 87.96%. CONCLUSIONS: The study found a significant link between psoriasis and NAFLD, with psoriatic patients having a higher chance of developing NAFLD compared to the controls. The study calls for regular NAFLD screening in psoriatic patients to prevent liver complications.
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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 | 0.034 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.049 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".