Liver Abnormalities in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: We aimed to determine the prevalence and incidence, and to identify the factors associated with liver abnormalities in patients with psoriatic arthritis (PsA). METHODS: From a longitudinal cohort study, we identified PsA patients with either elevated serum transaminase or alkaline phosphatase levels or liver disease after the first visit to the PsA clinic (cases). Controls were subjects from the same cohort who never had such abnormalities or liver disease. Cases and controls were matched 1:1 by sex, age at the first clinic visit, and followup duration; variables at the onset of the first appearance of liver test abnormality associated with liver abnormalities were identified using univariate logistic and multivariate logistic regression analyses. RESULTS: Among 1061 patients followed in the PsA clinic, 343 had liver abnormalities. Two hundred fifty-six patients who developed liver abnormalities after the first visit were identified as cases, and 718 patients were identified as controls. The prevalence of liver abnormalities was 32% and the incidence was 39/1000 patient-years where there were 256 cases over 6533 total person-years in the PsA cohort. Liver abnormalities were detected after a mean (SD) followup duration of 8.3 ± 7.8 years. The common causes of liver abnormalities were drug-induced hepatitis and fatty liver. Independent factors associated with liver abnormalities were higher body mass index (BMI), daily alcohol intake, higher damaged joint count, elevated C-reactive protein, and use of methotrexate, leflunomide, or tumor necrosis factor inhibitors. CONCLUSION: Liver abnormalities are common among patients with PsA and are associated with higher BMI, more severe disease, and certain therapies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".