Differences in body mass index among individuals with PsA, psoriasis, RA and the general population
Bibliographic record
Abstract
OBJECTIVES: To compare obesity among individuals with PsA, psoriasis (PsO), RA and the general population (n), and identify correlates of obesity among individuals with PsO and PsA. METHODS: We compared the BMI of patients with PsA (n = 644), PsO (n = 448), RA (n = 350) and the general population using age- and sex-adjusted linear and logistic regression analyses. We conducted multivariate analyses limited to PsO and PsA to determine correlates of BMI and obesity. RESULTS: The mean BMI (kilogram per square metre) for individuals with PsA, PsO, RA and the general population were 29.6, 27.9, 27.3 and 26.1, respectively. The proportion with obesity was 37, 29, 27 and 18% for individuals with PsA, PsO, RA and the general population, respectively. The differences in BMI were significant between all categories (P < 0.05) except between PsO and RA. Age- and sex-adjusted linear and logistic regression confirmed that these differences were significant. In multivariate logistic regression analyses adjusted for age, sex, smoking, PsO duration, psoriasis area severity index score, use of DMARDs, glucocorticoids and biologics, the odds of obesity were 61% higher for PsA patients than PsO patients (95% CI 1.10, 2.37). When we additionally adjusted for the physical component summary of the short form-36, the association was attenuated and became insignificant. CONCLUSIONS: Individuals with PsA have a higher mean BMI than those with PsO, RA or the general population. The BMI difference between PsA and PsO correlates with physical health.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".