Association of Body Mass Index Categories with Disease Activity and Radiographic Joint Damage in Rheumatoid Arthritis: A Systematic Review and Metaanalysis
Bibliographic record
Abstract
OBJECTIVE: Obesity and overweight are increasing conditions. Adipose tissue with proinflammatory properties could be involved in rheumatoid arthritis (RA) activity and radiographic progression. This study aims to investigate the influence of overweight and obesity on RA activity and severity. METHODS: We conducted a systematic review and metaanalysis to assess the association of body mass index (BMI) categories with the Disease Activity Score in 28 joints (DAS28), functional disability [Health Assessment Questionnaire (HAQ)], and radiographic joint damage in patients with RA. We searched Medline through PubMed, EMBASE, and the Cochrane Database of Systematic Reviews for all studies assessing DAS28, HAQ, or/and radiographic damage according to predefined BMI groups. RESULTS: Among the 737 citations retrieved, 58 articles met the inclusion criteria and 7 were included in the metaanalysis. DAS28 was higher in obese (BMI > 30 kg/m(2)) than non-obese (BMI ≤ 30 kg/m(2)) patients (mean difference 0.14, 95% CI 0.01-0.27, p = 0.04, I(2) = 0%). HAQ score was also higher among obese patients (mean difference 0.10, 95% CI 0.01-0.19, p = 0.03, I(2) = 0%). Radiographic joint damage was negatively associated with obesity (standardized mean difference -0.15, 95% CI -0.29 to -0.02, p = 0.03, I(2) = 38%). CONCLUSION: Obesity in RA is associated with increased DAS28 and HAQ score and with lower radiographic joint damage. These associations mainly result from an increase of subjective components of the DAS28 (total joint count and global health assessment) in obese patients. Conflicting results were reported concerning inflammation markers (C-reactive protein and erythrocyte sedimentation rate).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.043 |
| Bibliometrics | 0.008 | 0.010 |
| 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".