Impact of Obesity on Remission and Disease Activity in Rheumatoid Arthritis: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: To summarize the relationship between obesity and remission in rheumatoid arthritis (RA); secondary objectives were to summarize other measures of treatment response and mortality in RA. METHODS: Medline and Embase searches were performed in March 2016 using relevant MeSH and keyword terms for obesity and RA. Articles were selected if they reported estimates for achieving remission in obese subjects relative to other body mass index (BMI) categories, or changes in composite or individual disease activity measures or patient-reported outcomes during therapy, or mortality rates, in relation to BMI category or on a continuous scale. Remission outcomes were conducive to meta-analysis, and all other outcomes were summarized. RESULTS: A total of 3,368 records were screened; we included 8 reporting remission rates, 9 reporting disease activity measures or patient-reported outcomes, and 3 examining mortality by obesity status or BMI. Obese patients attain remission less frequently than nonobese and/or normal-weight patients. In adjusted models, obese patients demonstrated lower odds of achieving remission (pooled odds ratio [OR] 0.57 [95% confidence interval (95% CI) 0.45, 0.72]) and sustained remission (pooled OR 0.49 [95% CI 0.32, 0.74]) relative to nonobese subjects. Most studies found obese patients to have worse Disease Activity Scores or Disease Activity Scores in 28 joints, tender joint counts, inflammatory markers, patient global evaluation scores, pain scores, and physical function scores during followup, but not worse swollen joint counts. Obesity was not associated with increased mortality. CONCLUSION: Obesity decreases the odds of achieving remission in RA and negatively impacts disease activity and patient-reported outcomes during therapy. Interventions to reduce BMI should be investigated for their ability to improve disease outcomes.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.039 |
| Bibliometrics | 0.007 | 0.008 |
| 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".