Associated factors of osteoporosis in Chinese patients with rheumatoid arthritis: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The aim of this systematic review and meta-analysis was to analyze the factors associated of osteoporosis in patients with rheumatoid arthritis (RA) in China. METHODS: PubMed, Embase, Web of Science, Cochrane Library, CINAHL, and four Chinese electronic databases were searched for observational studies without language restrictions that reported the factors associated of osteoporosis from inception to February 2023. A modified Newcastle-Ottawa Scale evaluated the risk of bias. Statistical heterogeneity among the included studies was analyzed using Cochran Q and I2 tests. Begg and Egger tests were used to assess the publication bias. RESULTS: A total of 15 studies were finally included. The meta-analysis showed that 10 factors were grouped into three themes with statistical significance: (1) demographics theme: age ≥50 (odds ratio [OR] = 1.161; 95% CI, 1.111-1.231; p < 0.001), low body mass index (BMI) (OR = 1.248; 95% CI, 1.192-1.312; p < 0.001), female (OR = 5.174; 95% CI, 3.058-7.290; p < 0.001), and menopause (OR = 4.917; 95% CI, 1.558-15.523; I2 = 0.0%; p = 0.007); (2) RA-related factor theme: disease duration (OR = 1.083; 95% CI, 1.038-1.127; p < 0.001), and glucocorticoids (OR = 2.740; 95% CI, 2.000-3.750; p < 0.001); (3) relevant physiological indicators or scores theme: low 25(OH)D 3 (OR = 1.009; 95% CI, 1.003-1.016; p < 0.001), erythrocyte sedimentation rate (ESR) (OR = 1.489; 95% CI, 1.041-2.130; p = 0.029), high Disease Activity Score in 28 joints (DAS28) score (OR = 2.5991; 95% CI, 1.094-6.138; p < 0.001); and β-isomerized C-terminal telopeptide (β-CTx) (OR = 1.009; 95% CI, 1.003-1.016; p = 0.005). CONCLUSION: Osteoporosis in patients with RA is associated with various factors. Therefore, patients with RA should be monitored in a timely manner and targeted interventions should be taken. In addition, further longitudinal studies are needed to confirm the direct link between multiple factors and osteoporosis.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.034 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".