Bone fracture risk in patients with rheumatoid arthritis
Bibliographic record
Abstract
BACKGROUND: Patients with rheumatoid arthritis (RA) are predisposed to osteoporotic fracture. The present study aims to determine the association between rheumatoid arthritis (RA) and bone fracture risk, and in relation to gender and site-specific fractures. METHODS: Studies related to bone fracture in patients with RA were searched from databases including PubMed, EMBASE, and OVID from inception through April 2016. The quality of the studies was evaluated using the Newcastle-Ottawa Scale. Meta-analysis was performed with Stata13.1 software. The results were reported based on risk ratio (RR) and 95% confidence interval (95% CI) using a random effects model. RESULTS: The meta-analysis of 13 studies showed a significant higher risk of bone fracture in patients with RA than in patients without RA (RR = 2.25, 95% CI [1.76-2.87]). Subgroup analyses showed that both female and male patients with RA had increased risk of fracture when compared with female and male patients without RA (female: RR = 1.99, 95% CI [1.58-2.50]; male: RR = 1.87, 95% CI [1.48-2.37]). Another subgroup analysis of site-specific fracture also showed that RA is positively correlated with the incidence of vertebral fracture (RR = 2.93, 95% CI [2.25-3.83]) or hip fracture (RR = 2.41, 95% CI [1.83-3.17]). CONCLUSION: RA is a risk factor for bone fracture in both men and women, with comparable risks of fractures at the vertebral and hip.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".