Bisphosphonates therapy for osteoarthritis: a meta-analysis of randomized controlled trials
Bibliographic record
Abstract
High-turnover type bone metabolism derangement has been considered to be one of the major causes of osteoarthritis (OA). Bisphosphonates can attach to hydroxyapatite binding sites on bony surfaces, particularly those which are undergoing active bone resorption. To evaluate the effectiveness of bisphosphonates in OA treatment, literature databases were searched from inception to February 28, 2016 for clinical studies of bisphosphonates for OA treatment. All randomized controlled trials in which bisphosphonates therapy was compared with a placebo or a conventional medication, were selected. 15/1145 studies were eligible for analysis, which included 3566 participants. Bisphosphonates therapy improved pain, stiffness and function significantly in OA assessed by the Western Ontario and McMaster Universities Arthritis Index scale (MD = 4.59; 95 % CI 2.83-6.34; P < 0.00001; MD = 1.43; 95 % CI 0.83-2.23; P = 0.0005; MD = 2.01; 95 % CI 1.27-2.75; P < 0.00001). Bisphosphonates also reduced osteophyte score significantly (MD = -0.51; 95 % CI -0.84 to -0.19; P = 0.002). However, no significant differences were found in subjective improvement, osteoarthritis progression, the number of required acetaminophen treatment or joint replacement. In conclusion, bisphosphonates therapy is effective in relieving pain,stiffness and accelerating functional recovery in OA. Limitations of the studies we analysed included the differences in duration of bisphosphonates use, the doses and types of bisphosphonates and the lack of long-term data on OA joint structure modification after bisphosphonates therapy. More targeted studies are required to evaluate on the effectiveness of bisphosphonates for OA treatment.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".