Systematic review and meta-analysis: dipeptidyl peptidase-4 inhibitors and rheumatoid arthritis risk
Bibliographic record
Abstract
This review evaluated the risk of rheumatoid arthritis in patients with type 2 diabetes treated with dipeptidyl peptidase-4 inhibitors (Dpp-4i). The MEDLINE (via PubMed), Embase, the Cochrane Library databases and web of science were used to search the effects of Dpp-4i on rheumatoid arthritis in patients with type 2 diabetes from inception to 7 September, 2020. We included studies that met the following criteria:(i) A randomized controlled trial (RCT), prospective or retrospective cohort study examining the relationship between Dpp-4i and rheumatoid arthritis. Exclusion criteria included the following: Reviews and researches related to other diseases or subjects; and studies without data on the prevalence of rheumatoid arthritis were excluded. Risk of Bias table contained in Review Manager 5.3 and Newcastle-Ottawa scale (NOS) were used for quality assessment of included RCT and observational studies separately. Meta-analysis was used to estimate the risk of disease. We conducted a subgroup analysis of duration of follow-up, adjusted (adjusted RR or unadjusted RR), sample size and study design. A total of 10 independent studies assessing 1,420,414 patients were included in this analysis. In this meta-analysis, we found that there was nonsignificant increase of rheumatoid arthritis with Dpp-4 inhibitor exposure (RR 0.96, 95%CI (0.69-1.32)). Our results revealed that Dpp-4 inhibitors do not seem to increase the risk of rheumatoid arthritis. Long-term follow-up monitoring is necessary.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.008 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".