Association between antibiotic use and the risk of rheumatoid arthritis
Bibliographic record
Abstract
BACKGROUND: The potential association between antibiotic use and the risk of rheumatoid arthritis (RA) has drawn significant attention from clinicians and researchers in recent years due to the wild usage of antibiotic. This study aimed to perform a systematic review and meta-analysis of the literature to determine if antibiotic use is associated with an increased risk of RA, so as to provide an important reference for clinical decision-making. METHODS: Case-control and nest case-control studies of assessing whether antibiotic use is associated with the onset of RA will be identified in searches of 4 databases from their inception to August 2019. All data were assessed and extracted by 2 authors independently. The Newcastle-Ottawa scale was used to assess the quality of the selected studies. Manager Software 5.3 from Cochrane Collaboration (London, UK) and Stata 15.1 (Stata Corp, College Station, TX) will be used to conduct meta-analysis, determining pooled odds ratios and evaluating heterogeneity between studies. RESULT: The results of this systemic review and meta-analysis will be submitted to a recognized journal for publication. CONCLUSION: This systemic review and meta-analysis will determine if antibiotic use is associated with an increased risk of RA. We hope this study can make a definitive conclusion for the association.
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".