A Systematic Review to Identify the Effects of Biologics in the Feet of Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
Background and Objective: Ninety percent of patients with rheumatoid arthritis (RA) feel foot pain during the disease process. Pharmacological treatment of RA has a systematic effect on the body and includes: Nonsteroidal anti-inflammatory drugs, disease-modifying antirheumatic drugs (DMARDs) and biologics. The objective of our review was to examine the impact of biologics on patients with RA ‘foot. Methods and Material: A systematic review of randomized control trials and observational studies that evaluated the efficacy of biologics against other pharmacological treatment, and included a foot outcome measure. The search covered MEDLINE Ovid, Pubmed, CINAHL, Cochrane Library, Evidence Search, and Web of Science. Risk of bias was evaluated using Cochrane guidance and the Newcastle Ottawa Scale adapted version. Results: A total of eight studies fully met the inclusion criteria: Three randomized control trials, and five observational studies were the basis of our review. A total sample of 1856 RA patients with RA treatment participated. The use of biologics was not associated as a risk factor for post-operative surgical site infection or delayed wound healing. The benefits of biologics, in terms of the disease evolution, were assessed using X-ray. Conclusion: Evidence suggests that the use of biologics is not a risk factor for post-operative surgical site infection or delayed wound healing. The use of biologics presents benefits in terms of the disease evolution assessed through X-ray.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.011 | 0.012 |
| 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) | 0.006 | 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".