Relative safety and efficacy of topical and oral NSAIDs in the treatment of osteoarthritis: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) often affects the hands, knees, and hip joints, causing considerable pain and disability, and often affecting the patient's quality of life. Non-steroidal anti-inflammatory drugs (NSAIDs) are common pain relievers often applied as first line therapies for OA. However, prolonged NSAIDs application can have unwanted side effects. Given this, this study was designed to systematically evaluate the efficacy and safety of topical and oral NSAIDs for the treatment of OA. METHODS: We searched the PubMed, Embase, Cochrane Library, and Web of Science databases for relevant papers from their inception dates to May 2021. Our study only included randomized controlled trials comparing topical and oral NSAIDs and all data were analyzed using Review Manager version 5.3 (RevMan version 5.3). RESULTS: We identified 8 RCTs (2096 patients with OA), for evaluation and revealed that, in general, topical and oral NSAIDs presented with similar efficacies for the treatment of OA. The Western Ontario and McMaster Osteoarthritis Index for assessing pain relief in OA patients was (standardized mean difference [SMD] 0.07; 95%CI -0.02, 0.17) and visual analog scale was (SMD -0.01; 95%CI -0.02, 0.18), and improved stiffness in OA patients (SMD 0.09; 95%Cl 0.03, 0.20). CONCLUSIONS: Topical NSAIDs are as effective as oral NSAIDs for the treatment of OA and both topical and oral NSAIDs are equally effective in reducing pain and improving physical function in OA patients. In terms of safety, a larger number of samples are still needed to determine if there are any differences in the safety profile of topical or oral NSAIDs. REGISTRATION NUMBER: INPLASY 2021110009.
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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.023 | 0.036 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".