Efficacy and safety of oral NSAIDs and analgesics in the management of osteoarthritis: Evidence from real-life setting trials and surveys
Bibliographic record
Abstract
Non-steroidal anti-inflammatory drugs (NSAIDs) are at the cornerstone of treatment for osteoarthritis (OA). In recent years, the widespread use of oral NSAIDs has been called into question due to the appearance of significant upper gastrointestinal (GI) complications and cardiovascular (CV) adverse events (AEs). However, NSAIDs are non-homogeneous, and there are noticeable differences between them in AE risk for GI and CV events. Nevertheless, if properly prescribed oral NSAIDs can provide an effective and safe treatment for OA in real-life situations. The identification of patients with significant CV and/or GI risk is critical, and the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) treatment algorithm provides guidance on appropriate treatments for OA patients with elevated risk. Among non-selective NSAIDs, ibuprofen and naproxen seem preferable to diclofenac, the latter being associated with higher CV risk. Recommendation has been made by some that naproxen may be the preferred agent in patients at high CV risk because of its lower risk of CV events. Low dose celecoxib (200mg/day) is also associated with a lower risk of CV events compared with other coxibs. In addition, drugs with a demonstrated low GI risk profile may be of benefit, such as coxibs and nabumetone. Among patients who fail to respond adequately to sequential ESCEO algorithm Step 1 and Step 2 treatments, the short-term use of weak opioids, such as tramadol, for severely symptomatic OA patients is recommended. Although studies exploring the efficacy of tramadol in OA are limited, there is good evidence that tramadol works if prescribed properly. The sustained-release (SR) formulation of tramadol is preferred as it avoids the peak plasma concentrations reached with immediate-release tramadol, and is believed to reduce the incidence of AEs. Furthermore, slow upwards titration of tramadol SR is recommended to improve tolerability and minimize treatment discontinuations.
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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 | 0.033 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".