Recommendations for the Appropriate Use of Anti-Inflammatory Drugs in the Era of the Coxibs: Defining the Role of Gastroprotective Agents
Bibliographic record
Abstract
Treatment with anti-inflammatory drugs and the analgesic efficacy of conventional nonsteroidal anti-inflammatory drugs (NSAIDs) are compromised by a two- to fourfold increased risk of gastrointestinal complications. This increased risk has resulted in an increasing use of the new selective cyclooxygenase-2 inhibitors or coxibs, which, in clinical trials and outcomes studies, reduced gastrointestinal adverse events by 50% to 65% compared with conventional NSAIDs. However, the coxibs are not available to all patients who need them, and NSAIDs are still widely used. Moreover, treatment with a coxib cannot heal pre-existing gastrointestinal lesions, and cotherapy with an anti-secretory drug or mucosal protective agent may be required. This paper addresses the management of patients with risk factors for gastrointestinal complications who are taking NSAIDs and makes recommendations for the appropriate use of 'gastroprotective' agents (GPAs) in patients who need to take an NSAID or a coxib. When economically possible, a coxib alone is preferable to a conventional NSAID plus a GPA to minimize exposure to potential gastrointestinal damage and avoid unnecessary dual therapy. Patients at high risk require a GPA in addition to a coxib.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".