International Consensus on Guiding Recommendations for Management of Patients with Nonsteroidal Antiinflammatory Drugs Induced Gastropathy-ICON-G
Bibliographic record
Abstract
INTRODUCTION: Nonsteroidal anti-inflammatory drugs (NSAIDs), one of the most commonly used medications worldwide, are frequently associated with gastrointestinal adverse events. Primary care physicians often face the challenge of achieving adequate pain relief with NSAIDs, while keeping their adverse events to a minimum. This is especially true when long-term use of NSAIDs is required such as in patients with osteoarthritis and rheumatoid arthritis. To help primary care physicians deal with such challenges more effectively, a panel of expert gastroenterologists came together with the aim of developing practice recommendations. METHODS: A modified 'Delphi' process was used to reach consensus and develop practice recommendations. Twelve gastroenterologists from nine countries provided their expert inputs to formulate the recommendations. These recommendations were carefully developed taking into account existing literature, current practices, and expert opinion of the panelists. RESULTS: infection should be considered and treated before initiating NSAIDs; patients should be properly educated regarding NSAIDs use; patients who need to be on long-term NSAIDs should be prescribed a gastroprotective agent, preferably a proton pump inhibitor and these patients should be closely monitored for any untoward adverse events. CONCLUSION/CLINICAL SIGNIFICANCE: Hunt R, Lazebnik LB, Marakhouski YC, Manuc M, Ramesh GN, Aye KS, Bordin DS, Bakulina NV, Iskakov BS, Khamraev AA, Stepanov YM, Ally R, Garg A. International Consensus on Guiding Recommendations for Management of Patients with Nonsteroidal Anti-inflammatory Drugs Induced Gastropathy-ICON-G. Euroasian J Hepatogastroenterol, 2018;8(2):148-160.
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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 | 0.095 | 0.142 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".