An evidence-based approach to the management of uninvestigated dyspepsia in the era of Helicobacter pylori
Bibliographic record
Abstract
Objectives: To provide Canadian primary care physicians with an evidence-based clinical management tool, including diagnostic and treatment recommendations, for patients who present with uninvestigated dyspepsia. Recommendations: The management tool has 5 key decision steps addressing the following: (1) evidence that symptoms originate in the upper gastrointestinal tract, (2) presence of alarm features, (3) use of nonsteroidal anti-inflammatory drugs (NSAIDs), (4) dominant reflux symptoms and (5) evidence of Helicobacter pylori infection. All patients over 50 years of age who present with new-onset dyspepsia and patients who present with alarm features should receive prompt investigation, preferably by endoscopy. The management options for patients with uninvestigated dyspepsia who use NSAIDs regularly are: (1) to stop NSAID therapy and assess symptomatic response, (2) to treat with NSAID prophylaxis if NSAID therapy cannot be stopped or (3) to refer for investigation. Gastroesophageal reflux disease can be diagnosed clinically if the patient9s dominant symptoms are heartburn or acid regurgitation, or both; these patients should be treated with acid suppressive therapy. The remaining patients should be tested for H. pylori infection, and those with a positive result should be treated with H. pylori -eradication therapy. Those with a negative result should have their symptoms treated with optimal antisecretory therapy or a prokinetic agent. Validation and evidence: Evidence for resolution of the dyspepsia symptoms was the main outcome measure. Supporting evidence for the 5 steps in the management tool and the recommendations for treatment were graded according to the strength of the evidence and were endorsed by consensus of committee members. If no randomized controlled clinical trials were available, the recommendations were based on the best available evidence. Literature review: Evidence was obtained from MEDLINE searches for pertinent articles published from 1966 to October 1999. The searches focused on dyspepsia, diagnosis and treatment. Additional articles were retrieved through a manual search of bibliographies and abstracts from international gastroenterology conferences. Sponsors: Supported by unrestricted educational grants from AstraZeneca Canada Inc., Isotechnika Inc. and Integrated Healthcare Communications Inc.
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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 | 0.186 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.016 | 0.008 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".