A Canadian Clinical Practice Algorithm for the Management of Patients with Non-Variceal Upper Gastrointestinal Bleeding
Bibliographic record
Abstract
AIM: To use current evidence-based recommendations to provide a user-friendly clinical algorithm for the management of upper gastrointestinal bleeding, adapted to the Canadian environment. METHODS: A multidisciplinary consensus group of 25 participants representing 11 national societies used a seven-step approach to develop recommendations according to accepted standards. Sources of data included narrative and systematic reviews as well as published and new meta-analyses. A small writing subgroup subsequently created the algorithm. RESULTS: Recommendations emphasize appropriate initial resuscitation of the patient and a multidisciplinary approach to clinical risk stratification that determines the need for early endoscopy. Early endoscopy allows safe and prompt discharge of selected patients classified as low risk. Endoscopic hemostasis is reserved for patients with high-risk endoscopic lesions. Although monotherapy with injection or thermal coagulation is effective, the combination is superior to either treatment alone. High-dose intravenous proton-pump inhibition is recommended in patients who have undergone successful endoscopic therapy. Routine second-look endoscopy is not recommended. Patients with upper gastrointestinal bleeding secondary to ulcer disease should be tested and treated for Helicobacter pylori infection. CONCLUSIONS: This algorithm should facilitate appropriate risk stratification, use of endoscopic therapy and the appropriate utilization of proton-pump inhibition to optimize the care of patients with upper gastrointestinal bleeding. The algorithm should be customized to the resources of individual medical centres. Its application should be studied with appropriate outcomes recorded and validation performed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".