Cost‐effectiveness in Canada of intravenous proton pump inhibitors for all patients presenting with acute upper gastrointestinal bleeding
Bibliographic record
Abstract
BACKGROUND: The administration of proton pump inhibitors intravenously after endoscopic treatment of peptic ulcers significantly reduces the recurrence of bleeding. AIM: To evaluate the incremental cost-effectiveness in Canada of intravenous proton pump inhibitor before endoscopic therapy to patients presenting with acute upper gastrointestinal bleeding, compared with endoscopic treatment alone. METHODS: From a third-party payer perspective, we modelled the costs and effectiveness over 60 days of the two approaches using decision analysis. The probabilities of various outcomes, such as re-bleeding and the need for surgery, were taken from the published literature. We included the costs of intravenous proton pump inhibitor, therapeutic endoscopy, surgical procedures and hospitalizations, all expressed in 2001 Canadian dollars. RESULTS: In a hypothetical cohort of 1000 patients, the intravenous proton pump inhibitor approach resulted in mean savings of 20,700 Canadian dollars with 37 re-bleeding episodes averted. The investigation of uncertainty resulted in a likelihood of intravenous proton pump inhibitor being cost-effective of at least 0.73. CONCLUSION: It is common in Canada to administer intravenous proton pump inhibitors to patients with upper gastrointestinal bleeding even before endoscopic confirmation of bleeding peptic ulcers. Our results suggest that this approach has a high likelihood of being cost-effective.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".