Methodology for Randomized Trials of Patients With Nonvariceal Upper Gastrointestinal Bleeding: Recommendations From an International Consensus Conference
Bibliographic record
Abstract
The aim of this document is to provide a methodological framework for the design, performance, analysis, interpretation, and communication of randomized trials that assess management of patients with nonvariceal upper gastrointestinal bleeding. Literature searches were performed and an iterative process with electronic and face-to-face meetings was used to achieve consensus among panel members as part of an International Consensus Conference on Nonvariceal Upper Gastrointestinal Bleeding. Recommendations of the panel include the following. Randomized trials must explicitly state their primary hypothesis. A nonmanipulable randomization schedule with concealed allocation should be used. Stratification (e.g., for age and stigmata of hemorrhage) may be considered, especially in smaller studies. The patient and personnel providing care or recording information should be blinded. Inclusion criteria should be overt bleeding with endoscopy performed within 24 h or less. One type of lesion (e.g., ulcer) should be studied with stigmata to be included predefined. Use of placebo/no therapy vs. active controls depends on current standard practice. Standardizing study and key non-study interventions should ensure uniform provision of interventions. Criteria for repeat endoscopy and subsequent interventions should be predefined. The primary end point should be further bleeding (persistent and recurrent bleeding) with primary assessment at 7 days; mortality, with primary assessment at 30 days, would be appropriate in very large trials. Sample size calculation based on assumptions regarding primary end point results with regard to study intervention and control must be provided, and all patients enrolled must be accounted for. In general, the primary population for analysis is all patients randomized, although a per-protocol population may be used if this is the more conservative approach (e.g., equivalence study).
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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 | 0.834 | 0.829 |
| Meta-epidemiology (narrow) | 0.008 | 0.009 |
| Meta-epidemiology (broad) | 0.025 | 0.036 |
| Bibliometrics | 0.015 | 0.020 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.024 | 0.013 |
| Open science | 0.021 | 0.012 |
| Research integrity | 0.036 | 0.052 |
| Insufficient payload (model declined to judge) | 0.009 | 0.012 |
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".