Practices in Peptic Ulcer Bleeding Controversies among University‐ Versus Nonuniversity‐Affiliated Gastroenterologists
Bibliographic record
Abstract
BACKGROUND: Practices relating to acute peptic ulcer bleeding (APUB) outside of guideline recommendations are unknown. OBJECTIVE: To evaluate the practices of university-affiliated (UA) versus nonuniversity-affiliated (non-UA) gastroenterologists in controversial APUB issues. METHODS: Gastroenterologists in Canada were mailed an anonymous questionnaire (January 2008) regarding APUB management. RESULTS: Responses were received for 281 of the 530 questionnaires mailed (53%). There were no differences between the UA versus non-UA gastroenterologists regarding acid suppression medication and route of administration pre- and postendoscopy (all P>0.05). There were no differences in endoscopic practices between groups regarding large versus small volume injection, endoclip versus combination injection plus coagulation, endoclip versus endoclip plus injection, and management of adherent clots (all P>0.05). There was variability within each group regarding optimal empirical acid suppression pre- and postendoscopy, volume of injection therapy and endoclip use. The non-UA group had longer delays before restarting acetylsalicyclic acid (P=0.08) and warfarin (P=0.02) post-APUB. CONCLUSIONS: UA and non-UA gastroenterologists have similar practices in acid suppression and endoscopic therapy for controversial APUB issues; however, non-UA gastroenterologists appear more cautious in restarting acetylsalicylic acid and warfarin. Further studies are needed to address the optimal empirical acid suppression pre- and postendoscopy, injection therapy volume, endoclip use, and timing of restarting antiplatelet and anticoagulation therapy.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".