Diagnostic and therapeutic yields of balloon-assisted enteroscopy on different subtypes of patients with suspected small bowel bleeding
Bibliographic record
Abstract
Background: Small bowel bleeding accounts for about 5%-8% of all cases of gastrointestinal bleeding. Suspected small bowel bleeding (SSBB) can be classified into occult, inactive overt, and overt. Most patients with SSBB will undergo balloon-assisted enteroscopy (BAE) for diagnosis and treatment. There are currently no recommendations from practice guidelines on what is the best approach and limited information about diagnostic and therapeutic yields for each subtype of SSBB. Aims and Methods: We aimed to investigate the diagnostic and therapeutic yields of BAE in the 3 subtypes of patients with SSBB by performing a retrospective analysis of all patients that underwent BAE for this diagnosis at the University of Alberta Hospital in a 5-year period. We also aimed to identify other factors that could influence diagnostic and therapeutic yields. Results: < .05), respectively. BAE performed within 72 hours of presentation and patients requiring transfusion within the past 12 months had a significantly higher diagnostic yield. Conclusions: Our data showed the clinical differences between the 3 subtypes of patients with SSBB and the usefulness of an appropriate and timely approach to maximize the diagnostic and therapeutic yields.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".