Routine Second-Look Endoscopy: Ineffective, Costly, and Potentially Misleading
Bibliographic record
Abstract
Despite the best medical and endoscopic efforts, some patients with nonvariceal upper gastrointestinal bleeding suffer recurrences. Because high risk stigmata (visible vessels, active bleeders and adherent clots) often persist despite apparently successful initial hemostasis and have a variable natural history, it would seem reasonable to at least consider a routine second look endoscopy. However, a review of the literature revealed six randomized trials that, in aggregate, do not support such a strategy. In fact, a second look does not appear to be effective and is associated with an increased number of procedures, treatment sessions and possibly retreatment-related complications. In addition, the cointerventions in these trials are already out of date and the potential absolute risk reductions are low when a second look is used with intravenous proton pump inhibitors and/or the application of endoscopic hemoclips or combination endoscopic therapy. Finally, the Forrest classification may provide dangerously misleading estimates of prognosis because it is being used out of context. This review critically analyzes routine second look endoscopy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".