Time trends of causes of upper gastrointestinal bleeding and endoscopic findings
Bibliographic record
Abstract
BACKGROUND: Upper gastrointestinal bleeding (UGIB) is a frequent cause for emergency endoscopy and, in a proportion, requires the application of endotherapy. We aim to evaluate the proportion of variceal and nonvariceal upper gastrointestinal bleeding (NVUGIB), the endoscopic findings that were detected, as well as the temporal trends of endoscopic findings over a period of 13 years. METHODS: This is a retrospective study of patients who underwent an esophagogastroduodenoscopy with an indication of UGIB or presented with hematemesis, melena, or both, as well as those who had hematochezia, from January 2004 to December 2016 (13 years). RESULTS: A total of 2075 patients were included with a mean age of 56.8 years (range 18-113) and males constituted 67.9%, while 65.9% had at least one comorbidity. Symptoms on presentation included hematemesis (52.5%), melena (31.2%), both hematemesis & melena (15.1%), and hematochezia (1.2%). The majority of UGIB were from a NVUGIB source (80.5%) and a variceal source was found in 13.1%, while no endoscopic findings were found in 6.4% of cases. The most common endoscopic diagnosis was gastroduodenal erosions (23.8%), duodenal ulcers (23.5%), reflux esophagitis (16.0%), esophageal varices (12.1%), and gastric ulcers (10.8%). There was no change in the endoscopic findings over the time period of the study. A third of duodenal ulcers (33.3%) as well as 21.9% of gastric ulcers were actively bleeding at the time of endoscopy, while 3.3% of duodenal ulcers had an adherent clot. CONCLUSIONS: NVUGIB composed the majority of cases presenting with UGIB and variceal bleeding was lower than that described in prior studies, but there were no clear trends in the proportion of causes of UGIB during the study duration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".