Predictors of Clinically Significant Upper Gastrointestinal Hemorrhage Among Children With Hematemesis
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to determine the proportion of children with hematemesis who experience a clinically significant upper gastrointestinal hemorrhage (UGIH) and to identify variables predicting their occurrence. METHODS: A retrospective cohort study was conducted. All of the emergency department visits by children ages 0 to 18 years who presented with hematemesis between 2000 and 2007 were reviewed. The primary aim of the study was to determine the proportion of children who developed a clinically significant UGIH; the secondary aim was to identify risk factors predictive of a clinically significant UGIH. A significant UGIH was defined by any of the following: hemoglobin drop >20 g/L, blood transfusion, or emergent endoscopy or surgical procedure. RESULTS: Twenty-seven of 613 eligible children (4%; 95% confidence interval 3%-6%) had a clinically significant UGIH. Clinically significant hemorrhages were associated with older age (9.7 vs 2.9 years; P<0.001), vomiting moderate to large amounts of fresh blood (58% vs 20%; P<0.001), melena (37% vs 5%; P<0.001), significant medical history (63% vs 24%; P<0.001), unwell appearance (44% vs 6%; P<0.001), and tachycardia (41% vs 10%; P<0.001). The frequency of laboratory investigations increased with age (P<0.001). The hemoglobin level was the only laboratory investigation whose results differed between those with and without significant bleeds. The presence of any one of the following characteristics identified all of the children with a clinically significant hemorrhage: melena, hematochezia, unwell appearance, or a moderate to large volume of fresh blood in the vomitus, sensitivity 100% (95% confidence interval 85%-100%). CONCLUSIONS: The occurrence of a clinically significant UGIH was uncommon among children with hematemesis, especially in well-appearing children without melena, hematochezia, or who had not vomited a moderate to large amount of fresh blood.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".