Prediction of Bleeding Etiology: The Clinician is Vindicated!
Bibliographic record
Abstract
G astrointestinal (GI) bleeding is associated with significant mor- bidity and mortality.Variceal bleeds are significantly more lifethreatening than nonvariceal bleeds, with mortality rates of 18% in variceal bleeds (1) versus 5% in nonvariceal bleeds (2).Determining the acuity of the bleed is important to ensure that therapeutic upper endoscopy is performed within a window of time that balances mortality risk against optimal use of a limited resource.Several prediction scores have been proposed to risk stratify patients with upper GI bleeds, including the Rockford and Blatchford scales (3,4).These scores are, however, limited because they do not discriminate between GI bleeds of variceal and nonvariceal origin.This is a crucial distinction because management is different.In the current issue of the Canadian Journal of Gastroenterology, Alharbi et al (5) (pages 187-192) investigate preprocedure characteristics of patients ultimately diagnosed with variceal and nonvariceal upper GI bleeds.The patients were enrolled in the REgistry of patients undergoing endoscopic and/or Acid Suppression therapy and Outcomes analysis for upper gastrointestinal bleediNg (REASON) trial, with an aim to identify patient characteristics that distinguish variceal bleeds from nonvariceal bleeds.This multicentre, Canadian study conducted over an 18-month period found 11% of upper GI hemorrhages to be secondary to varices, which is similar to the rate found in the United Kingdom (6).Thirty-day mortality rates were significant for nonvariceal bleeds (9.4%) and 14.4% for variceal bleeds.After multivariate analysis, statistically significant risk factors associated with a variceal bleed included a history of liver disease, the presence of any stigmata of liver disease, alcohol abuse, hematemesis and hematochezia.This study also provides a unique snapshot of the management of GI bleeds in a very large geographical area.While outcome comparisons among centres were not reported, as a whole, mortality figures were similar to those reported in other western societies.Somewhat surprisingly, in 42% of cases, a rectal examination appeared not to be performed.In 19% of cases, a fecal occult blood test from a stool sample was performed -a test that has no utility in the context of an upper GI bleed (however, these fecal occult blood tests may have been performed by nongastroenterologists).Given that definitive management of variceal and nonvariceal upper GI bleeds is different, as are the transfusion goals and adjunct therapy (albumin and antibiotics in variceal bleeding), better methodology to discriminate variceal from nonvariceal bleeding has the potential to improve patient outcomes through earlier recognition.Previous work has investigated predictive factors of who will experience poor outcomes with a GI bleed (ie, the Rockford and Blatchford scales).These scales have been validated in real-world populations of patients presenting with both variceal and nonvariceal bleeding (3,4).An extension of this concept is to predict which patients are likely to experience variceal bleeds before a potentially life-threatening bleeding episode.This includes measuring liver stiffness through transient elastography (7) and biochemical parameters such as a platelet to spleen ratio (8,9).Unfortunately, a diagnosis of cirrhosis is often made at the time of a variceal bleed, limiting the utility of these techniques,
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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.021 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 0.007 |
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".