Review article: Advances in the management of lower gastrointestinal bleeding
Bibliographic record
Abstract
BACKGROUND: Lower gastrointestinal bleeding (LGIB) is a common emergency with substantial associated morbidity and mortality. Elective colonoscopy plays an essential role in management, with an even more important role for radiology in the acute setting. Recent advances in the management of patients with LGIB warrant review as the management has recently evolved. AIMS: To provide a comprehensive and updated overview of advances in the approach to patients with LGIB METHODS: We performed a comprehensive literature search to examine the current data for this narrative review supplemented by expert opinion. RESULTS: The incidence of LGIB is increasing worldwide, partly related to an ageing population and the increasing use of antithrombotics. Diverticulosis continues to be the most common aetiology of LGIB. Pre-endoscopic risk stratification tools, especially the Oakland score, can aid appropriate patient triage. Adequate resuscitation continues to form the basis of management, while appropriate management of antithrombotics is crucial to balance the risk of worsening bleeding against increased cardiovascular risk. Radiological imaging plays an essential role in the diagnosis and treatment of acute LGIB, especially among unstable patients. Colonoscopy remains the gold-standard test for the elective management of stable patients. CONCLUSIONS: The management of LGIB has evolved significantly in recent years, with a shift towards radiological interventions for unstable patients while reserving elective colonoscopy for stable patients. A multidisciplinary approach is essential to optimise the outcomes of patients with LGIB.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".