A Risk Assessment of Factors for the Presence of Angiodysplasias During Endoscopy and Factors Contributing to Symptomatic Bleeding and Rebleeds
Bibliographic record
Abstract
BACKGROUND: Few studies have assessed factors associated with angiodysplasias during endoscopy or factors associated with symptomatic disease. AIMS: To evaluate risk factors for the presence of and contribution to symptomatic disease in patients with angiodysplasias. METHODS: We performed a systematic MEDLINE, EMBASE and Cochrane Library search according to the PRISMA guidelines for studies assessing risk factors involved in angiodysplasias detected during endoscopy and factors that lead to anemia or overt bleeding. Study quality was assessed with the Newcastle-Ottawa scale. A risk assessment was performed by selecting risk factors identified by two independent studies and/or by a large effect size. RESULTS: Twenty-three studies involving 92,634 participants were included. The overall quality of the evidence was moderate. Risk factors for the diagnosis of angiodysplasias during endoscopy confirmed by at least two studies were increasing age (OR 1.09 per year, 95% CI 1.04-1.1), chronic kidney disease (OR 4.5, 95% CI 1.9-10.5) and cardiovascular disease (2.9, 95% CI 1.4-6.2). The risk of rebleeds was higher in the presence of multiple lesions (OR 4.2, 95% CI 1.1-16.2 and 3.8, 95% CI 1.3-11.3 and 8.6, 95% CI 1.4-52.6), liver cirrhosis (OR 4.0, 95% 1.1-15.0) and prothrombin time < 30% (OR 4.2, 95% 1.1-15.4) with a moderate effect size. Multiple comorbidities were associated with an increased in-hospital mortality (OR 2.29, 95% CI 1.2-4.3). CONCLUSIONS: This systematic review identified age, chronic kidney disease and cardiovascular disease as the most important risk factors for the diagnosis of angiodysplasias during endoscopy. Multiple lesions increase the risk of recurrent bleeding.
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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 | 0.022 | 0.082 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.016 |
| Bibliometrics | 0.016 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".