Meta‐analysis: vasoactive medications for the management of acute variceal bleeds
Bibliographic record
Abstract
BACKGROUND: Vasoactive medications such as vasopressin, somatostatin and their analogues (terlipressin, vapreotide and octreotide) are commonly used for the treatment of acute variceal bleeding. However, the risks and benefits of these interventions are not well understood. AIM: To undertake a meta-analysis of the efficacy of vasoactive medications in patients having acute variceal bleeds. METHODS: Randomised controlled trials (RCTs) of vasopressin, somatostatin and their analogues, administered to patients with acute variceal bleeds were identified based on systematic searches of nine electronic databases and multiple sources of grey literature. RESULTS: The search identified 3011 citations, and 30 trials with a total of 3111 patients met eligibility criteria. The use of vasoactive agents was associated with a significantly lower risk of 7-day mortality (RR 0.74; 95% CI 0.57-0.95; P = 0.02; I(2) = 0%; moderate quality of evidence), and a significant improvement in haemostasis (RR 1.21, 95% CI 1.13-1.30; P < 0.001; I(2) = 28%; very low quality of evidence), lower transfusion requirements (pooled mean difference -0.70 units of blood transfused, 95% CI -1.01 to -0.38; P < 0.001; I(2) = 82%; moderate quality of evidence), and a shorter duration of hospitalisation (pooled mean difference -0.71 days; 95% CI -1.23 to -0.19; P = 0.007; I(2) = 0%; low quality of evidence). Studies comparing different vasoactive agents did not show a difference in efficacy, although the quality of evidence was very low. CONCLUSIONS: The use of vasoactive agents was associated with a significantly lower risk of acute all-cause mortality and transfusion requirements, and improved control of bleeding and shorter hospital stay. Studies comparing different vasoactive medications failed to demonstrate a difference in efficacy.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.052 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".