Acute Variceal Bleeding: Does Octreotide Improve Outcomes in Patients with Different Functional Hepatic Reserve?
Bibliographic record
Abstract
BACKGROUND: Current guidelines do not differentiate in the utilization of vasoactive drugs in patients with cirrhosis and acute variceal bleeding (AVB) depending on liver disease severity. MATERIAL AND METHODS: In this retrospective study, clinical outcomes in 100 patients receiving octreotide plus endoscopic therapy (ET) and 216 patients with ET alone were compared in terms of failure to control bleeding, in-hospital mortality, and transfusion requirements stratifying the results according to liver disease severity by Child-Pugh (CP) score and MELD. RESULTS: In patients with CP-A or those with MELD < 10 octreotide was not associated with a better outcome compared to ET alone in terms of hospital mortality (CP-A: 0.0 vs. 0.0%; MELD < 10: 0.0 vs. 2.9%, p = 1.00), failure to control bleeding (CP-A: 8.7 vs. 3.7%, p = 0.58; MELD < 10: 5.3 vs. 4.3%, p = 1.00) and need for transfusion (CP-A: 39.1 vs. 61.1%, p = 0.09; MELD < 10: 63.2 vs. 62.9%, p = 1.00). Those with severe liver dysfunction in the octreotide group showed better outcomes compared to the non-octreotide group in terms of hospital mortality (CP-B/C: 3.9 vs. 13.0%, p = 0.04; MELD ≥ 10: 3.9 vs. 13.3%, p = 0.03) and need for transfusion (CP-B/C: 58.4 vs. 71.6%, p = 0.05; MELD ≥ 10: 50.6 vs. 72.7%, p < 0.01). In multivariate analysis, octreotide was independently associated with in-hospital mortality (p = 0.028) and need for transfusion (p = 0.008) only in patients with severe liver dysfunction (CP-B/C or MELD ≥ 10). CONCLUSION: Patients with cirrhosis and AVB categorized as CP-A or MELD < 10 had similar clinical outcomes during hospitalization whether or not they received octreotide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".