β-blockers in advanced cirrhosis: More friend than enemy
Bibliographic record
Abstract
Nonselective beta-adrenergic blocker (NSBB) therapy for the prevention of initial and recurrent gastrointestinal bleeding in cirrhotic patients with gastroesophageal varices has been used for the past four decades. NSBB therapy is considered the cornerstone of treatment for varices, and has become the standard of care. However, a 2010 study from the group that pioneered β-blocker therapy suggested a detrimental effect of NSBBs in decompensated cirrhosis, especially in patients with refractory ascites. Since then, numerous additional studies have incompletely resolved whether NSBBs are deleterious, although more recent evidence weighs against a harmful effect. The possibility of a "therapeutic window" has also been raised. We aimed to review the literature to analyze the pros and cons of using NSBBs in patients with cirrhosis, not only with respect to bleeding or mortality but also to other potential benefits and risks. β-blockers are highly effective in preventing first bleeding and recurrent bleeding. Furthermore, NSBBs improve congestion/ischemia of the gut mucosa, decrease intestinal permeability, and therefore indirectly alleviate systemic inflammation. β-blockers shorten the electrocardiographic prolonged QTc interval and may also decrease the incidence of hepatocellular carcinoma. On the other hand, the possibility of deleterious effects in cirrhosis has not been completely eliminated. NSBBs may be associated with an increased risk of portal vein thrombosis, although this could be correlational artifact. Overall, we conclude that β-blockers in cirrhosis are much more of a friend than enemy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".