Clinical trial: short‐term effects of combination of satavaptan, a selective vasopressin V<sub>2</sub> receptor antagonist, and diuretics on ascites in patients with cirrhosis without hyponatraemia – a randomized, double‐blind, placebo‐controlled study
Bibliographic record
Abstract
BACKGROUND: There is little information on the effects of vaptans in patients with cirrhosis. AIM: To investigate the short-term effects of satavaptan, a selective vasopressin V2 receptor antagonist on ascites in cirrhosis without hyponatraemia. METHODS: A total of 148 patients with cirrhosis, ascites and serum sodium >130 mmol/L were included in a multicentre, double-blind, randomized, controlled study of 14 days comparing three fixed doses of satavaptan (5 mg, 12.5 mg or 25 mg once daily) vs. placebo. Average MELD scores were: 13.4, 12.3, 13.8 and 13.1 respectively. All patients received spironolactone 100 mg/day plus furosemide 20-25 mg/day. RESULTS: Satavaptan treatment was associated with a decrease in ascites (mean change in body weight was -0.36 kg (+/-3.03) for placebo vs. -2.46 kg (+/-3.11), -2.08 kg (+/-4.17) and -2.28 kg (+/-3.24) for the 5 mg, 12.5 mg and 25 mg doses respectively; P = 0.036, P = 0.041 and P = 0.036 for satavaptan 5, 12.5 and 25 mg/day vs. placebo respectively). Thirst and slight increases in serum sodium were more common in patients treated with satavaptan compared with placebo, while other adverse events were similar. CONCLUSIONS: The administration satavaptan for a 14-day period is associated with reduction in ascites in patients with moderately severe cirrhosis without hyponatraemia under diuretic treatment.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".