The Effect of Terlipressin on Renal Replacement Therapy in Patients with Hepatorenal Syndrome
Bibliographic record
Abstract
Key Points Hepatorenal syndrome type 1 (HRS-1) is an often fatal, but potentially reversible, kidney failure in patients with decompensated cirrhosis. Treatment with terlipressin in patients with HRS-1 is associated with a reduction in the need for RRT. Background Hepatorenal syndrome type 1 (HRS-1)—also known as hepatorenal syndrome-AKI (HRS-AKI)—is a rapidly progressing and usually fatal, but potentially reversible, kidney failure occurring in patients with decompensated cirrhosis. A large proportion of patients with HRS-1 require renal replacement therapy (RRT). Terlipressin demonstrated efficacy in reversing HRS and improving renal function in patients with HRS-1 in three phase III, randomized, clinical trials (RCTs; i.e. , OT-0401, REVERSE, and CONFIRM). However, these RCTs were not designed to evaluate the effect of terlipressin on the requirement of RRT. In this study, the effect of terlipressin on RRT requirements in the pooled phase III patient population was assessed. Methods For this retrospective analysis, data from patients who participated in the OT-0401, REVERSE, and CONFIRM studies were integrated in the largest-to-date randomized database ( N =608). Results The need for RRT was significantly decreased in patients in the terlipressin group versus the placebo group by day 30 (28.1% versus 35.9%, respectively; P = 0.040) and day 60 (30.1% versus 37.9%, respectively; P = 0.045) in the pooled population and also postliver transplantation (LT) at day 60 (20.5% versus 40.3%, respectively; P = 0.008) and day 90 (25.3% versus 43.1%, respectively; P = 0.018). More patients were alive and RRT-free by day 90 in the overall population (36.9% versus 28.5%; P = 0.030) and among patients who received an LT (60.0% versus 39.7%; P = 0.010). Random assignment to receive terlipressin was an independent positive predictor of avoidance of RRT ( P = 0.042); while higher baseline serum creatinine (sCr) level and Child-Pugh scores were negatively associated with RRT avoidance ( P < 0.001 and P = 0.040, respectively). Conclusions Terlipressin decreased the requirement of RRT compared with placebo among patients with HRS-1, including those receiving LT. A lower sCr level at the beginning of therapy was associated with avoidance of RRT.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.001 |
| 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".