Decreased need for RRT in liver transplant recipients after pretransplant treatment of hepatorenal syndrome-type 1 with terlipressin
Bibliographic record
Abstract
Hepatorenal syndrome-acute kidney injury (HRS-AKI), a serious complication of decompensated cirrhosis, has limited therapeutic options and significant morbidity and mortality. Terlipressin improves renal function in some patients with HRS-1, while liver transplantation (LT) is a curative treatment for advanced chronic liver disease. Renal failure post-LT requiring renal replacement therapy (RRT) is a major risk factor for graft and patient survival. A post hoc analysis with a 12-month follow-up of LT recipients from a placebo-controlled trial of terlipressin (CONFIRM; NCT02770716) was conducted to evaluate the need for RRT and overall survival. Patients with HRS-1 were treated with terlipressin plus albumin or placebo plus albumin for up to 14 days. RRT was defined as any type of procedure that replaced kidney function. Outcomes compared between groups included the incidence of HRS-1 reversal, the need for RRT (pretransplant and posttransplant), and overall survival. Of the 300 patients in CONFIRM (terlipressin n = 199; placebo, n = 101), 70 (23%) underwent LT alone (terlipressin, n = 43; placebo, n = 27) and 5 had simultaneous liver-kidney transplant (terlipressin, n = 3, placebo, n = 2). The rate of HRS reversal was significantly higher in the terlipressin group compared with the placebo group (37%, n = 16 vs. 15%, n = 4; p = 0.033). The pretransplant need for RRT was significantly lower among those who received terlipressin ( p = 0.007). The posttransplant need for RRT, at 12 months, was significantly lower among those patients who received terlipressin and were alive at Day 365, compared to placebo ( p = 0.009). Pretransplant treatment with terlipressin plus albumin in patients with HRS-1 decreased the need for RRT pretransplant and posttransplant.
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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) | 0.001 | 0.001 |
| 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".