Terlipressin for Hepatorenal Syndrome in Patients With Early‐Stage Acute‐on‐Chronic Liver Failure
Bibliographic record
Abstract
BACKGROUND & AIMS: Hepatorenal syndrome-acute kidney injury (HRS-AKI) is a life-threatening complication of decompensated cirrhosis. The US Food and Drug Administration approved terlipressin use for HRS-AKI based on the CONFIRM study, which demonstrated a significant improvement in HRS reversal with terlipressin versus placebo. The label notes elevated risk of respiratory failure in patients with volume overload or acute-on-chronic liver failure (ACLF) grade 3 and limited benefit when serum creatinine (SCr) exceeds 5 mg/dL. METHODS: We performed a post hoc analysis of CONFIRM excluding patients with ACLF grade 3 or SCr ≥ 5 mg/dL. This allowed us to assess the efficacy and safety of terlipressin in a population where the benefit-to-risk profile is more favourable. Efficacy outcomes included HRS reversal, renal replacement therapy (RRT), liver transplantation (LT), RRT-free survival, LT-free survival and overall survival. Changes in SCr, Model for End Stage Liver Disease (MELD) and sodium were also assessed. RESULTS: HRS reversal occurred in 43% (60/141) of patients with terlipressin versus 17% (13/75) with placebo (p < 0.001). Terlipressin was associated with significantly larger reductions (vs. placebo) in SCr (p < 0.001) and increases in serum sodium (p < 0.001). Importantly, LT rates were similar even though MELD scores decreased. 90-day survival was similar between treatment arms. Notably, selecting patients with a favourable benefit-to-risk profile led to a similar incidence of respiratory failure between treatment arms (11% with terlipressin vs. 7% with placebo; p = 0.360). CONCLUSIONS: In patients with HRS-AKI without baseline ACLF grade 3 or SCr ≥ 5 mg/dL, terlipressin improved clinical outcomes and was not associated with an increased risk of respiratory failure. TRIAL REGISTRATION: CONFIRM, ClinicalTrials.gov identifier: NCT02770716.
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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".