INFUSE: Rationale and design of a multi-center, open label, collaborative study to treat HRS-AKI with continuous terlipressin infusion
Bibliographic record
Abstract
Background: Hepatorenal syndrome-acute kidney injury (HRS-AKI) carries significant morbidity and mortality among those with end-stage liver disease. Bolus terlipressin for treatment of HRS-AKI received FDA approval in September 2022. US implementation of terlipressin, however, is hindered by the paucity of local data on the optimal patient population and administration mode, as well as the effect on transplant priority. The INFUSE study is designed to evaluate the use of continuous terlipressin infusion among transplant candidates with advanced liver disease and HRS-AKI. Methods: Fifty prospective patients with HRS-AKI will receive a single bolus of terlipressin 0.5 mg followed by continuous infusions of terlipressin from 2 to 8 mg/day for up to 14 days. The cohort will be enriched with those listed, in evaluation, or eligible for liver transplantation, while those with ACLF grade 3, MELD ≥35, and serum creatinine >5.0 mg/dL will be excluded. Fifty patients who received midodrine plus octreotide or norepinephrine for HRS-AKI will serve as a retrospective comparator cohort. Conclusion: The INFUSE study aims to assess the safety and efficacy of continuous terlipressin infusion among largely transplant-eligible patients with HRS-AKI, and to provide US-based data on transplant outcomes. This novel study design simultaneously mitigates terlipressin adverse events while providing renal benefits to patients, thus addressing the unmet medical need of those with HRS-AKI who have limited treatment options and are awaiting liver transplantation in the US.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".