Defining Renal Recovery in Patients With Hepatorenal Syndrome‐Acute Kidney Injury: Experience From North American Studies
Bibliographic record
Abstract
ABSTRACT Introduction The degree of improvement in serum creatinine (SCr) has previously been suggested as a sensitive indicator of treatment response in patients with hepatorenal syndrome‐acute kidney injury (HRS‐AKI), while HRS reversal remains the primary endpoint in clinical trials. Methods A total of ≥ 30% SCr improvement was analyzed as an exploratory prespecified endpoint in the CONFIRM trial. In this post hoc analysis, intent‐to‐treat population data from three Phase 3 studies (OT‐0401, REVERSE, and CONFIRM) conducted in North America in patients with HRS‐AKI were pooled to assess the incidence of > 30% improvement in SCr and its association with clinical outcomes. Results Significantly more patients treated with terlipressin achieved > 30% improvement in SCr compared with those who received a placebo (42.9% vs. 23.4%; p < 0.001). Compared with patients who did not achieve > 30% improvement in SCr, those who achieved this threshold had a lower incidence of renal replacement therapy (RRT) (55.2% vs. 14%, respectively; p < 0.001) and greater overall survival at Day 90 (41.6% vs. 71.1%, respectively; p < 0.001); a greater proportion achieved durability of HRS reversal (1% [95% confidence interval, 95% CI: 0] vs. 68.9% [95% CI: 0.6, 0.8]) and more patients were alive without RRT (22.7% vs. 61.6%, respectively; p < 0.001) or transplant (11.6% vs. 43.0%, respectively; p < 0.0001). Additionally, the overall survival and RRT‐free survival in the group that achieved > 30% improvement in SCr without HRS reversal were comparable to the overall group that achieved HRS reversal. Conclusion A total of > 30% improvement in SCr levels even without HRS reversal may serve as a clinically meaningful endpoint to define renal recovery in patients with HRS‐AKI.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".