Terlipressin May Decrease In-Hospital Mortality of Cirrhotic Patients with Acute Gastrointestinal Bleeding and Renal Dysfunction: A Retrospective Multicenter Observational Study
Bibliographic record
Abstract
BACKGROUND: Acute gastrointestinal bleeding (GIB) rapidly reduces effective blood volume, thereby precipitating acute kidney injury (AKI). Terlipressin, which can induce splanchnic vasoconstriction and increase renal perfusion, has been recommended for acute GIB and hepatorenal syndrome in liver cirrhosis. Thus, we hypothesized that terlipressin might be beneficial for cirrhotic patients with acute GIB and renal impairment. METHODS: In this Chinese multi-center study, 1644 cirrhotic patients with acute GIB were retrospectively enrolled. AKI was defined according to the International Club of Ascites (ICA) criteria. Renal dysfunction was defined as serum creatinine (sCr) > 133 μmol/L at admission and/or any time point during hospitalization. Incidence of renal impairment and in-hospital mortality were the primary end-points. RESULTS: The incidence of any stage ICA-AKI, ICA-AKI stages 1B, 2, and 3, and renal dysfunction in cirrhotic patients with acute GIB was 7.1%, 1.8%, and 5.0%, respectively. The in-hospital mortality was significantly increased by renal dysfunction (14.5% vs. 2.2%, P < 0.001) and ICA-AKI stages 1B, 2, and 3 (11.1% vs. 2.8%, P = 0.011), but not any stage ICA-AKI (5.7% vs. 2.7%, P = 0.083). The in-hospital mortality was significantly decreased by terlipressin in patients with renal dysfunction (3.6% vs. 20.0%, P = 0.044), but not in those with any stage ICA-AKI (4.5% vs. 6.0%, P = 0.799) or ICA-AKI stages 1B, 2, and 3 (0.0% vs. 14.3%, P = 0.326). CONCLUSION: Renal dysfunction increased the in-hospital mortality of cirrhotic patients with acute GIB. Terlipressin might decrease the in-hospital mortality of cirrhotic patients with acute GIB and renal dysfunction. TRIAL REGISTRATION: NCT03846180 ( https://clinicaltrials.gov ).
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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 | 0.000 | 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".