Early Diagnosis and Timely Terlipressin in Hepatorenal Syndrome Improves Projected Outcomes and Lowers Cost
Bibliographic record
Abstract
Introduction: Terlipressin is the only Food and Drug Administration-approved medication for adults with hepatorenal syndrome-acute kidney injury (HRS-AKI) with rapid reduction in kidney function. Treatment with terlipressin, particularly in patients with lower serum creatinine (SCr) at diagnosis, improves outcomes. Despite evidence suggesting that treating HRS-AKI at lower SCr thresholds may improve clinical outcomes, the impact on healthcare resource utilization (HCRU) and medical costs of an earlier intervention strategy remains unquantified. This model-based analysis was conducted from a United States hospital perspective to project the clinical and economic impact of early HRS-AKI diagnosis and treatment with terlipressin among adults. Methods: A decision-analytic model compared two SCr level-based scenarios and projected the outcomes for both scenarios. For current clinical practice, patient distribution was based on the CONFIRM trial (SCr <3 mg/dL: 45% and ≥3 to <5 mg/dL: 55%). For early diagnosis and treatment, distribution was based on the HRS medical chart review study (<3 mg/dL: 85% and ≥3 to <5 mg/dL: 15%). Terlipressin HRS reversal rate for the on-label population (SCr <5 mg/dL and acute-on-chronic liver failure grade 0-2) was 52.2% for SCr <3 mg/dL and 33.3% for SCr ≥3 to <5 mg/dL. An annual HRS incidence of 50,000 was assumed. Results: Based on the modeled projections, early diagnosis and treatment with terlipressin versus current practice yielded an additional 3040 HRS reversals and consequently led to a reduction in hospital days and intensive care unit days. Early intervention resulted in 960 fewer patients requiring renal replacement therapy during hospitalization and 1200 more patients with 90-day transplant-free survival. Early intervention is projected to save $11,504 per patient, with total national savings of $460.2 million annually. Conclusion: Based on the modeled projections using data from clinical trial, earlier HRS diagnosis and treatment with terlipressin may improve clinical outcomes, reduce HCRU, and save costs versus current clinical practice.
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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 | 0.001 | 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".