Mortality Risk Factors Among Patients With Cirrhosis and a Low Model for End-Stage Liver Disease Sodium Score (≤15): An Analysis of Liver Transplant Allocation Policy Using Aggregated Electronic Health Record Data
Bibliographic record
Abstract
Although the Model for End-Stage Liver Disease sodium (MELD Na) score is now used for liver transplant allocation in the United States, mortality prediction may be underestimated by the score. Using aggregated electronic health record data from 7834 adult patients with cirrhosis, we determined whether the cause of cirrhosis or cirrhosis complications was associated with an increased risk of death among patients with a MELD Na score ≤15 and whether patients with the greatest risk of death could benefit from liver transplantation (LT). Over median follow-up of 2.3 years, 3715 patients had a maximum MELD Na score ≤15. Overall, 3.4% were waitlisted for LT. Severe hypoalbuminemia, hepatorenal syndrome, and hepatic hydrothorax conferred the greatest risk of death independent of MELD Na score with 1-year predicted mortality >14%. Approximately 10% possessed these risk factors. Of these high-risk patients, only 4% were waitlisted for LT, despite no difference in nonliver comorbidities between waitlisted patients and those not listed. In addition, risk factors for death among waitlisted patients were the same as those for patients not waitlisted, although the effect of malnutrition was significantly greater for waitlisted patients (hazard ratio 8.65 [95% CI 2.57-29.11] vs. 1.47 [95% CI 1.08-1.98]). Using the MELD Na score for allocation may continue to limit access to LT.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".