Sarcopenia Predicts Post-transplant Mortality in Acutely Ill Men Undergoing Urgent Evaluation and Liver Transplantation
Bibliographic record
Abstract
BACKGROUND: We examined the association between sarcopenia and post-transplant mortality in acutely ill inpatients with cirrhosis who underwent urgent liver transplantation. METHODS: Included were inpatients at 4 centers who were urgently listed as nonstatus 1 and transplanted from 2005 to 2017 with an abdominal computed tomography scan <90 days before transplantation. Skeletal muscle index (SMI) = total skeletal muscle cross-sectional area at the L3 vertebral level, normalized to height. Cox regression associated SMI with post-transplant mortality. Optimal search identified SMI cutoffs to detect survival. RESULTS: Of 126 inpatients, 63% were male patients, model for end-stage liver disease (MELDNa) was 32, and follow up was 5.1 years. Among men, 23% died. Median SMI was lower in men who died versus survived (45 versus 51 cm/m). SMI was associated with post-transplant mortality (hazard ratio [HR] = 0.96 per cm/m, 95% CI 0.92-0.99). Patients with SMI ≤ 48 cm/m versus >48 cm/m experienced higher rates of death at 1 year (86% versus 95%) and 3 years (73% versus 95%) (Log-rank P = 0.01). In MELD-adjusted analysis, sarcopenia was strongly associated with post-transplant mortality (HR = 4.39, 95% CI 1.49-12.97). Among women, 35% died. Median SMI was similar in women who died versus survived (45 versus 44 cm/m). SMI was not associated with post-transplant mortality (HR = 1.02, 95% CI 0.96-1.09). Optimal search did not identify any SMI cutoff that predicted post-transplant mortality. CONCLUSIONS: Among patients who underwent urgent inpatient evaluation and liver transplantation, we identified an SMI cutoff value of 48 cm/m to predict post-transplant mortality in men. Our data support the use of SMI as a tool to capture the impact of muscle depletion on post-transplant mortality in acutely ill men with cirrhosis undergoing urgent liver transplantation.
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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".