Recipient ineligibility after liver transplantation assessment: a single centre experience
Bibliographic record
Abstract
BACKGROUND: Candidacy for liver transplantation is determined through standardized evaluation. There are limited data on the frequency and reasons for denial of transplantation after assessment; analysis may shed light on the short-term utility of the assessment. We sought to describe the frequency and reasons for ineligibility for liver transplantation among referred adults. METHODS: We studied all prospectively followed recipient candidates at a single centre who were deemed unsuitable for liver transplantation after assessment. Inclusion criteria were age 18 years and older and completion of a standard liver transplantation evaluation over a 3-year period. Patients were excluded if they had a history of prior assessment or liver transplantation within the study period. Demographic and baseline clinical data and reasons for recipient ineligibility were recorded. RESULTS: In all, 337 patients underwent their first liver transplantation evaluation during the study period; 166 (49.3%) fulfilled inclusion criteria. The mean age was 55.4 years, and 106 (63.9%) were men. The 3 most common reasons for denial of listing were patient too well (n = 82, 49.4%), medical comorbidities and/or need for medical optimization (n = 43, 25.9%) and need for addiction rehabilitation (n = 28, 16.9%). CONCLUSION: Ineligibility for transplantation after assessment was common, occurring in nearly half of the cohort. Most denied candidates could be identified with more discriminate screening before the resource-intensive assessment; however, the assessment likely provides unforeseen positive impacts on patient care.
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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) | 0.002 | 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".