Recipient factors associated with having a potential living donor for liver transplantation
Bibliographic record
Abstract
Because of a persistent discrepancy between the demand for liver transplantation (LT) and the supply of deceased donor organs, there is an interest in increasing living donation rates at centers trained in this method of transplantation. We examined a large socioeconomically heterogeneous cohort of patients listed for LT to identify recipient factors associated with living donation. We retrospectively reviewed 491 consecutive patients who were listed for LT at our center over a 24-month period. Demographic, medical, and socioeconomic data were extracted from electronic records and compared between those who had a potential living donor (LD) volunteer for assessment and those who did not; 245 patients (50%) had at least 1 potential LD volunteer for assessment. Multivariate logistic regression analysis identified that patients with a LD were more likely to have Child-Pugh C disease (odds ratio [OR], 2.44; P = 0.02), and less likely to be older (OR, 0.96; P = 0.002), single (OR, 0.34; P = 0.006), divorced (OR, 0.53; P = 0.03), immigrants (OR, 0.38; P = 0.049), or from the lowest income quintile (OR, 0.44; P = 0.02). In conclusion, this analysis has identified several factors associated with access to living donation. More research is warranted to define and overcome barriers to living donor liver transplantation through targeted interventions in underrepresented populations.
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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".