Early Intervention With Live Donor Liver Transplantation Reduces Resource Utilization in NASH: The Toronto Experience
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In parallel with the obesity epidemic, liver transplantation for nonalcoholic steatohepatitis (NASH) is increasing dramatically in North America. Although survival outcomes are similar to other etiologies, liver transplantation in the NASH population has been associated with significantly increased resource utilization. We sought to compare outcomes between live donor liver transplantation (LDLT) and deceased donor liver transplantation (DDLT) at a high volume North American transplant center, with a particular focus on resource utilization. METHODS: The study population consists of primary liver transplants performed for NASH at Toronto General Hospital from 2000 to 2014. Recipient characteristics, perioperative outcomes, graft and patient survivals, and resource utilization were compared for LDLT versus DDLT. RESULTS: A total of 176 patients were included in the study (48 LDLT vs 128 DDLT). LDLT recipients had a lower model for end-stage liver disease score and were less frequently hospitalized prior to transplant. Estimated blood loss and early markers of graft injury were lower for LDLT. LDLT recipients had a significantly shorter hospitalization (intensive care unit, postoperative, and total hospitalization). CONCLUSIONS: LDLT for NASH facilitates transplantation of patients at a less severe stage of disease, which appears to promote a faster postoperative recovery with less resource utilization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it