Increased Risk of Severe Recurrence of Hepatitis C Virus in Liver Transplant Recipients of Donation After Cardiac Death Allografts
Bibliographic record
Abstract
BACKGROUND: In hepatitis C virus (HCV) recipients of donation after cardiac death (DCD) grafts, there is suggestion of lower rates of graft survival, indicating that DCD grafts themselves may represent a significant risk factor for severe recurrence of HCV. METHODS: We evaluated all DCD liver transplant recipients from August 2006 to February 2011 at our center. Recipients with HCV who received a DCD graft (group 1, HCV+ DCD, n=17) were compared with non-HCV recipients transplanted with a DCD graft (group 2, HCV- DCD, n=15), and with a matched group of HCV recipients transplanted with a donation after brain death (DBD) graft (group 3, HCV+ DBD, n=42). RESULTS: A trend of poorer graft survival was seen in HCV+ patients who underwent a DCD transplant (group 1) compared with HCV- patients who underwent a DCD transplant (group 2) (P=0.14). Importantly, a statistically significant difference in graft survival was seen in HCV+ patients undergoing DCD transplant (group 1) (73%) as compared with DBD transplant (group 3) (93%)(P=0.01). There was a statistically significant increase in HCV recurrence at 3 months (76% vs. 16%) (P=0.005) and severe HCV recurrence within the first year (47% vs. 10%) in the DCD group (P=0.004). CONCLUSIONS: HCV recurrence is more severe and progresses more rapidly in HCV+ recipients who receive grafts from DCD compared with those who receive grafts from DBD. DCD liver transplantation in HCV+ recipients is associated with a higher rate of graft failure compared with those who receive grafts from DBD. Caution must be taken when using DCD grafts in HCV+ recipients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".