Factor V Serves as an Early Biomarker for Graft Loss After Liver Transplant: A Prospective Evaluation
Bibliographic record
Abstract
BACKGROUND: Low post-operative day (POD) 1 Factor V has been retrospectively associated with graft loss after liver transplantation when stratified by a cutoff of 0.36 U/mL. We aimed to validate this prospectively. METHODS: Patients transplanted at Toronto General Hospital were recruited (May 2018-March 2021). Factor V measurements were obtained on POD1-3, 5, and 7. Graft and patient survival at 3, 6, and 12 months were primary and secondary outcomes, respectively. We identified an optimal cutoff through receiver operating characteristic (ROC) analysis and the Youden index. Kaplan-Meier method and Log-rank tests were used to assess/compare survival. RESULTS: One hundred and twenty-nine patients were included. One hundred and eight had Factor V >0.36 and 21 had ≤0.36 U/mL. This cutoff was predictive of 6- and 12-month graft survival and 12-month patient survival. With an optimal cutoff of 0.46 U/mL on POD1, 87 patients had Factor V >0.46 and 42 had ≤0.46 U/mL. Three-, 6-, and 12-month graft survival rates were 100%, 98.8%, and 98.8%, for patients with Factor V >0.46 U/mL, and 92.9%, 87.7%, and 87.7% for Factor V ≤0.46 U/mL. Similarly, 3-, 6-, and 12-month patient survival rates were 98.8%, 96.4%, and 95.0% for patients with Factor V >0.46 U/mL, and 92.9%, 88.0%, and 82.9% for Factor V ≤0.46 U/mL. Stratification below the novel cutoff was associated with decreased graft survival at months 3 (p = 0.012), 6 (p = 0.006), and 12 (p = 0.006), and decreased patient survival at 12 months (p = 0.022). CONCLUSIONS: Factor V serves as an early biomarker for graft loss, with an optimal predictive cutoff of 0.46 U/mL in this prospective population. Validation of this new cutoff is necessary.
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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".