Preliminary Results in the Development of A Generic Transplant Function Rating System
Bibliographic record
Abstract
IntroductionA unique challenge to clinical trials in deceased donor care is the integration of outcomes from the recipients of potentially many organs (kidneys, liver, lungs, heart, pancreas, intestine) from a single donor. MethodsIn consultation with experts in research methodology, biostatistics, and multi-organ transplantation, we sought to develop a generic rating system of transplant function that is easy to apply (less than 1 minute by a transplant physician) using routine clinical data, at a specific, early post-operative point in time. We aimed for a surrogate measure of long-term graft function, survival, and quality of life. Working iteratively with clinical experts, and taking into consideration the early and late post-operative courses across organ types, we sought to unify key concepts of normal, impaired, severely impaired, and irreversible loss of graft function. Simple, organ-specific guides to apply this instrument are informed by organ-specific systematic reviews to identify all independent predictors of graft loss post-transplantation.ResultsFigure 1 shows the current generic instrument. Clinical experts rate organ function at a single point in time: i) at hospital discharge, ii) death, or iii) 28 days, when hospitalization is prolonged. When function is impaired, they consider the expected trajectory. Conceptually, severe impairment in graft function refers to a 25% probability of irreversible graft loss after one year. For recipients who die in hospital, cause of death is judged as: due to graft dysfunction, related to graft dysfunction, or unrelated to graft dysfunction. Organ-specific systematic reviews are at various stages of completion, with a registered protocol (PROSPERO).ConclusionWe have developed a generic system for rating graft function following transplantation that has face validity among collaborating transplant experts and research methodologists. Research application will depend upon future validation studies including retrospective and prospective clinical application in Canadian and international transplant centers.
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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 | 0.109 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".