Banff 2022 Vascularized Composite Allotransplantation Meeting Report: Diagnostic criteria for vascular changes
Bibliographic record
Abstract
As more data become available, the Banff 2007 working classification of skin-containing vascularized composite allograft (VCA) pathology is expected to evolve and develop. This report represents the Banff VCA Working Group's consensus on the first revision of the 2007 scoring system. Prior to the 2022 Banff-CanXadian Society of Transplantation Joint Meeting, 83 clinicians and/or researchers were invited to a virtual meeting to discuss whether the 2007 Banff VCA system called for a revision. Unanimously, it was determined that the vascular changes were to be included in the first revision. Subsequently, 2 international online surveys, each followed by virtual discussions, were launched. The goals were (1) to identify which changes define severe rejection, (2) to grade their importance in the evaluation of severe rejection, and (3) to identify emerging criteria to diagnose rejection. A final hybrid (in-person and virtual) discussion at the Banff/Canadian Society of Transplantation Joint Meeting finalized the terminology, the definition, a scoring system, and a reporting system of the vascular changes. This proposal represents an international consensus on this topic and establishes the first revision of the Banff 2007 working classification of skin-containing vascularized composite allograft pathology.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".