Banff 2022 Kidney Commentary: Reflections and Future Directions
Bibliographic record
Abstract
In September 2022, in Banff, Alberta, Canada, the XVIth Banff meeting, corresponding to the 30th anniversary of the Banff classification, was held, leading to 2 recent publications. Discussions at the Banff meeting focused on proposing improvements to the Banff process as a whole. In line with this, a unique opportunity was offered to a selected group of 16 representatives from the pathology and transplant nephrology community, experts in the field of kidney transplantation, to review these 2 Banff manuscripts. The aim was to provide an insightful commentary, to gauge any prospective influence the proposed changes may have, and to identify any potential areas for future enhancement within the Banff classification. The group expressed its satisfaction with the incorporation of 2 new entities, namely "microvascular inflammation/injury donor-specific antibodies-negative and C4d negative" and "probable antibody-mediated rejection," into category 2. These changes expand the classification, facilitating the capture of more biopsies and providing an opportunity to explore the clinical implications of these lesions further. However, we found that the Banff classification remains complex, potentially hindering its widespread utilization, even if a degree of complexity may be unavoidable given the intricate pathophysiology of kidney allograft pathology. Addressing the histomorphologic diagnosis of chronic active T cell-mediated rejection (CA TCMR), potentially reconsidering a diagnostic-agnostic approach, as for category 2, to inflammation in interstitial fibrosis and tubular atrophy and chronic active T cell-mediated rejection was also an important objective. Furthermore, we felt a need for more evidence before molecular diagnostics could be routinely integrated and emphasized the need for clinical and histologic context determination and the substantiation of its clinical impact through rigorous clinical trials. Finally, our discussions stressed the ongoing necessity for multidisciplinary decision-making regarding patient care.
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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 | 0.000 | 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 | 0.000 |
| 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".