Mayo Clinic Consensus Report on Membranous Nephropathy: Proposal for a Novel Classification
Bibliographic record
Abstract
Membranous nephropathy (MN) is a pattern of injury caused by autoantibodies binding to specific target antigens, with accumulation of immune complexes along the subepithelial region of glomerular basement membranes. The past 20 years have brought revolutionary advances in the understanding of MN, particularly via the discovery of novel target antigens and their respective autoantibodies. These discoveries have challenged the traditional classification of MN into primary and secondary forms. At least 14 target antigens have been identified, accounting for 80%-90% of cases of MN. Many of the forms of MN associated with these novel MN target antigens have distinctive clinical and pathologic phenotypes. The Mayo Clinic consensus report on MN proposes a 2-step classification of MN. The first step, when possible, is identification of the target antigen, based on a multistep algorithm and using a combination of serology, staining of the kidney biopsy tissue by immunofluorescence or immunohistochemistry, and/or mass spectrometry methodology. The second step is the search for a potential underlying disease or associated condition, which is particularly relevant when knowledge of the target antigen is available to direct it. The meeting acknowledges that the resources and equipment required to perform the proposed testing may not be generally available. However, the meeting consensus was that the time has come to adopt an antigen-based classification of MN because this approach will allow for accurate and specific MN diagnosis, with significant implications for patient management and targeted treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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".