Efforts to Better Characterize “Antiphospholipid Antibody Nephropathy” for the 2023 ACR/EULAR Antiphospholipid Syndrome Classification Criteria: Renal Pathology Subcommittee Report
Bibliographic record
Abstract
OBJECTIVE: Antiphospholipid antibody (aPL) nephropathy (-N) can be challenging to recognize due to a lack of established classification or diagnostic criteria. As part of efforts to develop new antiphospholipid syndrome (APS) classification criteria (CC), the APS CC Renal Pathology Subcommittee aimed to better characterize the entity of aPL-N. METHODS: We used a 4-pronged approach that included (1) administering Delphi surveys to worldwide APS physicians to generate aPL-N terminology; (2) conducting a literature review to demonstrate the association of nephropathy with aPL and identify published aPL-N histopathological terminology and descriptions; (3) evaluating aPL-N terminology used in renal biopsy reports from an international patient registry; and (4) evaluating proposed kidney pathologic features for aPL-N by assessment of international Renal Pathology Society (RPS) members. RESULTS: After completing our metaanalysis demonstrating an association between nephropathy and aPL, we used Delphi surveys, a literature review, and international renal biopsy reports to develop a preliminary definition of aPL-N. The preliminary definition included include specific terms associated with acute (ie, thrombotic microangiopathy in glomeruli or arterioles/arteries) and chronic (ie, organized arterial or arteriolar microthrombi with or without recanalization, organized glomerular thrombi, fibrous and fibrocellular [arterial or arteriolar] occlusions, focal cortical atrophy with or without thyroidization, and fibrous intimal hyperplasia) lesions. Most RPS survey respondents agreed with this terminology and the importance of knowing aPL results for histopathological diagnosis. CONCLUSION: Our results support the inclusion of aPL-N in the 2023 American College of Rheumatology/European Alliance of Associations for Rheumatology APS CC, and provide the most widely accepted terminology to date for both acute and chronic pathologic lesions of aPL-N.
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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 | 0.159 | 0.172 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".