Management of antineutrophil cytoplasmic antibody-associated vasculitis: a changing tide
Bibliographic record
Abstract
PURPOSE OF REVIEW: Antineutrophil cytoplasmic antibody associated vasculitis (AAV) is a group of autoimmune disorders of small blood vessels. While outcomes in AAV have improved with the use of glucocorticoids (GC) and other immunosuppressants, these treatments are associated with significant toxicities. Infections are the major cause of mortality within the first year of treatment. There is a move towards newer treatments with better safety profiles. This review reflects on recent advances in the treatment of AAV. RECENT FINDINGS: The role of plasma exchange (PLEX) in AAV with kidney involvement has been clarified with new BMJ guideline recommendations following the publication of PEXIVAS and an updated meta-analysis. Lower dose GC regimens are now standard of care. Avacopan (C5a receptor antagonist) was noninferior to a regimen of GC therapy and is a potential steroid-sparing agent. Lastly, rituximab-based regimens were noninferior to cyclophosphamide in two trials for induction of remission and superior to azathioprine in one trial of maintenance of remission. SUMMARY: AAV treatments have changed tremendously over the past decade with a drive towards targeted PLEX use, increased rituximab use and lower GC dosing. Striking a crucial balance between morbidity from relapses and toxicities from immunosuppression remains a challenging path to navigate.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".