Getting the balance right: adverse events of therapy in anti-neutrophil cytoplasm antibody vasculitis
Bibliographic record
Abstract
Antineutrophil cytoplasm antibody associated systemic vasculitides (AASV) have traditionally been managed with a combination of cyclophosphamide and glucocorticoids during the induction phase, followed by azathioprine in the maintenance phase. Whilst these therapies have markedly improved the prognosis in AASV, treatment related adverse events remain a major challenge and include complications such as infection, glucocorticoid related side effects, malignancy, cardiovascular disease, infertility and death. Newer biologic therapies have been shown to demonstrate equivalent efficacy as cyclophosphamide for remission but the hoped for reduction in adverse events has yet to be realised. More recent efforts have been focused on refining existing therapeutic regimens and strategies, tailoring individual treatment to disease severity, patient age and kidney function to derive maximum treatment efficacy while minimising treatment toxicity. In particular, current interventional trials are targeting a reduction in corticosteroid exposure in an effort to make induction and maintenance regimens safer.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".