Prevalence and Risk Factors for Major Infections in Patients with Antineutrophil Cytoplasmic Antibody–associated Vasculitis: Influence on the Disease Outcome
Bibliographic record
Abstract
OBJECTIVE: To analyze the role that infections play on the antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) outcome. METHODS: A retrospective study of adult patients with AAV diagnosed in a tertiary center. Clinical features, laboratory findings, treatment, relapses, major infections, and outcome were evaluated. RESULTS: Included were 132 patients [51 microscopic polyangiitis (MPA), 52 granulomatosis with polyangiitis (GPA), 29 eosinophilic GPA (EGPA)] with a mean followup of 140 (96-228) months. ANCA were positive in 85% of cases. A total of 300 major infections, mainly bacterial (85%), occurred in 60% patients during the followup. Lower respiratory tract (64%) and urinary tract infections (11%) were the most frequent, followed by bacteremia (10%). A total of 7.3% opportunistic infections were observed, most due to systemic mycosis. Up to 46% of all opportunistic infections took place in the first year of diagnosis, and 55% of them under cyclophosphamide (CYC) treatment. Bacterial infections were associated with Birmingham Vasculitis Activity Score (version 3) > 15 at the disease onset, a total cumulative CYC dose > 8.65 g, dialysis, and development of leukopenia during the followup. Leukopenia was the only factor independently related to opportunistic infections. Forty-four patients died, half from infection. Patients who had major infections had an increased mortality from any cause. CONCLUSION: Our results confirm that major infections are the main cause of death in patients with AAV.
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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 | 0.001 |
| 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".