Predictors for Mortality in Patients with Antineutrophil Cytoplasmic Autoantibody-associated Vasculitis: A Study of 398 Chinese Patients
Bibliographic record
Abstract
OBJECTIVE: Patients with antineutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis (AAV) have high mortality despite the introduction of immunosuppressive therapy. We investigated factors associated with mortality of patients with AAV in a single Chinese cohort. METHODS: A total of 398 consecutive patients with AAV diagnosed in our center were recruited. Clinical and laboratory data were collected retrospectively. The predictive values of variables associated with mortality were analyzed. RESULTS: During followup of a median duration 25.5 months (range 1-196 mo), 135 out of 398 patients (33.9%) died, with 83 deaths within the first 12 months after diagnosis. Independent predictors of all-cause mortality were age (p < 0.001), secondary infection (p < 0.001), pulmonary involvement of AAV (p = 0.012), and initial renal function (p = 0.001). Secondary infection was the leading cause of death (53/153, 39.3%) during the first year after diagnosis, while cardiovascular event was the leading cause of death (15/53, 28.8%) after 12 months from diagnosis. Independent predictors of secondary infection were age (p = 0.002), initial renal function (p = 0.041), lymphocyte counts in the peripheral blood (p = 0.03), and underlying pulmonary involvement of AAV (p = 0.001). CONCLUSION: Secondary infection is the overall leading cause and independent predictor of death in patients diagnosed with AAV. Cardiovascular event is a major cause of death during the late followup. Prudent monitoring should be given to patients of advancing age with renal dysfunction to reduce adverse events, especially infectious complications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".