All‐Cause and Cause‐Specific Mortality in Patients With Granulomatosis With Polyangiitis: A Population‐Based Study
Bibliographic record
Abstract
OBJECTIVE: To investigate all-cause and cause-specific mortality in patients with newly diagnosed granulomatosis with polyangiitis (GPA) between 2 calendar time periods, 1997-2004 and 2005-2012. METHODS: Using an administrative health database, we compared all patients with incident GPA with non-GPA controls matched for sex, age, and time of entry into the study. The study cohorts were divided into 2 subgroups based on the year of diagnosis ("early cohort [1997-2004] and "late cohort" [2005-2012]). The outcome was death (all-cause, cardiovascular disease [CVD]-related cancer-related, renal disease-related, and infection-related) during the follow-up period. Hazard ratios (HR) were estimated using Cox proportional hazards models, first adjusted for age, sex, and time of entry and then adjusted for selected covariates based on a purposeful selection algorithm. RESULTS: Three hundred seventy patients with GPA and 3,700 non-GPA controls were included in this study, contributing 1,624.8 and 1,8671.3 person-years of follow-up, respectively. Sixty-eight deaths occurred in the GPA cohort, and 310 deaths occurred in the non-GPA cohort. Overall, the age-, sex-, and entry time-adjusted all-cause mortality HR in the GPA cohort was 3.12 (95% confidence interval CI 2.35-4.14). There was excess mortality due to CVD-related causes, but not cancer, in the GPA cohort. Reports of death due to infection or renal disease was not permitted, because the numbers of death were insufficient (<6 deaths for each outcome). All-cause mortality significantly improved between the early cohort and late cohort time periods (HR 5.61 and 2.33, respectively; P for interaction = 0.017). CONCLUSION: This population-based study showed increased all-cause and CVD-related mortality risks in patients with GPA. There was significant improvement in the all-cause mortality risk over time, but the risk remained increased compared with that in the general population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".