Mortality related to cerebrovascular disease in systemic lupus erythematosus
Bibliographic record
Abstract
The objective of this study was to examine mortality rates related to cerebrovascular disease in systemic lupus erythematosus (SLE) compared to the general population. Our sample was a multisite Canadian SLE cohort (10 centres, n = 2688 patients). Deaths due to cerebrovascular disease were ascertained by vital statistics registry linkage using ICD diagnostic codes. Standardized mortality ratio (SMR, ratio of deaths observed to expected) estimates were calculated. The total SMR for death due to cerebrovascular disease was 2.0 (95% confidence interval [CI] 1.0, 3.7). When considering specific types of events, the category with the greatest increased risk was that of ill-defined cerebrovascular events (SMR 44.9 95% CI 9.3, 131.3) and other cerebrovascular disease (SMR 8.4, 95% CI 2.3, 21.6). Deaths due to cerebral infarctions appeared to be less common than hemorrhages and other types of cerebrovascular events. Our data suggest an increase in mortality related to cerebrovascular disease in SLE patients compared to the general population. The large increase in ill-defined cerebrovascular events may represent cases of cerebral vasculitis or other rare forms of nervous system disease; alternately, it may reflect diagnostic uncertainty regarding the etiology of some clinical presentations in SLE patients. The suggestion that more deaths are attributed to cerebral hemorrhage, as opposed to infarction, indicates that inherent or iatrogenic factors (eg, thrombocytopenia or anticoagulation) may be important. In view of the paucity of large-scale studies of mortality attributed to neuropsychiatric outcomes in SLE, our findings highlight the need for additional research in large SLE cohorts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".