Mortality and Functionality after Stroke in Patients with Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: To investigate mortality and functional impairment after stroke in systemic lupus erythematosus (SLE). METHODS: Using Swedish nationwide registers, we identified 423 individuals with SLE and 1652 people without SLE who developed a first-ever ischemic or hemorrhagic stroke (1998-2013) and followed them until all-cause death or for 1 year. HR for death after ischemic or hemorrhagic stroke and the risk ratio of functional impairment (dependence in either transferring, toileting, or dressing) 3 months after ischemic stroke were estimated. RESULTS: One year after stroke, 22% of patients with SLE versus 16% of those without SLE died. After ischemic stroke, patients with SLE had an increased risk of death (HR 1.85, 95% CI 1.39-2.45), which was attenuated after controlling for SLE-related comorbidities (HR 1.41, 95% CI 1.04-1.91). Functional impairment at 3 months was increased in SLE by almost 2-fold (risk ratio 1.73, 95% CI 1.16-2.57). After hemorrhagic stroke, patients with SLE had an HR of 2.30 (95% CI 1.38-3.82) for death, which was increased even during the first month. CONCLUSION: Compared to subjects without SLE, mortality after ischemic stroke increases after the first month in individuals with SLE, and functionality is worse at 3 months. SLE is associated with all-cause death after hemorrhagic stroke even during the first month. A shift of focus to patient functionality and prevention of hemorrhagic strokes is required.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".