Imaging Pattern and Outcome of Stroke in Patients With Systemic Lupus Erythematosus: A Case-control Study
Bibliographic record
Abstract
Objective To evaluate the outcome of stroke in patients with systemic lupus erythematosus (SLE). Methods Patients who fulfilled ≥ 4 American College of Rheumatology criteria for SLE and had a history of stroke from 1997 to 2017 were identified. The functional outcome of stroke [assessed by the modified Rankin Scale (mRS) at 90 days], mortality, stroke complications, and recurrence were retrospectively studied and compared with matched non-SLE patients with stroke. Results Forty SLE patients and 120 non-SLE patients with stroke (age at stroke 44.7 ± 13.7 yrs, 87.5% women) were studied. Ischemic type of stroke (90% vs 63%, P = 0.001) and extensive infarction (69.4% vs 18.7%, P < 0.001) were more common in SLE than non-SLE patients. Border zone infarct and multiple infarcts on imaging were significantly more prevalent in SLE patients. Patients with SLE were more functionally dependent than controls at 90 days poststroke. Logistic regression showed that SLE was significantly associated with a poor stroke functional outcome independent of age, sex, past stroke, atherosclerotic risk factors, and the severity of stroke (OR 5.4, 95% CI 1.1–26.0, P = 0.035). Stroke mortality at 30 days was nonsignificantly higher in SLE than non-SLE patients, but all-cause mortality (37.5% compared to 8.3%, P < 0.001), recurrence of stroke (30% compared to 9.2%, P = 0.002), and poststroke seizure (22.5% compared to 3.3%, P = 0.001) were significantly more common in SLE patients after an observation of 8.4 ± 6.1 years. SLE was independently associated with all-cause mortality and stroke recurrence over time. Conclusions Stroke in patients with SLE is associated with a poorer outcome than matched controls in terms of functional recovery, recurrence, and mortality.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".