Microembolic Signals in Patients with Systemic Lupus Erythematosus
Bibliographic record
Abstract
INTRODUCTION: Central nervous system (CNS) involvement is a common and less understood aspect of systemic lupus erythematosus (SLE). Microembolic signals (MES) have been reported in SLE. We conducted a prospective study to evaluate the frequency of MES among patients with CNS involvement and those without. The main aim of the study is to clarify the pathophysiology of the CNS involvement in SLE. METHODS AND MATERIALS: Sixty eight patients with a diagnosis of SLE (60 females, 8 males) participated in the study. Both middle cerebral arteries were monitored using transcranial Doppler for 60 min to detect MES. All cases underwent neurology and psychiatry assessments. RESULTS: MES were detected in 7/68 patients (10.3%) with the mean number of 3.5 per hour. MES were significantly higher in patients with CNS involvement (6/24, 25%) than those without (1/44, 2.2%) (P=0.006). SLE disease activity index, duration of disease, plaque formation, intima-media thickness, and antiphospholipid antibodies were not associated with MES. MES were more frequent in patients receiving Aspirin and/or Warfarin (p=0.02). CONCLUSIONS: MES may be a predictor for CNS involvement in SLE patients at risk for neuropsychiatric syndromes. Cerebral embolism may be implicated in the pathophysiology of neuropsychiatric SLE.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.004 | 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".