Blood Pressure and Vascular Dysfunction Underlie Elevated Cerebral Blood Flow in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: In previous studies cerebral blood flow (CBF) was found to be altered in patients with systemic lupus erythematosus (SLE) compared to controls. We investigated the relationships between CBF and clinical data from subjects with SLE with the aim of determining the pathologic factors underlying altered CBF in SLE. METHODS: A total of 42 SLE subjects and 19 age- and sex-matched healthy control subjects were studied. Dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) was used to measure CBF. Patients and controls underwent complete clinical and laboratory evaluations in close proximity with their MRI studies. RESULTS: A higher CBF was present in the SLE group and was independently associated in statistical models with higher systolic blood pressure (SBP; p < 0.01). The intensity of the relationships (slope of curve) between CBF and mean arterial blood pressure, diastolic blood pressure, or blood levels of tissue plasminogen activator in the SLE group was significantly blunted relative to the control group. CONCLUSION: These findings are consistent with an underlying cerebral hyperperfusion in SLE induced by elevated but nonhypertensive levels of SBP. The factors underlying this relationship may be functional and/or structural (atherosclerotic, thrombotic, thromboembolic, or vasculitic) cerebrovascular disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".