Blood Pressure Variability and Age-related Blood Pressure Patterns in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Despite the high prevalence of cardiovascular (CV) disease among patients with systemic lupus erythematosus (SLE), the relationship between age, blood pressure (BP), and BP variability (BPV) is not well understood. We studied visit-to-visit BPV, its relationship to age, clinical, and demographic characteristics, and its potential role as a CV risk factor in patients with SLE. METHODS: We analyzed systolic (SBP) and diastolic BP (DBP) measures in our cohort using mixed-effects regression models. From these models, we then obtained estimates of the mean BP, the visit-to-visit SD, and the between-person SD. The estimated means were compared to the general population using data from the National Health Statistics Reports from 2001 to 2008. In addition, we examined the relationship between BP (means, variances), patient demographic and clinical characteristics, and subsequent CV events. RESULTS: The mean SBP in SLE increased with age and was significantly higher in younger patients compared to the general population. BPV in SLE was elevated across all ages. BPV was significantly higher in African Americans, in patients with traditional CV risk factors, those with high disease activity, and in patients taking prednisone. Hydroxychloroquine was associated with significantly lower BPV. Within-person variability in DBP of ≥ 9 mmHg was highly associated with CV events in a multivariate analysis. CONCLUSION: Age-related BP patterns in SLE differ from the general population. Increased visit-to-visit BPV is affected by many disease-specific and traditional CV factors. Increased DBP variability is highly associated with CV events in 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 | 0.001 | 0.004 |
| 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) | 0.001 | 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".