Vascular events in hypertensive patients with systemic lupus erythematosus
Bibliographic record
Abstract
Our purpose was to examine prospectively the relationship between systemic hypertension and vascular events in patients with SLE. SLE patients followed in the University of Toronto Lupus Clinic presenting between 1980 and 1988 and within one year of their diagnosis of SLE were identified. Standard definitions were used for hypertension and for all vascular events (MI, angina, CVA, PVD). The presence of traditional CAD risk factors, along with disease- and therapy-related risk factors for the development of vascular disease, were compared in the hypertensive and normotensive group. A multivariate logistic regression was performed to determine the best predictor of a vascular event. One hundred and fifty patients were identified in our inception cohort [75 hypertensive (50%) and 75 (50%) normotensive]. Seventeen hypertensive patients (22.7%) had at least one vascular event as compared to six (8.0%) normotensive patients (p = 0.022). The vascular events included 7 with CAD, 5 with CVA, and 5 with PVD in the hypertensive group while in the normotensive group 3 patients developed CAD, 2 CVA and 1 PVD. Fifteen deaths were recorded in the hypertensive group as compared to eight deaths in the non-hypertensive groups (P = 0.09). The groups were comparable with respect to associated risk factors, except for higher frequency of hypercholesterolemia (P = 0.003), azotemia (P = 0.001) and corticosteroid use (P = 0.038) in the hypertension group. In a multivariate analysis the best predictor of a vascular event was hypercholesterolemia (OR 6.9, 95% CI 2.4-24.8, P < 0.001). We conclude that systemic hypertension is associated with an increased frequency of vascular events in SLE. This is best explained by its association with hypercholesterolemia.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".