Low Socioeconomic Status Is Associated with Cardiovascular Risk Factors and Outcomes in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Accelerated atherosclerosis is a major cause of death in systemic lupus erythematosus (SLE), yet little is known about the effect of socioeconomic status. We investigated whether education or income levels are associated with cardiovascular risk factors and outcomes in SLE. METHODS: Our study involved a longitudinal cohort of all patients with SLE enrolled in the Hopkins Lupus Cohort from 1987 through September 2011. Socioeconomic status was measured by education level (≥ 12 years or < 12) and income tertiles (> $60,000, $25,000-$60,000, or < $25,000). RESULTS: A total of 1752 patients with SLE were followed prospectively every 3 months. There were 1052 whites and 700 African Americans. Current smoking, obesity, hypertension, and diabetes mellitus were more common in African Americans (p < 0.01 for all), but there was no statistical difference in the frequency of myocardial infarction or stroke. In multivariate analyses stratified by ethnicity, low income was strongly associated with most traditional cardiovascular risk factors in whites, but only with smoking and diabetes in African Americans. In whites, low income increased the risk of both myocardial infarction (OR 3.24, 95% CI 1.41-7.45, p = 0.006) and stroke (OR 2.85, 95% CI 1.56-5.21, p = 0.001); in African Americans, these relationships were not seen. Low education, in contrast, was associated with smoking in both ethnic groups. CONCLUSION: Low income, not low education, is the socioeconomic status variable associated with cardiovascular risk factors and events. This association is most clearly demonstrable in whites.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".