Abstract 253: The Association of Socioeconomic Status With Elevation of N-terminal Pro-b-type Natriuretic Peptide
Bibliographic record
Abstract
Background: The association between socioeconomic status (SES) and clinical cardiovascular disease (CVD) is well established. However, the association between SES and subclinical cardiac overload is unclear. We examined the association of SES with N-terminal pro-B-type natriuretic peptide (NT-pro-BNP), a marker of cardiac overload, in a population without prevalent clinical CVD (coronary disease, stroke, and heart failure hospitalization). Methods: In a cross-sectional study of 11,026 ARIC Study participants without prevalent clinical CVD at visit 2 (1990-1992), we assessed whether education level (<high school (low), high school/equivalent (medium) and >high school (high)) and household income (<$12,000 (low), $12,000 - $24,999 (medium) and ≥ $25,000 (high): $1 in 1991 = ~$1.75 in 2015) were associated with elevated NT-pro-BNP (≥400 pg/ml) in logistic regression models. Given that disproportionately high number of blacks belong to low SES and levels of NT-proBNP might vary by race, we tested SES-race interaction and stratified analyses by race. Results: After accounting for potential confounders, those with low education and income levels demonstrated higher odds of having elevated NT-proBNP compared to those with high education and income, although statistical significance was observed only for income. In race-stratified analysis, association of low education and income with NT-pro-BNP did not appear to differ between blacks and whites (p-interaction with income=0.99 or with education=0.52). When using NT-pro-BNP as a continuous dependent variable, both, low income and education showed a significant association with higher NT-proBNP levels compared to those with high income and education, respectively. Conclusions: Low SES (particularly low income) was associated with elevated level of NT-pro-BNP. Targeting low SES individuals might be helpful in early identification of high risk population for cardiac overload.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".