C-Reactive Protein as a Screening Test for Cardiovascular Risk in a Multiethnic Population
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Small increases in the inflammatory marker C-reactive protein (CRP) are predictive of vascular events among asymptomatic individuals. There are few data supporting the use of CRP as a risk marker among nonwhite individuals. METHODS AND RESULTS: 1250 adults of South Asian, Chinese, European, and Aboriginal ancestry were randomly sampled from 4 communities in Canada. Participants provided fasting blood samples for CRP, glucose, lipids, and coagulation factors, and they had undergone a carotid B-mode ultrasound. Cardiovascular disease was determined by history and electrocardiogram. The age- and sex-adjusted mean CRP was 3.74 mg/L (standard error, 0.14) among Aboriginals, 2.59 mg/L (0.12) among South Asians, and 1.18 mg/L (0.13) among Chinese compared with 2.06 mg/L (0.12) among Europeans (overall P<0.0001). Differences in the CRP concentration between ethnic groups were substantially diminished, but not abolished, after adjustment for metabolic factors. CRP was independently associated with CVD after adjusting for the Framingham risk factors, atherosclerosis, anthropometric measurements, and ethnicity (OR=1.03 for a 0.1-increase in CRP; P=0.02). CONCLUSIONS: CRP varies substantially between people of different ethnic origin and is influenced by their differences in metabolic factors. Prospective validation of CRP as a risk predictor for cardiovascular disease among nonwhite ethnic groups is required.
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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 | 0.000 | 0.000 |
| 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 it