High-sensitivity C-reactive protein and low-density lipoprotein cholesterol association with incident of cardiovascular events: Isfahan cohort study
Bibliographic record
Abstract
BACKGROUND: There are many studies on high-sensitivity C-reactive protein (hs-CRP) association with cardiovascular disease (CVD); however, just a few studies investigated whether the low-density lipoprotein cholesterol (LDL-C) could participate in hs-CRP prognostic strength. This study aimed to determine the alliance of hs-CRP and LDL-C in different concentrations in occurrence cardiovascular events in the Isfahan Cohort Study (ICS). METHODS: 3277 participants aged 35 and above were included in the current analysis. We evaluated the association of elevated hs-CRP levels (≥ 3 mg/dL) and CVD events including myocardial infarction, ischemic heart disease, stroke, CVD, CVD mortality, and all-cause mortality in those with LDL-C ≥ or < 130 mg/dL Cox frailty models was used to determine possible interactions. RESULTS: In both crude and fully adjusted models, there was no significant interaction between LDL-C and hs-CRP levels with the incidence of MI, stroke, CVD mortality, and all-cause death. Neither elevated LDL-C alone nor elevated CRP alone were associated with the risk of all cardiovascular events and all-cause death. However, participants with elevated concentrations of both hs-CRP and LDL-C had a greater risk of ischemic heart disease (IHD) (hazards ratio (HR) 1.44; 95% CI 1.03-2.02) and CVD (HR 1.36; 95% CI 1.01-1.83) than those with low LDL-C and hs-CRP. CONCLUSION: These results indicate that despite a null association between elevated levels of CRP or LDL-C alone and CVD events, concurrent rise in LDL-C and hs-CRP levels is associated with higher risk of IHD and CVD.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".