Impact of C-reactive protein levels on lipoprotein(a)-associated aortic stenosis incidence and progression
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
Abstract Aims Elevated lipoprotein(a) [Lp(a)] levels are associated with the risk of coronary artery disease (CAD) and calcific aortic valve stenosis (CAVS). Observational studies revealed that Lp(a) and C-reactive protein (CRP) levels, a biomarker of systemic inflammation, may jointly predict CAD risk. Whether Lp(a) and CRP levels also jointly predict CAVS incidence and progression is unknown. Methods and results We investigated the association of Lp(a) with CAVS according to CRP levels in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk study (n = 18 226, 406 incident cases) and the UK Biobank (n = 438 260, 4582 incident cases), as well as in the ASTRONOMER study (n = 220), which assessed the haemodynamic progression rate of pre-existing mild-to-moderate aortic stenosis. In EPIC-Norfolk, in comparison to individuals with low Lp(a) levels (<50 mg/dL) and low CRP levels (<2.0 mg/L), those with elevated Lp(a) (>50 mg/dL) and low CRP levels (<2.0 mg/L) and those with elevated Lp(a) (>50 mg/dL) and elevated CRP levels (>2.0 mg/L) had a higher CAVS risk [hazard ratio (HR) = 1.86 (95% confidence intervals, 1.30–2.67) and 2.08 (1.44–2.99), respectively]. A comparable predictive value of Lp(a) in patients with vs. without elevated CRP levels was also noted in the UK Biobank. In ASTRONOMER, CAVS progression was comparable in patients with elevated Lp(a) levels with or without elevated CRP levels. Conclusion Lp(a) predicts the incidence and possibly progression of CAVS regardless of plasma CRP levels. Lowering Lp(a) levels may warrant further investigation in the prevention and treatment of CAVS, regardless of systemic inflammation.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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