Effect of Lipoprotein(a) on Stroke Recurrence Attenuates at Low LDL-C (Low-Density Lipoprotein) and Inflammation Levels
Bibliographic record
Abstract
BACKGROUND: Lp(a) (lipoprotein(a)) contributes to cardiovascular disease mainly through proatherogenic and proinflammatory effects. Here, we aimed to evaluate whether a residual stroke risk of Lp(a) would remain when the LDL-C (low-density lipoprotein cholesterol) and inflammatory levels are maintained low. METHODS: This prospective cohort study included 9899 patients with ischemic stroke or transient ischemic attack from the Third China National Stroke Registry who had measurements of plasma Lp(a) and were followed up for 1 year. Cutoffs were set at the 50 mg/dL for Lp(a). LDL-C was corrected for Lp(a)-derived cholesterol (LDL-Cc [LDL-C corrected]) and cutoffs were set at 55 and 70 mg/dL.The threshold values of IL-6 (interleukin 6) and hsCRP (high-sensitive C-reactive protein) were the median 2.65 ng/L and 2 mg/L. Multivariable-adjusted hazard ratio (HR) were calculated using Cox regression models for each category to investigate the associations of Lp(a) with stroke recurrence within 1 year. RESULTS: Among all patients, those with Lp(a) ≥50 mg/dL were at higher stroke recurrence risk than those with Lp(a) <50 mg/dL (11.5% versus 9.4%; adjusted HR, 1.20 [95% CI, 1.02-1.42]). However, the risk associated with elevated Lp(a) was attenuated in patients with LDL-Cc <55 mg/dL (high Lp(a) versus low Lp(a): 8.9% versus 9.0%; adjusted HR, 0.92 [95% CI, 0.65-1.30]) or IL-6 <2.65 ng/L (9.0% versus 7.8%; adjusted HR, 1.14 [95% CI, 0.87-1.49]). Notably, in the group with both low LDL-Cc and inflammation levels, the rate of patients with high Lp(a) did not significantly different from the rate of patients with low Lp(a; LDL-Cc <55 mg/dL and IL-6 <2.65 ng/L: 6.2% versus 7.1%; adjusted HR, 0.86 [95% CI, 0.46-1.62]; LDL-Cc <55 mg/dL and hsCRP <2 mg/L: 7.7% versus 7.6%; adjusted HR, 0.97 [95% CI, 0.57-1.66]). However, there was no interaction between the LDL-Cc, IL-6, hsCRP, and Lp(a) levels on stroke recurrence risk. CONCLUSIONS: Increased Lp(a) was significantly associated with stroke recurrence risk in patients with ischemic stroke/transient ischemic attack. However, at low LDL-Cc or IL-6 levels, the elevated Lp(a) -associated stroke recurrence risk was attenuated in a secondary prevention setting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".