Small Dense Low-Density Lipoproteins and Associated Risk Factors in Patients with Stroke
Bibliographic record
Abstract
OBJECTIVE: Low-density lipoproteins (LDL) are a heterogeneous group of particles, with small, dense particles being more atherogenic. It remains controversial whether elevated plasma levels of small dense LDL (sd-LDL) are risk factors for stroke. The aim of the present study was to examine the plasma levels of sd-LDL in patients with stroke and to investigate the associations in a large Chinese case-control study. METHODS: We recruited 299 stroke patients (159 cerebral thrombosis, 42 lacunar infarction, 98 intracerebral hemorrhage) and 299 controls. The semiquantitative analysis of plasma levels of sd-LDL was performed by nondenaturing gradient gel electrophoresis. RESULTS: (1) The plasma levels of sd-LDL in patients with ischemic stroke or hemorrhagic stroke were higher than in controls. (2) Multiple regression analysis showed that there were significant relationships between sd-LDL and triglyceride, high-density lipoprotein cholesterol, LDL cholesterol, systolic blood pressure and history of diabetes, and a significant relationship between sd-LDL and stroke (r = 0.286, p < 0.001) even after adjusting for these factors. (3) Compared with the controls, the calculation of odds ratios indicated relative risk estimates of 3.111 for ischemic stroke (OR = 3.111 , 95% CI = 1.891-5.117, p < 0.001) and 3.164 for hemorrhagic stroke (OR = 3.164, 95% CI = 1.632-6.137, p < 0.01). CONCLUSION: Plasma sd-LDL was independently associated with both thrombotic and hemorrhagic stroke, suggesting it may be an independent predictor of as well as a risk factor for stroke in Chinese people, justifying clinical trials for primary and secondary prevention of stroke using statins or fibrates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".