Risk of Ischemic Stroke and Peripheral Arterial Disease in Heterozygous Familial Hypercholesterolemia: A Meta-Analysis
Bibliographic record
Abstract
Heterozygous familial hypercholesterolemia (HeFH) is a common genetic disorder predisposing affected individuals to lifelong low-density lipoprotein cholesterol (LDL-C) elevation and coronary heart disease. However, whether HeFH increases the risk of peripheral arterial disease (PAD) and ischemic stroke is undetermined. We examined associations between HeFH and these outcomes in a comprehensive systematic review and meta-analysis. We searched MEDLINE, EMBASE, Global Health, the Cochrane Library, and PubMed (for ahead-of-print publications) for relevant English-language studies. Maximally adjusted risk estimates were pooled under random- and fixed-effects meta-analysis to derive odds ratios (ORs) and 95% confidence intervals (CIs). We included 6 studies representing 183 388 participants. Heterozygnous familial hypercholesterolemia was associated with a higher risk of PAD (OR: 3.59 [95% CI: 1.30-9.89]). This trend was nonsignificantly preserved (OR: 2.96 [95% CI: 0.68-12.88]) in sensitivity analyses of genetically defined HeFH. Genetic HeFH was not associated with increased ischemic stroke risk (OR: 0.76 [95% CI: 0.37-1.58]) although possessing an LDL-C >4.9 mmol/L (190 mg/dL) was (OR: 1.42 [95% CI: 1.06-1.89]). We found clinical and genetic diagnoses of HeFH to be associated with increased PAD risk. Genetically confirmed HeFH may not confer an increased risk of ischemic stroke. Modest associations may exist between LDL-C and ischemic stroke risk in HeFH.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.062 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".