Sex differences in treatment of familial hypercholesterolaemia: a meta-analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Familial hypercholesterolaemia (FH) is a highly prevalent monogenic disorder characterized by elevated LDL cholesterol (LDL-C) levels and premature atherosclerotic cardiovascular disease. Sex disparities in diagnosis, lipid-lowering therapy, and achieved lipid levels have emerged worldwide, resulting in barriers to care in FH. A systematic review was performed to investigate sex-related disparities in treatment, response, and lipid target achievement in FH (PROSPERO, CRD42022353297). METHODS: MEDLINE, Embase, The Cochrane library, PubMed, Scopus, PsycInfo, and grey literature databases were searched from inception to 26 April 2023. Records were eligible if they described sex differences in the treatment of adults with FH. RESULTS: Of 4432 publications reviewed, 133 met our eligibility criteria. In 16 interventional clinical trials (eight randomized and eight non-randomized; 1840 participants, 49.4% females), there were no differences between males and females in response to fixed doses of lipid-lowering therapy, suggesting that sex was not a determinant of response. Meta-analysis of 25 real-world observational studies (129 441 participants, 53.4% females) found that females were less likely to be on lipid-lowering therapy compared with males (odds ratio .74, 95% confidence interval .66-.85). Importantly, females were less likely to reach an LDL-C < 2.5 mmol/L (odds ratio .85, 95% confidence interval .74-.97). Similarly, treated LDL-C levels were higher in females. Despite this, male sex was associated with a two-fold greater relative risk of major adverse cardiovascular events including myocardial infarction, atherosclerotic cardiovascular disease, and cardiovascular mortality. CONCLUSIONS: Females with FH were less likely to be treated intensively and to reach guideline-recommended LDL-C targets. This sex bias represents a surmountable barrier to clinical care.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.001 | 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 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".