Screening for Familial Hypercholesterolemia in Childhood: An Overview of Current Practices Around the World
Bibliographic record
Abstract
Familial hypercholesterolemia (FH) is a common genetic disorder with a fairly constant worldwide prevalence of 1 case per 311 individuals worldwide. It is characterized by severe hypercholesterolemia from birth, early atherosclerosis and death from cardiovascular disease at a young age. Diagnosis and treatment from childhood are essential to reduce cardiovascular mortality. Many countries have developed a strategy of implementing pediatric screening, which has led to an increase in diagnoses. This paper evaluates the screening strategies implemented in different countries worldwide. First, we examined which schemes were preferred in various national contexts in Europe. Next, we evaluated the screening methods used in the US, Canada, Australia and Japan. Finally, we researched the screening strategies proposed in some low-resource countries, discovering the difficulties and limitations they face. We have highlighted a wide range of realities, from small-scale pilot studies to cutting-edge proposals. We have also emphasized that, while the topic is certainly of interest, it is burdened by multiple difficulties and unresolved questions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".