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Record W4415008749 · doi:10.3390/children12101364

Screening for Familial Hypercholesterolemia in Childhood: An Overview of Current Practices Around the World

2025· review· en· W4415008749 on OpenAlexaboutno aff
Maria Elena Capra, Roberta Sodero, Elisa Travaglia, Giuseppe Banderali, Giacomo Biasucci, Cristina Pederiva

Bibliographic record

VenueChildren · 2025
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
Fundersnot available
KeywordsFamilial hypercholesterolemiaDiseaseAtherosclerotic cardiovascular diseaseDeveloped countryCause of deathGenetic testingGenetic diagnosis

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.159
GPT teacher head0.444
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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