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Record W2793323219 · doi:10.1097/mol.0000000000000487

Familial hypercholesterolemia: experience from the French-Canadian population

2018· review· en· W2793323219 on OpenAlexaffabout
Martine Paquette, Jacques Genest, Alexis Baass

Bibliographic record

VenueCurrent Opinion in Lipidology · 2018
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsFamilial hypercholesterolemiaDiseaseMedicinePopulationFamily aggregationCholesterolInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: There has recently been renewed interest in the study of the various facets of familial hypercholesterolemia, a severe monogenic disease associated with elevated LDL-cholesterol and premature cardiovascular disease (CVD). In the present review, novel data presenting the frequency of familial hypercholesterolemia as well as factors modulating the cardiovascular risk in familial hypercholesterolemia will be discussed. RECENT FINDINGS: Recent studies have showed that familial hypercholesterolemia is much more prevalent than initially thought. Classically, it was estimated that familial hypercholesterolemia affected one in 500 people worldwide, but a recent large-scale meta-analysis has shown a prevalence closer to one in 250. In the French-Canadian population, this disease is even more frequent reaching one in 81 in certain regions of the Province of Quebec. Several novel studies in the French-Canadian population have shown that the clinical outcomes in familial hypercholesterolemia seem to be greatly influenced by risk factors other than LDL-cholesterol. Also, scores to predict CVD in familial hypercholesterolemia have been recently proposed. SUMMARY: Familial hypercholesterolemia is more frequent than initially thought and the phenotype of this disease can be variable. Indeed, both clinical and genetic variables can modulate the CVD risk in this population.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.146
GPT teacher head0.406
Teacher spread0.261 · 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 designNot applicable
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

Citations30
Published2018
Admission routes2
Has abstractyes

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