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Record W4413384258 · doi:10.1016/j.jaccas.2025.104648

Multimodal Therapy Achieves Secondary Prevention LDL-C Targets in LDL-Receptor Null Homozygous Familial Hypercholesterolemia

2025· article· en· W4413384258 on OpenAlexaff
Areej Alkhairy, Pinhao Xiang, John Khoo, Carolyn Taylor, Gordon A. Francis

Bibliographic record

VenueJACC Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFamilial hypercholesterolemiaLDL receptorLdl cholesterolNull (SQL)MedicineInternal medicineCholesterolLipoproteinComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Homozygous familial hypercholesterolemia is a rare condition most commonly associated with pathogenic variants in the LDLR gene that leads to mortality before age 20 if not treated. CASE SUMMARY: A 4-year-old boy of Lebanese origin with multiple skin xanthomas was found to have untreated low-density lipoprotein cholesterol (LDL-C) of 1005 mg/dL (26 mM). Gene analysis revealed biallelic identical LDLR variants with <2% residual LDLR activity (LDLR-null). DISCUSSION: With combination therapy including maximum dose rosuvastatin, ezetimibe, plasma exchange, lomitapide, and evinacumab, guideline-recommended LDL-C of <70 mg/dL (1.8 mM) was achieved for secondary prevention of coronary disease. With this combined treatment, there has been no progression of his premature coronary heart disease. TAKE-HOME MESSAGES: Effective treatment of homozygous familial hypercholesterolemia requires multimodal lipid-lowering therapies. With currently available treatments it is possible to achieve previously unattainable lowering of LDL-C to prevent vascular disease and the need for liver transplantation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.012
GPT teacher head0.289
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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