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Record W4412391937 · doi:10.1016/j.jaccas.2025.103953

Apparent Nonresponse to PCSK9 Inhibition in a Patient With Heterozygous Familial Hypercholesterolemia Due to PCSK9 Gene Duplication

2025· article· en· W4412391937 on OpenAlexaff
Mustansir Pindwarawala, S Bose, Liam R. Brunham

Bibliographic record

VenueJACC Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia HospitalUniversity of SaskatchewanUniversity of British Columbia
Fundersnot available
KeywordsPCSK9EzetimibeEvolocumabKexinFamilial hypercholesterolemiaInternal medicineEndocrinologyMedicineLDL receptorAlirocumabGene duplicationProprotein convertaseCholesterolLipoproteinBiologyGeneticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Heterozygous familial hypercholesterolemia is a genetic disorder characterized by persistently elevated low-density lipoprotein (LDL-C) levels and increased cardiovascular risk. Management includes statins as well as nonstatin lipid-lowering agents, such as ezetimibe, bempedoic acid, and inhibitors of proprotein convertase subtilisin/kexin type 9 (PCSK9). Although PCSK9 inhibition is a potent mechanism to reduce levels of LDL-C, a small percentage of patients respond poorly for reasons that are not fully understood. CASE SUMMARY: A 52-year-old woman presented with persistently elevated LDL-C and a history of atherosclerotic cardiovascular disease. Her LDL-C levels remained elevated despite high-intensity statin therapy and ezetimibe. She was treated with various inhibitors of PCSK9 but displayed little or no reduction in LDL-C levels. Genetic testing identified a duplication of the PCSK9 gene. Treatment with a higher dose of evolocumab (420 mg every 2 weeks) led to a more pronounced reduction in LDL-C levels. DISCUSSION: This case identifies PCSK9 gene duplication as a potential mechanism underlying nonresponse to PCSK9 inhibition and suggests that higher dosing of PCSK9 inhibitors may overcome nonresponse in some patients.

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 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 score0.223
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.271
Teacher spread0.260 · 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.

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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