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Record W3213036992 · doi:10.3389/fcvm.2021.789931

Emerging Non-statin Treatment Options for Lowering Low-Density Lipoprotein Cholesterol

2021· review· en· W3213036992 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEzetimibeMedicineStatinDrugPCSK9CholesterolClinical trialPharmacologyAdverse effectResidual riskAtherosclerotic cardiovascular diseaseInternal medicineDiseaseLipoproteinLDL receptor

Abstract

fetched live from OpenAlex

Low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for the development of atherosclerotic cardiovascular disease. Statins have been the gold standard for managing cholesterol levels and reducing the risks associated with atherosclerotic cardiovascular disease; however, many patients do not achieve their cholesterol goals or are unable to tolerate this drug class due to adverse drug events. Recent studies of non-statin cholesterol lowering drugs (i.e., ezetimibe, PCSK9 inhibitors) have demonstrated cardiovascular benefits; and new drugs [i.e., bempedoic acid (BDA), inclisiran] have produced promising results in pre-clinical and clinical outcome trials. This narrative review aims to discuss the place in therapy of ezetimibe, PCSK9 inhibitors, BDA, and inclisiran and describe their relative pharmacokinetic (PK) profiles, efficacy and safety as monotherapy and combination therapy, and cardiovascular benefit(s) when used for hypercholesterolemia.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0110.008
Bibliometrics0.0010.001
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 head0.030
GPT teacher head0.320
Teacher spread0.290 · 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