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Record W3000712048 · doi:10.1016/j.jacc.2019.10.057

Effect of Alirocumab on Lipoprotein(a) and Cardiovascular Risk After Acute Coronary Syndrome

2020· article· en· W3000712048 on OpenAlexafffund
Vera Bittner, Michael Szarek, Philip E. Aylward, Deepak L. Bhatt, Rafael Díaz, Jay M. Edelberg, Zlatko Fras, Shaun G. Goodman, Sigrun Halvorsen, Corinne Hanotin, Robert A. Harrington, J. Wouter Jukema, Virginie Loizeau, Patrick M. Moriarty, Angèle Moryusef, Robert Pordy, Matthew T. Roe, Peter Sinnaeve, Sotirios Tsimikas, Robert A. Vogel, Harvey D. White, Doron Zahger, Andreas M. Zeiher, Philippe Gabríel Steg, Gregory G. Schwartz

Bibliographic record

VenueJournal of the American College of Cardiology · 2020
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsCanadian VIGOUR CentreUniversity of TorontoSt. Michael's HospitalUniversity of Alberta
FundersAmerican RegentEsperion TherapeuticsDuke Clinical Research InstituteAstellas PharmaEisaiUniversity of TorontoDaiichi-SankyoBayer HealthCareEuropean CommissionAstraZenecaAmarin CorporationEli Lilly and CompanyUniversity of AlabamaRegeneron PharmaceuticalsBoston VA Research InstituteMedicines CompanyUniversity of Alabama at BirminghamBristol-Myers SquibbCleveland ClinicNovo NordiskMyoKardiaUniversity of PennsylvaniaBelvoir Media GroupServierGilead SciencesYork UniversityPfizerHeart and Stroke Foundation of CanadaHLS TherapeuticsGlaxoSmithKlineCSL BehringAmgenSt. Jude MedicalKowa CompanySanofiAmerican Heart Association
KeywordsMedicineAlirocumabAcute coronary syndromeCardiologyInternal medicineLipoprotein(a)LipoproteinCholesterolMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: Lipoprotein(a) concentration is associated with cardiovascular events. Alirocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, lowers lipoprotein(a) and low-density lipoprotein cholesterol (LDL-C). OBJECTIVES: A pre-specified analysis of the placebo-controlled ODYSSEY Outcomes trial in patients with recent acute coronary syndrome (ACS) determined whether alirocumab-induced changes in lipoprotein(a) and LDL-C independently predicted major adverse cardiovascular events (MACE). METHODS: One to 12 months after ACS, 18,924 patients on high-intensity statin therapy were randomized to alirocumab or placebo and followed for 2.8 years (median). Lipoprotein(a) was measured at randomization and 4 and 12 months thereafter. The primary MACE outcome was coronary heart disease death, nonfatal myocardial infarction, ischemic stroke, or hospitalization for unstable angina. RESULTS: Baseline lipoprotein(a) levels (median: 21.2 mg/dl; interquartile range [IQR]: 6.7 to 59.6 mg/dl) and LDL-C [corrected for cholesterol content in lipoprotein(a)] predicted MACE. Alirocumab reduced lipoprotein(a) by 5.0 mg/dl (IQR: 0 to 13.5 mg/dl), corrected LDL-C by 51.1 mg/dl (IQR: 33.7 to 67.2 mg/dl), and reduced the risk of MACE (hazard ratio [HR]: 0.85; 95% confidence interval [CI]: 0.78 to 0.93). Alirocumab-induced reductions of lipoprotein(a) and corrected LDL-C independently predicted lower risk of MACE, after adjustment for baseline concentrations of both lipoproteins and demographic and clinical characteristics. A 1-mg/dl reduction in lipoprotein(a) with alirocumab was associated with a HR of 0.994 (95% CI: 0.990 to 0.999; p = 0.0081). CONCLUSIONS: Baseline lipoprotein(a) and corrected LDL-C levels and their reductions by alirocumab predicted the risk of MACE after recent ACS. Lipoprotein(a) lowering by alirocumab is an independent contributor to MACE reduction, which suggests that lipoprotein(a) should be an independent treatment target after ACS. (ODYSSEY Outcomes: Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab; NCT01663402).

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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 designObservational
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

Citations572
Published2020
Admission routes2
Has abstractyes

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