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Record W2903347258 · doi:10.2337/dc18-1491

Inclisiran Lowers LDL-C and PCSK9 Irrespective of Diabetes Status: The ORION-1 Randomized Clinical Trial

2018· article· en· W2903347258 on OpenAlexaff
Lawrence A. Leiter, Hwee Teoh, David Kallend, R. Scott Wright, Ulf Landmesser, Peter Wijngaard, John J.P. Kastelein, Kausik K. Ray

Bibliographic record

VenueDiabetes Care · 2018
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersEsperion TherapeuticsIonis PharmaceuticalsMylanNovo NordiskMedicines CompanySanofiKowa CompanyRegeneron PharmaceuticalsEli Lilly and CompanyAstraZenecaCSL BehringAmgenPfizer
KeywordsPCSK9MedicineDiabetes mellitusDyslipidemiaInternal medicinePlaceboAdverse effectCholesterolEndocrinologyType 2 diabetesApolipoprotein BRandomized controlled trialLipoproteinGastroenterologyLDL receptorPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the efficacy and safety of inclisiran by diabetes status. RESEARCH DESIGN AND METHODS: ORION-1 (ClinicalTrials.gov, NCT02597127) randomized 501 subjects with atherosclerotic cardiovascular disease (ASCVD) or ASCVD risk equivalents and high LDL cholesterol (LDL-C), despite maximally tolerated LDL-C-lowering therapies, to one or two doses of placebo or inclisiran. Levels of lipids and proprotein convertase subtilisin/kexin type 9 (PCSK9) at baseline and day 180 were compared. RESULTS: < 0.005 for all doses in the without- and with-diabetes groups, respectively) and PCSK9. The inclisiran-treated groups also had lower apolipoprotein B, non-HDL cholesterol, and lipoprotein(a) but higher HDL cholesterol. Inclisiran had an adverse profile similar to that of placebo, and adverse events were proportionally balanced in the baseline with- and without-diabetes groups. CONCLUSIONS: PCSK9-targeted siRNA-driven strategies may provide a novel therapeutic option for managing dyslipidemia in the presence and absence of diabetes.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.321
Teacher spread0.300 · 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 designRandomized trial
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

Citations113
Published2018
Admission routes1
Has abstractyes

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