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Record W2738941847 · doi:10.1161/jaha.117.005549

Atherogenic Lipoprotein Determinants of Cardiovascular Disease and Residual Risk Among Individuals With Low Low‐Density Lipoprotein Cholesterol

2017· article· en· W2738941847 on OpenAlexaff
Patrick R. Lawler, Akintunde O. Akinkuolie, Audrey Y. Chu, Svati H. Shah, William E. Kraus, Damian Craig, Latha Padmanabhan, Robert J. Glynn, Paul M. Ridker, Daniel I. Chasman, Samia Mora

Bibliographic record

VenueJournal of the American Heart Association · 2017
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsHeart and Stroke FoundationUniversity of TorontoUniversity Health Network
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthAstraZeneca
KeywordsMedicineInternal medicineVery low-density lipoproteinCholesterolLipoproteinEndocrinologyRosuvastatinStatinHazard ratioResidual riskPopulationLipoprotein particleTriglycerideConfidence interval

Abstract

fetched live from OpenAlex

Background Levels of LDL (low‐density lipoprotein) cholesterol in the population are declining, and increasing attention is being focused on residual lipid‐related pathways of atherosclerotic cardiovascular disease risk beyond LDL cholesterol. Among individuals with low (<130 mg/dL) LDL cholesterol, we undertook detailed profiling of circulating atherogenic lipoproteins in relation to incident cardiovascular disease in 2 populations. Methods and Results We performed proton nuclear magnetic resonance spectroscopy to quantify concentrations of LDL and VLDL (very low‐density lipoprotein) particle subclasses in 11 984 JUPITER trial participants ( NCT 00239681). Adjusted Cox models examined cardiovascular disease risk associated with lipoprotein measures according to treatment allocation. Risk (adjusted hazard ratio [95% CI ] per SD increment) among placebo‐allocated participants was associated with total LDL particles (1.19 [1.02, 1.38]) and total VLDL particles (1.21 [1.04, 1.41]), as well as apolipoprotein B, non–high‐density lipoprotein cholesterol, and triglycerides, but not LDL‐c. Rosuvastatin reduced LDL measures but had variable effects on triglyceride and VLDL measures. On‐statin levels of the smallest VLDL particle subclass were associated with a 68% per‐ SD (adjusted hazard ratio 1.68 [1.28, 2.22]) increase in residual risk—this risk was related to VLDL cholesterol and not triglyceride or larger VLDL particles. There was evidence that residual risk prediction during statin therapy could be significantly improved through the inclusion of key VLDL measures (Harrell C‐index 0.780 versus 0.712; P <0.0001). In an independent, prospective cohort of 4721 individuals referred for cardiac catheterization ( CATHGEN ), similar patterns of lipoprotein‐related risk were observed. Conclusions Atherogenic lipoprotein particle concentrations were associated with cardiovascular disease risk when LDL cholesterol was low. VLDL lipoproteins, particularly the smallest remnant subclass, may represent unused targets for risk prediction and potential therapeutic intervention for reducing residual risk. Clinical Trial Registration URL : http://www.clinicaltrials.gov . Unique identifier: NCT 00239681.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
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)0.0000.000

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 head0.008
GPT teacher head0.249
Teacher spread0.240 · 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 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

Citations145
Published2017
Admission routes1
Has abstractyes

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