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Cholesteryl Ester Transfer Protein Inhibition, High-Density Lipoprotein Raising, and Progression of Coronary Atherosclerosis

2008· article· en· W2152683287 on OpenAlexafffund
Stephen J. Nicholls, E. Murat Tuzcu, Danielle M. Brennan, Jean‐Claude Tardif, Steven E. Nissen

Bibliographic record

VenueCirculation · 2008
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMontreal Heart Institute
FundersCanadian Institutes of Health ResearchPfizer CanadaPfizer PharmaceuticalsCleveland ClinicAstraZenecaEli Lilly and Company
KeywordsMedicineCholesterylester transfer proteinCoronary atherosclerosisLipoproteinInternal medicineCardiologyCoronary heart diseaseHigh-density lipoproteinCholesterol

Abstract

fetched live from OpenAlex

BACKGROUND: Despite favorable effects on high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol, the cholesteryl ester transfer protein inhibitor torcetrapib failed to slow atherosclerosis progression and increased mortality. We investigated the relationship between lipid changes and progression of coronary atherosclerosis. METHODS AND RESULTS: Intravascular ultrasound was performed at baseline and follow-up in 910 participants randomized to torcetrapib/atorvastatin or atorvastatin monotherapy. The relationship between changes in lipoprotein levels and the primary intravascular ultrasound end point, change in percent atheroma volume, was investigated. Compared with atorvastatin monotherapy, torcetrapib raised HDL-C by 61%, lowered low-density lipoprotein cholesterol by 20%, raised serum sodium (0.44+/-0.14 mmol/L, P=0.02), and lowered serum potassium (0.11+/-0.02 mmol/L, P<0.0001). Despite substantial increases in HDL-C, no effect was found of torcetrapib on percent atheroma volume. In torcetrapib-treated patients, an inverse relationship was observed between changes in HDL-C and percentage atheroma volume (r=-0.17, P<0.001). Participants with regression had greater increases in HDL-C (mean+/-SE, 62.9+/-37.4% versus 54.0+/-39.1%, P=0.002). Compared with the lowest quartile, torcetrapib-treated patients in the highest quartile of HDL-C change showed the least progression (-0.31+/-0.27 versus 0.88+/-0.27%, P=0.001). The highest on-treatment HDL-C quartile showed significant regression of percent atheroma volume (-0.69+/-0.27%, P=0.01). In multivariable analysis, changes in HDL-C levels independently predicted the effect on atherosclerosis progression (P=0.001). CONCLUSIONS: The majority of torcetrapib-treated patients demonstrated no regression of coronary atherosclerosis. Regression was only observed at the highest HDL-C levels. Torcetrapib raised serum sodium and lowered potassium, consistent with an aldosterone-like effect, which may explain the lack of favorable effects in the full study cohort. Accordingly, other cholesteryl ester transfer protein inhibitors, if they lack this off-target toxicity, may successfully slow atherosclerosis progression.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.250
Teacher spread0.224 · 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

Citations212
Published2008
Admission routes2
Has abstractyes

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