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Record W2166790944 · doi:10.2174/157016110793563825

Effect of Non-Statin Lipid Lowering and Anti-Obesity Drugs on LDL Subfractions in Patients with Mixed Dyslipidaemia

2010· review· en· W2166790944 on OpenAlex
Matilda Florentin, A.D. Tselepis, Moses Elisaf, Christos V. Rizos, Dimitri P. Mikhailidis, Evangelos Liberopoulos

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCurrent Vascular Pharmacology · 2010
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
Fundersnot available
KeywordsEzetimibeOrlistatMedicineRimonabantInternal medicineEndocrinologyStatinOverweightNiacinMetabolic syndromeSibutramineLipid profileObesityLipoproteinPharmacologyWeight lossCholesterolAntagonistReceptor

Abstract

fetched live from OpenAlex

Small, dense low density lipoprotein (sdLDL) particles are considered an emerging cardiovascular risk factor. Obese patients with mixed dyslipidaemia frequently have elevated sdLDL cholesterol (sdLDL-C) levels. Therefore, agents that favourably modulate the LDL phenotype may be of clinical value in these patients. We review the efficacy of anti-obesity and lipid lowering drugs other than statins on LDL subfractions in patients with mixed dyslipidaemia primarily focusing on those who are overweight/obese. The literature search was based on PubMed listings up to 26 November 2009. In most studies ezetimibe decreases the large and medium LDL subclasses and, to a lesser extent, the sdLDL particles, while it does not substantially influence LDL size. Fibrates and niacin reduce sdLDL particles and shift LDL size towards large, buoyant LDL particles. More studies are needed to elucidate the effects of fish oils and resins on LDL phenotype. Orlistat and rimonabant have been associated with reductions in sdLDL-C levels along with an increase in LDL particle size. We did not find any literature describing the effect of sibutramine on sdLDL profile. Treatment with fibrates and niacin seems to be beneficial in patients with mixed dyslipidaemia. The addition of orlistat may further improve LDL phenotype in overweight/obese patients. Keywords: Mixed dyslipidaemia, ezetimibe, fibrates, nicotinic acid, obesity, orlistat, rimonabant, small, dense LDL, Non-Statin Lipid, Anti-Obesity Drugs, LDL Sub-fractions, sdLDL, sibutramine, Quebec Cardiovascular Study, ischemic heart disease, proteoglycan, LDL receptors, thromboxane A2, thrombogenicity, cardiovascular risk, high density lipoprotein cholesterol, metabolic syndrome, National Cholesterol Education Program Adult Treat-ment Panel III, cardio-vascular disease, fenofi-brate, bezafibrate, gemfibrozil, ciprofibrate, clofibrate, niacin, resins, sequestrants, coleseve-lam, omega-3, fatty acids, fish oil, high density, low density lipoprotein cholesterol, triglycerides, hyperlipidaemia, Lipoprint LDL System, hyper-cholesterolaemia, hyperlipoproteinaemia, LDL apheresisc, fenofibrate, Intraabdominal Adiposity

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.011
GPT teacher head0.335
Teacher spread0.323 · 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