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Record W2033942337 · doi:10.1186/1472-6823-10-3

The weight lowering effect of sibutramine and its impact on serum lipids in cardiovascular high risk patients with and without type 2 diabetes mellitus - an analysis from the SCOUT lead-in period

2010· article· en· W2033942337 on OpenAlexaff
Peter Weeke, Charlotte Andersson, Emil Loldrup Fosbøl, Bente Brendorp, Lars Køber, Arya M. Sharma, Nick Finer, Philip James, Ian D. Caterson, Richard A. Rode, Christian Torp‐Pedersen

Bibliographic record

VenueBMC Endocrine Disorders · 2010
Typearticle
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
FundersAbbott Laboratories
KeywordsMedicineSibutramineInternal medicineEndocrinologyDiabetes mellitusOverweightLipid profileObesityType 2 diabetesType 2 Diabetes MellitusCholesterolHigh-density lipoproteinWeight loss

Abstract

fetched live from OpenAlex

BACKGROUND: Obesity, type 2 diabetes mellitus (T2D) and unhealthy blood lipid profile are strongly associated with the risk of developing cardiovascular disease (CVD). We examined whether blood lipid changes with short term administration of the weight lowering drug, sibutramine and lifestyle modification in obese and overweight high-risk patients was associated with T2D status at screening. METHODS: The Sibutramine Cardiovascular OUTcomes (SCOUT) trial included obese and overweight patients at increased risk of cardiovascular events. All patients received guidance on diet and exercise plus once-daily 10 mg sibutramine during the 6-week, single blind lead-in period. Multivariable regression models were used to investigate factors associated with changes in lipid levels during the first four weeks of treatment. RESULTS: A total of 10 742 patients received at least one dose of sibutramine during the 6-week lead-in period of SCOUT. After four weeks, patients experienced mean reductions in low density lipoprotein (LDL-C) 0.19 mmol/L, high density lipoprotein (HDL-C) 0.019 mmol/L, very low density lipoprotein (VLDL-C) 0.08 mmol/L, total cholesterol (TC) 0.31 mmol/L and triglycerides 0.24 mmol/L (p < 0.0001 for each). Four week changes in LDL-C, HDL-C and total cholesterol for patients without vs. with T2D were: LDL-C:-0.25 mmol/L vs. -0.18 mmol/L, P = 0.0004; HDL-C: -0.03 mmol/L vs. -0.02 mmol/L, P = 0.0014; total cholesterol: -0.37 mmol/l vs. -0.29 mmol/l, P = 0.0009. Multivariable regression analysis showed that similar decreases in body mass index (BMI) affected lipid changes differently according to diabetes status. A 1 kg/m2 decrease in BMI in patients with T2D was associated with -0.09 mmol/L in LDL-C (P < 0.0001) and -0.01 mmol/L in HDL-C (P = 0.0001) but larger changes of -0.16 mmol/L LDL-C and -0.03 mmol/L in HDL-C (P < 0.0001 for both) in patients without T2D. CONCLUSION: Short term weight management with sibutramine therapy in obese or overweight high-risk patients induced significant mean reductions for all lipids. Those without T2D benefited most. Patients with hyperlipidaemia and the less obese patients also had greater falls in LDL-C and TC during weight loss. The trial is registered at ClinicalTrial.gov number: NCT00234832.

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)0.002
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.003
GPT teacher head0.254
Teacher spread0.251 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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