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Control of Lipids at Baseline in the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) Trial

2009· article· en· W1983031803 on OpenAlexaboutno aff
Georgia Pambianco, M. Lombardero, Vera Bittner, Alan D. Forker, Frank P. Kennedy, Ashok Krishnaswami, Arshag D. Mooradian, Rodica Pop‐Busui, Jamal S. Rana, Annabelle Rodríguez, Michael W. Steffes, Trevor J. Orchard

Bibliographic record

VenuePreventive Cardiology · 2009
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineDiabetes mellitusInternal medicineCholesterolTriglycerideCoronary artery diseaseRandomizationAngioplastyRevascularizationCardiologyLipoproteinRandomized controlled trialEndocrinologyMyocardial infarction

Abstract

fetched live from OpenAlex

In order to examine lipids, a major treatment parameter in those with diabetes and heart disease, the authors analyzed baseline data from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial. The study consisted of 2368 participants with type 2 diabetes and coronary artery disease from 49 sites in 6 countries (2295 provided lipid measurements). Fifty-nine percent of participants had a low-density lipoprotein (LDL) cholesterol level < 100 mg/dL. Levels of total, LDL, and non-high-density lipoprotein (HDL) cholesterol and triglycerides differed by age group (younger than 55, 55-64, and 65 years and older); they were lowest in those aged 65 years. Women had higher total, LDL, and non-HDL cholesterol values. Education was associated with lower total, LDL, and non-HDL cholesterol levels. LDL cholesterol and triglyceride values were lower in the United States and Canada. Adjustment for age, sex, education level, randomization year, and medication did not eliminate these differences. Geographic variation was seen and was not fully accounted for by demographic or treatment characteristics (all P values < .05).

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)0.001
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 score0.270
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 integrity0.0000.000
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 head0.012
GPT teacher head0.252
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

Citations9
Published2009
Admission routes1
Has abstractyes

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