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Lipid Treatment Assessment Project 2

2009· article· en· 308 citations· W1974768421 on OpenAlex· 10.1161/circulationaha.108.838466

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

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.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: ObservationalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.950
Threshold uncertainty score
0.228
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

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)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.033
GPT teacher head0.334
Teacher spread
0.301 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

BACKGROUND: Information about physicians' adherence to cholesterol management guidelines remains scant. The present survey updates our knowledge of lipid management worldwide. METHODS AND RESULTS: Lipid levels were determined at enrollment in dyslipidemic adult patients on stable lipid-lowering therapy in 9 countries. The primary end point was the success rate, defined as the proportion of patients achieving appropriate low-density lipoprotein cholesterol (LDL-C) goals for their given risk. The mean age of the 9955 evaluable patients was 62+/-12 years; 54% were male. Coronary disease and diabetes mellitus had been diagnosed in 30% and 31%, respectively, and 14% were current smokers. Current treatment consisted of a statin in 75%. The proportion of patients achieving LDL-C goals according to relevant national guidelines ranged from 47% to 84% across countries. In low-, moderate-, and high-risk groups, mean LDL-C was 119, 109, and 91 mg/dL and mean high-density lipoprotein cholesterol was 62, 49, and 50 mg/dL, respectively. The success rate for LDL-C goal achievement was 86% in low-, 74% in moderate-, and 67% in high-risk patients (73% overall). However, among coronary heart disease patients with > or =2 risk factors, only 30% attained the optional LDL-C goal of <70 mg/dL. In the entire cohort, high-density lipoprotein cholesterol was <40 mg/dL in 19%, 40 to 60 mg/dL in 55%, and >60 mg/dL in 26% of patients. CONCLUSIONS: Although there is room for improvement, particularly in very-high-risk patients, these results indicate that lipid-lowering therapy is being applied much more successfully than it was a decade ago.

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.

The record

Venue
Circulation
Topic
Lipoproteins and Cardiovascular Health
Field
Medicine
Canadian institutions
not available
Funders
Pfizer CanadaPfizer
Keywords
MedicineInternal medicineDiabetes mellitusCholesterolStatinCoronary heart diseaseNational Cholesterol Education ProgramCohortRisk factorLipid profileEndocrinology
Has abstract in OpenAlex
yes