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Record W2097663033 · doi:10.2337/diacare.27.2.441

Comparison of the [13C]Glucose Breath Test to the Hyperinsulinemic-Euglycemic Clamp When Determining Insulin Resistance

2004· article· en· W2097663033 on OpenAlexafffund
Richard Lewanczuk, Breay W. Paty, Ellen L. Toth

Bibliographic record

VenueDiabetes Care · 2004
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsClampMedicineInsulin resistanceInternal medicineGlucose clamp techniqueEndocrinologyInsulinDiabetes mellitusGlucose uptakeGlucose tolerance testCarbohydrate metabolismInsulin sensitivityQuantitative insulin sensitivity check indexType 2 diabetesBreath test

Abstract

fetched live from OpenAlex

OBJECTIVE: With increasing emphasis on the recognition of the metabolic syndrome and early type 2 diabetes, a clinically useful measure of insulin resistance is desirable. The purpose of this study was to evaluate whether an index of glucose metabolism, as measured by (13)CO(2) generation from ingested [(13)C]glucose, would correlate with indexes from the hyperinsulinemic-euglycemic clamp. RESEARCH DESIGN AND METHODS: A total of 26 subjects with varying degrees of insulin sensitivity underwent both the [(13)C]glucose breath test and the hyperinsulinemic-euglycemic clamp. Results from the [(13)C]glucose breath test were compared with measures of insulin sensitivity from the glucose clamp as well as with other commonly used indexes of insulin sensitivity. RESULTS: There was a strong correlation between the [(13)C]glucose breath test result and the glucose disposal rate (r = 0.69, P < 0.0001) and insulin sensitivity index (r = 0.69, P < 0.0001) from the insulin clamp. The magnitude of these correlations compared favorably with QUICKI and were superior to the homeostasis model assessment. CONCLUSIONS: The [(13)C]glucose breath test may provide a useful noninvasive assessment of insulin sensitivity.

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)0.001
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 score0.362
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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

Citations49
Published2004
Admission routes2
Has abstractyes

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