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Record W2115236055 · doi:10.2337/dc09-1867

Changes in Prandial Glucagon Levels After a 2-Year Treatment With Vildagliptin or Glimepiride in Patients With Type 2 Diabetes Inadequately Controlled With Metformin Monotherapy

2010· article· en· W2115236055 on OpenAlexaff
Bo Åhrén, James E. Foley, Ele Ferrannini, David R. Matthews, Bernard Zinman, S. Dejager, Vivian Fonseca

Bibliographic record

VenueDiabetes Care · 2010
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersNational Institute for Health and Care Research
KeywordsVildagliptinGlimepirideMedicineMetforminPostprandialSulfonylureaType 2 diabetesInternal medicineEndocrinologyDiabetes mellitusGlucagon-like peptide-1Post-prandialGlucagonInsulin

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine if the dipeptidyl peptidase-4 inhibitor vildagliptin more effectively inhibits glucagon levels than the sulfonylurea glimepiride during a meal. RESEARCH DESIGN AND METHODS: Glucagon responses to a standard meal were measured at baseline and study end point (mean 1.8 years) in a trial evaluating add-on therapy to metformin with 50 mg vildagliptin b.i.d. compared with glimepiride up to 6 mg q.d. in type 2 diabetes (baseline A1C 7.3 +/- 0.6%). RESULTS: A1C and prandial glucose area under the curve (AUC)(0-2 h) were reduced similarly in both groups, whereas prandial insulin AUC(0-2 h) increased to a greater extent by glimepiride. Prandial glucagon AUC(0-2 h) (baseline 66.6 +/- 2.3 pmol . h(-1) . l(-1)) decreased by 3.4 +/- 1.6 pmol . h(-1) . l(-1) by vildagliptin (n = 137) and increased by 3.8 +/- 1.7 pmol . h(-1) . l(-1) by glimepiride (n = 121). The between-group difference was 7.3 +/- 2.1 pmol . h(-1) . l(-1) (P < 0.001). CONCLUSIONS: Vildagliptin therapy but not glimepiride improves postprandial alpha-cell function, which persists for at least 2 years.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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.

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

Citations87
Published2010
Admission routes1
Has abstractyes

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