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Equal improvement in glycaemia with lixisenatide given before breakfast or the main meal of the day

2014· article· en· W2118929450 on OpenAlexaff
Bo Åhrén, Н. В. Ворохобина, Elisabeth Souhami, Nacima Demil, Jenny Ye, Ronnie Aronson

Bibliographic record

VenueJournal of Diabetes and its Complications · 2014
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsLMC Diabetes & Endocrinology (Canada)
Fundersnot available
KeywordsLixisenatideMedicinePostprandialMetforminMealInternal medicineType 2 diabetesDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

AIMS: The aim of this study is to explore whether administration timing affects glycaemic control by lixisenatide once-daily in type 2 diabetes mellitus (T2DM). METHODS: A phase IIIb, open-label, 1:1 randomized, active-controlled, 24-week multicentre study of T2DM patients inadequately controlled on metformin was conducted. Patients were administered lixisenatide before breakfast or the main meal. The primary endpoint was change from baseline at week 24 in glycated haemoglobin (HbA1c). Other endpoints: changes in body weight, fasting plasma glucose (FPG), 7-point self-monitored plasma glucose (SMPG) and Diabetes Treatment Satisfaction Questionnaire status (DTSQs) score. Adverse events (AEs) were monitored. RESULTS: Mean change in HbA1c from baseline at week 24 was -0.65% (-7.1mmol/mol; main meal) and -0.74% (-8.1mmol/mol; breakfast). Mean changes in FPG, body weight and DTSQs score were comparable between groups. The mean change in body weight (kg) was -2.60 (main meal) and -2.80 (breakfast group). The 7-point SMPG profiles showed greatest reductions in postprandial glucose after the meal at which lixisenatide was administered, with a residual effect seen on the subsequent meal. AE rates were similar between groups, including gastrointestinal AEs. CONCLUSIONS: Lixisenatide before the main meal was noninferior to lixisenatide before breakfast in patients insufficiently controlled on metformin. Lixisenatide treatment allows flexibility in administration timing.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.143

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)

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 head0.241
Teacher spread0.229 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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