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Record W2506770244 · doi:10.2196/resprot.5073

Effect of Sitagliptin and Metformin on Prediabetes Progression to Type 2 Diabetes - A Randomized, Double-Blind, Double-Arm, Multicenter Clinical Trial: Protocol for the Sitagliptin and Metformin in PreDiabetes (SiMePreD) Study

2016· article· en· W2506770244 on OpenAlexvenueno aff
Poobalan Naidoo, Jeffrey J. Wing, Virendra Rambiritch

Bibliographic record

VenueJMIR Research Protocols · 2016
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPrediabetesSitagliptinMetforminMedicineType 2 diabetesSitagliptin PhosphateDiabetes mellitusRandomized controlled trialClinical trialProtocol (science)Internal medicineEndocrinologyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The high prevalence and incidence of type 2 diabetes mellitus (DM), and its associated morbidity and mortality, has prompted growing international interest and effort in the primary prevention of this disease. Primary prevention is possible since type 2 DM is preceded by prediabetes, offering a window opportunity to treat patients, and prevent the emergence of advanced disease. Sitagliptin is an oral dipeptidyl peptidase-IV inhibitor that preserves existing beta cell function and increases beta cell mass. These two effects have been demonstrated both in vitro and in animal studies, and current clinical data show that sitagliptin is safe. Metformin, a biguanide, reduces insulin resistance and inhibits hepatic gluconeogenesis, and has an excellent safety profile. The combination of metformin and sitagliptin, targeting both characteristics of prediabetes (insulin resistance and progressive beta cell degeneration), may potentially slow or halt the progression from prediabetes to type 2 DM. This paper describes the rationale and design of the Sitagliptin and Metformin in PreDiabetes (SiMePreD) study. OBJECTIVE: The aim of this study is to determine the effect of sitagliptin and metformin on progression from prediabetes to type 2 DM. The objectives of the study are to determine the effects of metformin and placebo on glycemic endpoints, the effects of sitagliptin and metformin on glycemic endpoints, the effects of metformin and placebo on incidence of cardiovascular disease and death, and the effects of sitagliptin and metformin on incidence of cardiovascular disease and death. METHODS: This is a randomized, double-blind, multicenter clinical study that will determine if the combination of metformin and sitagliptin is effective in preventing the progression from prediabetes to type 2 DM. The study will contain two arms (metformin/sitagliptin and metformin/placebo). Primary endpoints include the number of subjects progressing from prediabetes to type 2 DM, the number of cardiovascular events, and the number of deaths. The planned duration of the study is five years, and 410 subjects will be included in each group. Data analyses will include clinically relevant measures (eg, numbers needed to treat and numbers needed to harm) and will be performed according to the intention-to-treat principle. RESULTS: This study is currently in the process of acquiring research funding. CONCLUSIONS: The SiMePreD study is the first study to investigate the utility of sitagliptin in combination with metformin for the primary prevention of type 2 DM. .

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.007
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0220.004

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 head0.266
GPT teacher head0.582
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations15
Published2016
Admission routes1
Has abstractyes

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