Evidence map›Paper›PMID 28681942›Full record

ArticleClinical endocrinology2017

Time to glucose peak during an oral glucose tolerance test identifies prediabetes risk.

Stephanie T Chung, Joon Ha, Anthony U Onuzuruike, Kannan Kasturi, Mirella Galvan-De La Cruz, Brianna A Bingham, Rafeal L Baker, Jean N Utumatwishima, Lilian S Mabundo, Madia Ricks and 2 more

Open access · greenAbstract read
In one paragraph

Article in Clinical endocrinology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
5.3field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

49 citing papers in PubMed, 77 citations in OpenAlex.

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  5. Glucose curve morphology and peak time as biomarkers of metabolic health.American journal of physiology. Endocrinology and metabolism · 2026
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  9. TheInternational journal of molecular sciences · 2025
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  17. Frontiers in nutrition · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Stephanie T ChungSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.ORCID http://orcid.org/0000-0001-6989-0417
Joon HaLaboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Anthony U OnuzuruikeSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Kannan KasturiEunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health (NIH), Bethesda, MD, USA.
Mirella Galvan-De La CruzSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Brianna A BinghamSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Rafeal L BakerSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Jean N UtumatwishimaSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Lilian S MabundoSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Madia RicksSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Arthur S ShermanLaboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
Anne E SumnerSection on Ethnicity and Health, Diabetes Endocrinology and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH), Bethesda, MD, USA.
National Institutes of Health · US

Funding

Modeling Pathogenesis of Type 2 DiabetesZIADK075137 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI SHERMAN, ARTHUR · 2016 to 2025
$3.3M
Nested Study: Identifying Risk for Diabetes and Heart Disease in Women: A Study of African-American, African and White Federal Employees and ContractorsZIADK075105 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI CHUNG, STEPHANIE THERESE · 2014 to 2025
$1.8M
Identifying Risk for Diabetes and Heart Disease in Women: A Study of African-American, African and White Federal Employees and ContractorsZIADK075117 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI SUMNER, ANNE · 2015 to 2018
$1.2M
Intramural NIH HHS Z99 DK999999
6 · The paper itself

Abstract

contextMorphological characteristics of the glucose curve during an oral glucose tolerance test (OGTT) (time to peak and shape) may reflect different phenotypes of insulin secretion and action, but their ability to predict diabetes risk is uncertain.

objectiveTo compare the ability of time to glucose peak and curve shape to detect prediabetes and β-cell function. DESIGN AND

participantsIn a cross-sectional evaluation using an OGTT, 145 adults without diabetes (age 42±9 years (mean±SD), range 24-62 years, BMI 29.2±5.3 kg/m

main outcome measuresPrediabetes and disposition index (DI)-a marker of β-cell function.

resultsPrediabetes was diagnosed in 36% (52/145) of participants. Peak>30 minutes, not monophasic curve, was associated with increased odds of prediabetes (OR: 4.0 vs 1.1; P<.001). Both monophasic curve and peak>30 minutes were associated with lower DI (P≤.01). Time to glucose peak and glucose area under the curves (AUC) were independent predictors of DI (adjR

conclusionGlucose peak >30 minutes was a stronger independent indicator of prediabetes and β-cell function than the monophasic curve. Time to glucose peak may be an important tool that could enhance prediabetes risk stratification.

Indexed as

AdultArea Under CurveCross-Sectional StudiesGlucose Tolerance TestHumansMiddle AgedPrediabetic StatePredictive Value of TestsRisk AssessmentTime FactorsYoung Adultglucose curveinsulin secretioninsulin sensitivityoral glucose tolerance testpancreatic functionprediabetic phenotype

Identifiers

PMID28681942
PMCPMC5658251
OpenAlexW2731692501

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.