Evidence map›Paper›PMID 35134821›Full record

ArticleThe American journal of clinical nutrition2022

Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition.

Jordi Merino, Inbar Linenberg, Kate M Bermingham, Sajaysurya Ganesh, Elco Bakker, Linda M Delahanty, Andrew T Chan, Joan Capdevila Pujol, Jonathan Wolf, Haya Al Khatib and 5 more

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in The American journal of clinical nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03479866 (Predicting Inter-individual Differences in Biochemical and Behavioral Response to Meals With Different Nutritional Compositions Using Metabolomic and Microbiome Profiling.), which is not on this map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.9field-weighted citation impact, top 5% 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.

NCT03479866 naunknown statusnot on this map

Predicting Inter-individual Differences in Biochemical and Behavioral Response to Meals With Different Nutritional Compositions Using Metabolomic and Microbiome Profiling.

TypeinterventionalSponsorGuy's and St Thomas' NHS Foundation TrustRan2018 to 2023Enrolled2,500ConditionsDiabetes, Heart Diseases, Diet Habit, Diet ModificationArmsDietary intervention
3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 37 citations in OpenAlex.

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  15. Use of technology in prediabetes and precision prevention.Journal of diabetes investigation · 2025
    Review
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  17. Leveraging continuous glucose monitoring as a catalyst for behaviour change: a scoping review.The international journal of behavioral nutrition and physical activity · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 6 institutions in 4 countries.

Jordi MerinoDiabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.ORCID 0000-0001-8312-1438
Inbar LinenbergZoe Ltd, London, United Kingdom.
Kate M BerminghamDepartment of Nutritional Sciences, King's College London, London, United Kingdom.
Sajaysurya GaneshZoe Ltd, London, United Kingdom.
Elco BakkerZoe Ltd, London, United Kingdom.
Linda M DelahantyDepartment of Medicine, Harvard Medical School, Boston, MA, USA.
Andrew T ChanClinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-7284-6767
Joan Capdevila PujolZoe Ltd, London, United Kingdom.
Jonathan WolfZoe Ltd, London, United Kingdom.ORCID 0000-0002-0530-2257
Haya Al KhatibZoe Ltd, London, United Kingdom.
Paul W FranksDepartment of Clinical Sciences, Lund University, Malmö, Sweden.
Tim D SpectorDepartment of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom.
Jose M OrdovasJean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA.ORCID 0000-0002-7581-5680
Sarah E BerryDepartment of Nutritional Sciences, King's College London, London, United Kingdom.ORCID 0000-0002-5819-5109
Ana M ValdesSchool of Medicine, University of Nottingham, Nottingham, United Kingdom.
ZOE (United Kingdom) · GBHarvard University · USKing's College London · GBBroad Institute · USTufts University · USUniversity of Nottingham · GB

Funding

ROLE OF DIETARY CONSTITUENTS ON GENE EXPRESSION IN INTESTINAL EPITHELIUMP30DK040561 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Elizabeth Austen Lawson, Takara Leah Stanley · 1994 to 2026
$31.6M
New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
Precision Prevention Research ProgramR35CA253185 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Andrew T Chan · 2020 to 2026
$6.9M
Biotechnology and Biological Sciences Research Council BB/NO12739/1Department of HealthMedical Research CouncilNCI NIH HHS R35 CA253185NIDDK NIH HHS P30 DK040561NIDDK NIH HHS P30 DK111022NIH HHS P30 DK40561Wellcome Trust
6 · The paper itself

Abstract

backgroundContinuous glucose monitor (CGM) devices enable characterization of individuals' glycemic variation. However, there are concerns about their reliability for categorizing glycemic responses to foods that would limit their potential application in personalized nutrition recommendations.

objectivesWe aimed to evaluate the concordance of 2 simultaneously worn CGM devices in measuring postprandial glycemic responses.

methodsWithin ZOE PREDICT (Personalised Responses to Dietary Composition Trial) 1, 394 participants wore 2 CGM devices simultaneously [n = 360 participants with 2 Abbott Freestyle Libre Pro (FSL) devices; n = 34 participants with both FSL and Dexcom G6] for ≤14 d while consuming standardized (n = 4457) and ad libitum (n = 5738) meals. We examined the CV and correlation of the incremental area under the glucose curve at 2 h (glucoseiAUC0-2 h). Within-subject meal ranking was assessed using Kendall τ rank correlation. Concordance between paired devices in time in range according to the American Diabetes Association cutoffs (TIRADA) and glucose variability (glucose CV) was also investigated.

resultsThe CV of glucoseiAUC0-2 h for standardized meals was 3.7% (IQR: 1.7%-7.1%) for intrabrand device and 12.5% (IQR: 5.1%-24.8%) for interbrand device comparisons. Similar estimates were observed for ad libitum meals, with intrabrand and interbrand device CVs of glucoseiAUC0-2 h of 4.1% (IQR: 1.8%-7.1%) and 16.6% (IQR: 5.5%-30.7%), respectively. Kendall τ rank correlation showed glucoseiAUC0-2h-derived meal rankings were agreeable between paired CGM devices (intrabrand: 0.9; IQR: 0.8-0.9; interbrand: 0.7; IQR: 0.5-0.8). Paired CGMs also showed strong concordance for TIRADA with a intrabrand device CV of 4.8% (IQR: 1.9%-9.8%) and an interbrand device CV of 3.2% (IQR: 1.1%-6.2%).

conclusionsOur data demonstrate strong concordance of CGM devices in monitoring glycemic responses and suggest their potential use in personalized nutrition.This trial was registered at clinicaltrials.gov as NCT03479866.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDietGlucoseHumansMealsReproducibility of ResultsBlood GlucoseGlucosecontinuous glucose monitoringdietglycemic variabilitymeal responsesprecision nutrition

Identifiers

PMID35134821
PMCPMC9170468
OpenAlexW4212862774

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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 Socratic graph.