Evidence map›Paper›PMID 42310311›Full record

ArticleNutrition & diabetes2026

Reproducibility of continuous glucose monitoring-derived postprandial glucose features and their association with glycemic control in type 2 diabetes.

Annalisa Giosuè, Roberta Testa, Giovanna D'Abbronzo, Marilena Vitale, Gabriele Riccardi, Olga Vaccaro, Alessandra Corrado, Viktor Skantze, Rikard Landberg, Giuseppina Costabile and 1 more

Abstract read
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Article in Nutrition & diabetes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

11 authors.

Annalisa GiosuèNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy. annalisa.giosue@unina.it.ORCID http://orcid.org/0000-0002-5799-1744
Roberta TestaNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.
Giovanna D'AbbronzoNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.
Marilena VitaleNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.
Gabriele RiccardiNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.
Olga VaccaroNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.
Alessandra CorradoNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.
Viktor SkantzeFraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden.
Rikard LandbergDivision of Food and Nutrition Science, Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden.ORCID http://orcid.org/0000-0002-6399-7608
Giuseppina CostabileNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.
Lutgarda BozzettoNutrition, Diabetes and Metabolism Unit, Department of Clinical Medicine and Surgery, Federico II University of Naples, Naples, Italy.ORCID http://orcid.org/0000-0001-6549-4476

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesTargeting postprandial glucose response (PPGR) is more effective than lowering fasting plasma glucose in improving glycemic control and reducing cardiovascular risk in individuals with type 2 diabetes (T2D). Continuous glucose monitoring (CGM) has the potential to uncover time-related features of PPGR. This study evaluates the within-subject reproducibility of dynamic PPGR parameters obtained by CGM and explores their potential as independent predictors of glycemic control in T2D. SUBJECTS/

methodsA total of 102 individuals with T2D underwent a 7-day CGM and consumed a standardized breakfast twice to assess the 4-h glucose response, described by the following parameters: glucose peak-the highest glucose value; time to peak-time of peak occurrence; delta glucose max-the difference between the peak and fasting glucose; nadir-the lowest post-peak glucose value; incremental area under the glucose curve; mean postprandial glucose-the average interstitial glucose concentration. Intraclass correlation coefficients (ICCs) for both single and average measurements with their 95% confidence intervals (CIs), were calculated for PPGR parameters to estimate their within-subject reproducibility. Multivariable linear regression models assessed the independent predictive contribution of PPGR parameters, fasting glucose, and 2-h postprandial glucose on 7-day CGM metrics and HbA1c.

resultsModerate to good reproducibility for single measurements was observed for mean glucose (ICC: 0.78, 95%CI 0.69-0.84), glucose peak (ICC: 0.69, 95% CI 0.57-0.78), and nadir (0.74, 95% CI 0.64-0.82). Mean postprandial glucose was the strongest predictor of 7-day time in range (β = -0.772, p < 0.001), 7-day mean glucose (β = 0.800, p < 0.001) and HbA1c (β = 0.434, p < 0.001), whereas the glucose peak was the main predictor of short-term glycemic variability, as reflected by the 7-day coefficient of variation (β = 0.258, p = 0.006) and mean amplitude of glucose excursions (β = 0.613, p < 0.001).

conclusionIn individuals with T2D, CGM-derived parameters of PPGR are reproducible and could represent a practical tool to uncover meaningful information about glucose control, which 2-h postprandial glucose fails to predict.

Indexed as

Blood GlucoseContinuous Glucose MonitoringDiabetes Mellitus, Type 2Glycemic ControlPostprandial PeriodAgedBlood Glucose Self-MonitoringFemaleGlycated HemoglobinHumansMaleMiddle AgedReproducibility of ResultsBlood GlucoseGlycated Hemoglobin

Identifiers

PMID42310311
PMCPMC13519019

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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.