Evidence map›Paper›PMID 42901039›Full record

Trial reportJournal of diabetes and its complications2026

Association of continuous glucose monitoring metrics with cardiovascular and kidney outcomes in type 2 diabetes: Data from the GRADE-CGM substudy.

Mengyao Tang, David M Nathan, Deborah J Wexler, Melissa S Putman, John M Higgins, Hui Zheng, Eugene P Rhee, Ian H de Boer, Sahir Kalim

Abstract readMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Journal of diabetes and its complications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Mengyao TangDivision of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States of America; Harvard Medical School, Boston, MA, United States of America. Electronic address: mtang11@mgh.harvard.edu.
David M NathanHarvard Medical School, Boston, MA, United States of America; Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States of America.
Deborah J WexlerHarvard Medical School, Boston, MA, United States of America; Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States of America.
Melissa S PutmanHarvard Medical School, Boston, MA, United States of America; Diabetes Center, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States of America.
John M HigginsHarvard Medical School, Boston, MA, United States of America; Department of Pathology and Center for Systems Biology, Massachusetts General Hospital, Boston, MA, United States of America.
Hui ZhengHarvard Medical School, Boston, MA, United States of America; Center for Biostatistics, Massachusetts General Hospital, Boston, MA, United States of America.
Eugene P RheeDivision of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States of America; Harvard Medical School, Boston, MA, United States of America.
Ian H de BoerKidney Research Institute and Division of Nephrology, University of Washington, Seattle, WA, United States of America; Veterans Affairs Puget Sound Health Care System, Seattle, WA, United States of America.
Sahir KalimDivision of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA, United States of America; Harvard Medical School, Boston, MA, United States of America.

Funding

P&F programP30DK135043 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Aaron S Leong · 2023 to 2026
$5.4M
Hypoglycemia and glycemic control in patients treated with dialysisR01DK126373 · NIDDK · UNIVERSITY OF WASHINGTON · PI Leila R Zelnick, Ian H de Boer · 2020 to 2026
$4.2M
Optimizing Glycemic Monitoring and Management in People with Type 2 Diabetes and Chronic Kidney DiseaseK23DK143316 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Mengyao Tang · 2026 to 2026
$197k
NIDDK NIH HHS K23 DK143316NIDDK NIH HHS P30 DK135043NIDDK NIH HHS R01 DK126373
6 · The paper itself

Abstract

aimsWe compared associations of CGM-derived time in range (TIR) and glucose management indicator (GMI) vs. HbA1c with CVD and eGFR decline in type 2 diabetes.

methodsWe studied 1363 participants with ≥10-day blinded CGM in the GRADE-CGM Substudy. Exposures were TIR and GMI, with HbA1c as comparator. Cox models estimated hazard ratios (HR) for the composite of any CVD or all-cause death. Linear mixed-effects models estimated eGFR slope. Models were adjusted for age, sex, race/ethnicity, treatment group, diabetes duration, and baseline eGFR, then mutually adjusted each CGM metric with HbA1c.

resultsOver median 2.3 years, 74 CVD or death occurred, eGFR slope was -2.37 mL/min/1.73m

conclusionsIn type 2 diabetes, GMI and HbA1c were comparably associated with cardiovascular and kidney outcomes, whereas TIR was associated with cardiovascular outcomes only.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2Diabetic AngiopathiesDiabetic NephropathiesAgedBlood GlucoseContinuous Glucose MonitoringDiabetic CardiomyopathiesFemaleGlomerular Filtration RateGlycated HemoglobinHumansMaleMiddle AgedBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanCardiovascular outcomesContinuous glucose monitoringeGFRHbA1cTime in rangeType 2 diabetes

Identifiers

PMID42901039
PMCPMC13739211

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Registered trials

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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.