Evidence map›Paper›PMID 40824875›Full record

ArticleDiabetes technology & therapeutics2026

Accuracy of Dexcom G6 Pro and G7 Continuous Glucose Monitors in Patients Treated with Maintenance Dialysis.

Leila R Zelnick, Subbulaxmi Trikudanathan, Yoshio N Hall, Ernest Ayers, Lisa Anderson, Nathaniel Ashford, Evelin Jones, Andrew N Hoofnagle, Ian H de Boer, Irl B Hirsch

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

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

0numbers the graph read from it
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

10 authors.

Leila R ZelnickKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-8461-5111
Subbulaxmi TrikudanathanDivision of Metabolism, Endocrinology, and Nutrition, University of Washington, Seattle, Washington, USA.
Yoshio N HallKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.
Ernest AyersKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.
Lisa AndersonKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.
Nathaniel AshfordKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.
Evelin JonesKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.
Andrew N HoofnagleKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.
Ian H de BoerKidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington, USA.
Irl B HirschDivision of Metabolism, Endocrinology, and Nutrition, University of Washington, Seattle, Washington, USA.ORCID 0000-0003-1675-8417

Funding

Blood Sugar Sensing on Maintenance DialysisR01DK126373 · UNIVERSITY OF WASHINGTON · 2025 to 2025
$814k
NIDDK NIH HHS R01 DK126373
6 · The paper itself

Abstract

BACKGROUND AND

aimsContinuous glucose monitors (CGMs) can comprehensively assess glycemic patterns in patients treated with dialysis, in whom conventional biomarkers such as glycated hemoglobin are inaccurate. Nonetheless, adoption of recent versions of CGMs in this population has been complicated by concerns about interstitial volume expansion, interfering substances, and effects of dialysis treatment. This study aimed to examine the accuracy of the G6 Pro and G7 CGM systems (Dexcom, Inc.) compared with self-monitored blood glucose (SMBG) in a dialysis population.

methodsTwelve participants treated with maintenance dialysis (11 hemodialysis, 1 peritoneal dialysis [PD]) with diabetes wore concurrent G6 Pro and G7 CGMs for a period of 10 days, during which they measured SMBG using a Contour Next glucometer. We summarized CGM-glucometer Pearson correlations, calculated the mean absolute relative difference (MARD) of G6 Pro/G7 and SMBG, created Diabetes Technology Society (DTS) error grids, and investigated the CGM lag time that most closely corresponded with SMBG.

resultsMean (standard deviation [SD]) age of participants was 50 (12) years, 50% were female, mean (SD) diabetes duration was 24 (9) years, and 92% used insulin. Participants collected 245 SMBG measurements over a total of 178 days of CGM. The Pearson correlations of G6 Pro and SMBG, G7 and SMBG, and G6 Pro and G7 were 0.87, 0.88, and 0.95, respectively. The MARDs of G6 Pro versus SMBG and G7 versus SMBG were 21.2% and 16.7%, respectively; excluding one PD participant with highly variable glucose, MARDs were 18.3% and 13.5%. The DTS error grids showed that 96.7% of G6 Pro and 98.0% of G7 measurements were clinically acceptable (Zones A/B) when compared with SMBG. We observed evidence of greater lag times than previously seen in nondialysis populations and substantial between- and within-person variability in CGM performance.

conclusionsAmong patients with diabetes treated with maintenance dialysis, CGM measurements of glucose had high correlation with SMBG, with better performance of the G7 compared with G6 Pro. MARD was higher than previously reported in nondialysis populations, but most values fell within clinically acceptable ranges. While issues around lag time, sensor placement, and interfering substances that may impact CGM performance warrant further investigation, our study findings support the use of CGM to evaluate glycemia in the dialysis population.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 2Diabetic NephropathiesKidney Failure, ChronicRenal DialysisAdultAgedDiabetes Mellitus, Type 1FemaleGlycated HemoglobinHumansMaleMiddle AgedReproducibility of ResultsBlood GlucoseGlycated Hemoglobinaccuracycontinuous glucose monitoringdiabetes mellitusdialysisend-stage kidney disease

Identifiers

PMID40824875
PMCPMC13167265

What Socratic 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 Socratic graph.