Evidence map›Paper›PMID 42224118›Full record

ArticleDiabetes care2026

Continuous Glucose Monitoring and Mortality Risk Among U.S. Veterans Receiving Dialysis With Diabetes.

Yoko Narasaki, Kamyar Kalantar-Zadeh, Yaara Zisman-Ilani, David C Klonoff, Csaba P Kovesdy, Zhaoping Li, Anna Jin, Susan Crowley, Justin M Belcher, Patrick Gee and 7 more

Abstract read
In one paragraph

Article in Diabetes care, 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

17 authors.

Yoko NarasakiDavid Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA.
Kamyar Kalantar-ZadehDavid Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA.ORCID 0000-0002-8666-0725
Yaara Zisman-IlaniBarnett College of Public Health, Temple University, Philadelphia, PA.
David C KlonoffDiabetes Research Institute, Mills-Peninsula Medical Center (Sutter Health), San Mateo, CA.ORCID 0000-0002-0624-698X
Csaba P KovesdyUniversity of Tennessee Health Science Center, Memphis, TN.
Zhaoping LiDavid Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA.
Anna JinTibor Rubin Veterans Affairs Long Beach Medical Center, Long Beach, CA.
Susan CrowleyYale University School of Medicine, New Haven, CT.
Justin M BelcherYale University School of Medicine, New Haven, CT.
Patrick GeeiAdvocate, Inc., Richmond, VA.
Greg E GinTibor Rubin Veterans Affairs Long Beach Medical Center, Long Beach, CA.
Mark JordanTibor Rubin Veterans Affairs Long Beach Medical Center, Long Beach, CA.
Amy S YouDavid Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA.
Andrea C DazaDavid Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA.
Ramy HannaUniversity of California Irvine School of Medicine, Orange, CA.
Danh V NguyenVeterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA.
Connie M RheeDavid Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA.ORCID 0000-0002-9703-6469

Funding

NIDDK NIH HHS R01-DK092232NIDDK NIH HHS R01-DK122767NIDDK NIH HHS R01-DK124138NIDDK NIH HHS R01-DK132869NIDDK NIH HHS R01-DK132875
6 · The paper itself

Abstract

objectivePatients receiving dialysis who have diabetes have a high burden of dysglycemia. Whereas traditional glycemic markers have limited accuracy and convenience in dialysis, continuous glucose monitoring (CGM) provides automated, less invasive, and more comprehensive glycemic data than do conventional measures. However, it remains unclear whether CGM is associated with improved clinical outcomes in patients undergoing dialysis. RESEARCH DESIGN AND

methodsWe examined the association between CGM use versus non-CGM use and survival among U.S. veterans receiving dialysis who also have diabetes, using linked national Veterans Affairs, U.S. Renal Data System, and Medicare data. We examined data from veterans undergoing dialysis and with diabetes with incident CGM use (newly prescribed CGM) versus non-CGM use over the period January 2012 to December 2023 matched by propensity score (PS) to address confounding by indication and who were followed for all-cause mortality events through February 2025. Associations of CGM use versus non-CGM use with death were evaluated using complete case analysis and multiple imputation.

resultsAmong 2,008 patients in the complete case analysis cohort, CGM use was associated with a lower mortality risk in PS-matched unadjusted and doubly adjusted Cox models (reference: non-CGM use; hazard ratio [HR] 0.86 [95% CI 0.76, 0.98]; and 0.83 [95% CI 0.75, 0.92], respectively). Among 3,088 patients in the multiple imputation cohort, CGM use was also associated with greater survival in PS-matched unadjusted and doubly adjusted Cox models (HR 0.88 [95% CI 0.77, 0.99]; and 0.84 [95% CI 0.73, 0.96], respectively).

conclusionsIn veterans receiving dialysis who also had diabetes, incident CGM use was associated with better survival versus non-CGM use. Further studies are needed to determine underlying mechanisms and the impact of CGM on other dialysis outcomes.

Indexed as

Continuous Glucose MonitoringDiabetes MellitusRenal DialysisAgedBlood GlucoseFemaleHumansMaleMiddle AgedUnited StatesVeteransBlood Glucose

Identifiers

PMID42224118
PMCPMC13294783

What Socratic holds

Textmetadata
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.