Evidence map›Paper›PMID 39213372›Full record

ArticleDiabetes care2024

Accuracy of Continuous Glucose Monitoring in Hemodialysis Patients With Diabetes.

Yoko Narasaki, Kamyar Kalantar-Zadeh, Andrea C Daza, Amy S You, Alejandra Novoa, Renal Amel Peralta, Man Kit Michael Siu, Danh V Nguyen, Connie M Rhee

Abstract read
In one paragraph

Article in Diabetes care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Observational
  5. The Role of Precision Nutrition in Kidney Disease.Clinical journal of the American Society of Nephrology : CJASN · 2026
    Review
  6. Article
  7. Article
  8. Observational
  9. Review
  10. Observational
  11. Article
  12. Observational
  13. Review
  14. Time to Plan for Continuous Glucose Monitoring in Dialysis-Dependent Kidney Failure.Journal of the American Society of Nephrology : JASN · 2025
    Article
  15. Article
  16. Article
  17. Review
  18. 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

9 authors.

Yoko NarasakiDivision of Nephrology, Department of Medicine, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA.
Kamyar Kalantar-ZadehDivision of Nephrology, Department of Medicine, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA.ORCID 0000-0002-8666-0725
Andrea C DazaDivision of Nephrology, Department of Medicine, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA.
Amy S YouDivision of Nephrology, Department of Medicine, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA.
Alejandra NovoaDivision of Nephrology, Department of Medicine, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA.
Renal Amel PeraltaDivision of Nephrology, Hypertension, and Kidney Transplantation, Department of Medicine, University of California Irvine School of Medicine, Orange, CA.
Man Kit Michael SiuDivision of Nephrology, Department of Medicine, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA.
Danh V NguyenDivision of General Internal Medicine, University of California Irvine School of Medicine, Orange, CA.
Connie M RheeDivision of Nephrology, Department of Medicine, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA.ORCID 0000-0002-9703-6469

Funding

Multilevel Time-Dynamic Modeling of Hospitalization and Survival in Patients on DialysisR01DK092232 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KURUM, ESRA, NGUYEN, DANH V · 2011 to 2025
$4.9M
A Randomized Controlled Trial of Thyroid Hormone Supplementation in Hemodialysis PatientsR01DK122767 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RHEE, CONNIE MEEYOUNG · 2019 to 2023
$3.3M
Defining Optimal Transitions of Care in Advanced Kidney Disease: Conservative Management vs. Dialysis ApproachesR01DK124138 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KALANTAR-ZADEH, KAMYAR, RHEE, CONNIE MEEYOUNG · 2020 to 2024
$2.9M
Plant-Focused Nutrition in Patients with Diabetes and Chronic Kidney Disease (PLAFOND Study): A Pilot/Feasibility StudyR01DK132875 · NIDDK · LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER · PI KALANTAR-ZADEH, KAMYAR, RHEE, CONNIE MEEYOUNG · 2023 to 2025
$836k
Continuous Glucose Monitoring in Dialysis Patients to Overcome Dysglycemia Trial (CONDOR TRIAL)R01DK132869 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KALANTAR-ZADEH, KAMYAR, RHEE, CONNIE MEEYOUNG · 2023 to 2025
$781k
DexcomNIDDK NIH HHS R01 DK092232NIDDK 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

objectiveIn the general population, continuous glucose monitoring (CGM) provides convenient and less-invasive glucose measurements than conventional self-monitored blood glucose and results in reduced hypoglycemia and hyperglycemia and increased time in target glucose range. However, accuracy of CGM versus blood glucose is not well established in hemodialysis patients. RESEARCH DESIGN AND

methodsAmong 31 maintenance hemodialysis patients with diabetes hospitalized from October 2020 to May 2021, we conducted protocolized glucose measurements using Dexcom G6 CGM versus blood glucose, with the latter measured before each meal and at night, plus every 30-min during hemodialysis. We examined CGM-blood glucose correlations and agreement between CGM versus blood glucose using Bland-Altman plots, percentage of agreement, mean and median absolute relative differences (ARDs), and consensus error grids.

resultsPearson and Spearman correlations for averaged CGM versus blood glucose levels were 0.84 and 0.79, respectively; Bland-Altman showed the mean difference between CGM and blood glucose was ∼+15 mg/dL. Agreement rates using %20/20 criteria were 48.7%, 47.2%, and 50.2% during the overall, hemodialysis, and nonhemodialysis periods, respectively. Mean ARD (MARD) was ∼20% across all time periods; median ARD was 19.4% during the overall period and was slightly lower during nonhemodialysis (18.2%) versus hemodialysis periods (22.0%). Consensus error grids showed nearly all CGM values were in clinically acceptable zones A (no harm) and B (unlikely to cause significant harm).

conclusionsIn hemodialysis patients with diabetes, although MARD values were higher than traditional optimal analytic performance thresholds, error grids showed nearly all CGM values were in clinically acceptable zones. Further studies are needed to determine whether CGM improves outcomes in hemodialysis patients.

Indexed as

Blood GlucoseRenal DialysisAgedBlood Glucose Self-MonitoringContinuous Glucose MonitoringDiabetes MellitusFemaleHumansMaleMiddle AgedBlood Glucose

Identifiers

PMID39213372
PMCPMC11502529

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.