Evidence map›Paper›PMID 40504990›Full record

ArticleDiabetes care2025

Detecting Hyperglycemia Using Biomarkers Versus Continuous Glucose Monitoring.

Natalie Rula Daya, Michael Fang, Jung-Im Shin, James S Pankow, Pamela L Lutsey, Arielle Valint, Justin B Echouffo-Tcheugui, Scott Zeger, Elizabeth Selvin

Abstract read
In one paragraph

Article in Diabetes care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Article
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  6. Article
  7. 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.

Natalie Rula DayaDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.ORCID 0000-0002-2257-0480
Michael FangDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.ORCID 0000-0003-2849-1780
Jung-Im ShinDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.ORCID 0000-0003-0374-6927
James S PankowDivision of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN.
Pamela L LutseyDivision of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN.
Arielle ValintUniversity of North Carolina Gillings School of Public Health, Chapel Hill, NC.
Justin B Echouffo-TcheuguiDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.ORCID 0000-0002-8460-1617
Scott ZegerDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Elizabeth SelvinDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.ORCID 0000-0001-6923-7151

Funding

CARDIOVASCULAR EPIDEMIOLOGY INSTITUTIONAL TRAININGT32HL007024 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Elizabeth Selvin · 1985 to 2026
$17.5M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - COORDINATING CENTER - TASK AREA B.2 AND B.375N92022D00001 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI COUPER, DAVID · 2022 to 2025
$13.7M
Diabetes and Prediabetes in Older Adults in ARICR01DK089174 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2011 to 2020
$6.4M
Medication Use and Adverse Events in CKDR01DK115534 · NIDDK · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Alexander R Chang, Morgan Erika Grams · 2018 to 2026
$5.7M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00003 · NHLBI · UNIVERSITY OF MINNESOTA · PI LUTSEY, PAMELA · 2022 to 2025
$5.1M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00005 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WAGENKNECHT, LYNNE · 2022 to 2025
$5.0M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00004 · NHLBI · UNIVERSITY OF MISSISSIPPI MED CTR · PI WINDHAM, BEVERLY GWEN · 2022 to 2025
$4.8M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00002 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CORESH, JOSEF · 2022 to 2025
$4.7M
Clinical relevance of glucose patterns in older adultsR01DK128837 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2021 to 2024
$2.7M
Effects of the DASH diet on glucose patterns in adults with type 2 diabetesR01DK128900 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2021 to 2025
$2.6M
Glucose instability and neurocognitive outcomes in older adultsRF1AG074044 · NIA · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2021 to 2021
$2.4M
Challenges to Guideline-Recommended Diabetes Care in the United StatesR01DK139324 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI Jung-Im Shin · 2025 to 2026
$1.4M
NHLBI NIH HHS 75N92022D00001NHLBI NIH HHS 75N92022D00002NHLBI NIH HHS 75N92022D00003NHLBI NIH HHS 75N92022D00004NHLBI NIH HHS 75N92022D00005NHLBI NIH HHS K23 HL153774NHLBI NIH HHS K24 HL152440NHLBI NIH HHS T32 HL007024NIA NIH HHS R01 AG074044NIA NIH HHS RF1 AG074044NIDDK NIH HHS K01 DK138273NIDDK NIH HHS R01 DK089174NIDDK NIH HHS R01 DK115534NIDDK NIH HHS R01 DK128837NIDDK NIH HHS R01 DK128900NIDDK NIH HHS R01 DK139324
6 · The paper itself

Abstract

objectiveTo evaluate the concordance of glycated albumin, fructosamine, 1,5-anhydroglucitol (1,5-AG), and hemoglobin A1c (HbA1c) with continuous glucose monitor (CGM) metrics of hyperglycemia and glycemic control in a diverse population of adults with type 2 diabetes. RESEARCH DESIGN AND

methodsThis was a pooled cross-sectional analysis of 552 adults, ages 30-97 years old, with diabetes. Participants wore a CGM for up to 2 weeks, and we evaluated the agreement between blood biomarkers (glycated albumin, fructosamine, and 1,5-AG) with CGM-defined metrics of hyperglycemia and glycemic control.

resultsOf the 552 participants (mean age 74 years, 53% women, 36% Black), the median of mean CGM glucose was 132 mg/dL, and participants spent on average 84% of their time in range (70-180 mg/dL). CGM mean glucose was strongly related to HbA1c (r = 0.72), glycated albumin (r = 0.64), and fructosamine (r = 0.64) but weakly related to 1,5-AG (r = 0.46). Results were similar for time above range (>180 mg/dL). Glycated albumin and fructosamine performed similarly to HbA1c in the detection of target time in and above range (c-statistics ranged from 0.85 to 0.94).

conclusionsGlycated albumin and fructosamine had similar associations with CGM-defined metrics of hyperglycemia compared with HbA1c. These three biomarkers performed similarly in the detection of time above range and in range. Our results provide evidence for the utility of glycated albumin and fructosamine as alternate measures of hyperglycemia.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 2HyperglycemiaAdultAgedAged, 80 and overBiomarkersContinuous Glucose MonitoringCross-Sectional StudiesDeoxyglucoseFemaleFructosamineGlycated HemoglobinGlycated Serum AlbuminGlycation End Products, Advanced1,5-anhydroglucitolBiomarkersBlood GlucoseDeoxyglucoseFructosamineGlycated HemoglobinGlycated Serum AlbuminGlycation End Products, AdvancedSerum Albumin

Identifiers

PMID40504990
PMCPMC12281982

What OpenQuestion holds

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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.