In one paragraphArticle in Clinical chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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What it found
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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 registryThe 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.
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3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
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5 · Who and what moneyAuthors and funding
9 authors.
Tianyu CaoThe Welch Center for Prevention, Epidemiology and Clinical Research and the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0001-7908-2886 Michael FangThe Welch Center for Prevention, Epidemiology and Clinical Research and the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-2849-1780 Amelia S WallaceThe Welch Center for Prevention, Epidemiology and Clinical Research and the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Natalie Daya MalekThe Welch Center for Prevention, Epidemiology and Clinical Research and the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Arielle ValintCollaborative Studies Coordinating Center, University of North Carolina Gillings School of Public Health, Chapel Hill, NC, United States.
Dan WangThe Welch Center for Prevention, Epidemiology and Clinical Research and the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Justin B Echouffo-TcheuguiThe Welch Center for Prevention, Epidemiology and Clinical Research and the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-8460-1617 Scott L ZegerDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Elizabeth SelvinThe Welch Center for Prevention, Epidemiology and Clinical Research and the Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-3539-2070 Funding
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
$13.7MTHE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00003 · NHLBI · UNIVERSITY OF MINNESOTA · PI LUTSEY, PAMELA · 2022 to 2025
$5.1MTHE 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
$5.0MTHE 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
$4.8MTHE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00002 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CORESH, JOSEF · 2022 to 2025
$4.7MGlucose patterns and cardiac arrhythmias in older adults with diabetesR01HL158022 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CHEN, LIN YEE, SELVIN, ELIZABETH · 2022 to 2025
$2.8MClinical relevance of glucose patterns in older adultsR01DK128837 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2021 to 2024
$2.7MGlucose instability and neurocognitive outcomes in older adultsR01AG074044 · NIA · JOHNS HOPKINS UNIVERSITY · PI Elizabeth Selvin · 2025 to 2026
$1.4MEstablishing the Pathways Between Diabetes and Cardiac Dysfunction: Epidemiology, Biomarkers, and ImagingK23HL153774 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI ECHOUFFO TCHEUGUI, JUSTIN BASILE · 2020 to 2024
$991kResearch and Mentoring in the Clinical Epidemiology of Type 2 DiabetesK24DK106414 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2015 to 2019
$654kResearch and Mentoring in the Clinical Epidemiology of Cardiovascular Disease and Type 2 DiabetesK24HL152440 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI SELVIN, ELIZABETH · 2020 to 2024
$612kDisparities in the management and prognosis of type 1 diabetesK01DK138273 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI Michael Fang · 2024 to 2026
$470kHHS R01 AG074044HHS R01 DK128837HHS R01 HL158022Merit Award from the American Heart Association K24 HL152440Merit Award from the American Heart Association R01 AG074044Merit Award from the American Heart Association R01 DK128837Merit Award from the American Heart Association R01 HL158022NHLBI NIH HHSNHLBI 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 R01 HL158022NIA NIH HHS R01 AG074044NIDDK NIH HHS K01 DK138273NIDDK NIH HHS K24 DK106414NIDDK NIH HHS R01 DK128837NIH HHSNIH/NHLBI K23 HL153774NIH/NIDDK K01 DK138273
6 · The paper itselfAbstract
backgroundHow changes in hemoglobin A1c (HbA1c) and continuous glucose monitoring (CGM) metrics track together over time is poorly understood, particularly in type 2 diabetes. We investigated the patterns of change in HbA1c and CGM metrics among older adults with type 2 diabetes.
methodsWe analyzed data from 88 Atherosclerosis Risk in Communities (ARIC) study participants (baseline age, 82 years; 28% Black race and 42% women) who had HbA1c and 14-days of CGM assessed by standardized protocols at visit 9 (2021-22) and visit 10 (2023). HbA1c, CGM mean glucose, and time in range (TIR, 70-180 mg/dL) were compared across visits. Discordance was defined as having a different direction or magnitude of change, based on an absolute HbA1c change of 0.5% and the corresponding changes in CGM metrics derived from linear mixed-effect models.
resultsOver a median of 1.6 (IQR, 1.3-1.8) years, HbA1c, CGM mean glucose, and TIR showed moderate to strong correlations (r ∼0.5 to 0.7) across visits, and HbA1c had the lowest within-person variability (CVw = 8.4%). Approximately one-third of the participants had discordant changes between HbA1c and CGM metrics, with percentage agreement of 68.2% between HbA1c and CGM mean glucose, and 67.0% between HbA1c and TIR. Similar results were found in subgroups by sex, race, diabetes medication use, and after excluding participants with reduced kidney function.
conclusionsAmong older adults with type 2 diabetes, long-term changes in HbA1c and CGM metrics are frequently discordant. This suggests the complementary nature of using HbA1c and CGM together to monitor glucose control.
Indexed as
Blood GlucoseDiabetes Mellitus, Type 2Glycated HemoglobinAgedAged, 80 and overBlood Glucose Self-MonitoringContinuous Glucose MonitoringFemaleHumansMaleBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, human
Identifiers
PMID42348255
PMCPMC13308177
What OpenQuestion holds
Textmetadata
LicenceTDM
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