The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Glycated Hemoglobin Measurement and Prediction of Cardiovascular Disease
Open accessAbstract
IMPORTANCE: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. OBJECTIVE: To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS: Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES: Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥ 7.5%) risk. RESULTS: During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE: In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“It should be noted that data from 73 studies on 294 998 individuals without known diabetes suggest that HbA1c is as good as or better than fasting, random, or post-load glucose levels for predicting CV risk.14”
From 2023 ESC guidelines for the management of cardiovascular disease in patients with diabetes. (2023) · cites this paper as [14]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763
Self-citationDiagnosis and Classification of Diabetes Mellitus
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc11-s062 · Cited by 14,094
2013 ACCF/AHA Guideline for the Management of Heart Failure
Yancy, C. W., Jessup, M., Bozkurt, B., Butler, J., Casey, D. E., Drazner, M. H., Fonarow, G. C., Geraci, S. A., Horwich, T., Januzzi, J. L., et al. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.05.019 · Cited by 12,536
Stone, N. J., Robinson, J. G., Lichtenstein, A. H., Bairey Merz, C. N., Blum, C. B., Eckel, R. H., Goldberg, A. C., Gordon, D., Levy, D., Lloyd-Jones, D. M., et al. (2014) · Circulation · doi:10.1161/01.cir.0000437738.63853.7a · Cited by 7,081
The Emerging Risk Factors Collaboration (2010) · The Lancet · doi:10.1016/s0140-6736(10)60484-9 · Cited by 5,125
2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk
Goff, D. C., Lloyd-Jones, D. M., Bennett, G., Coady, S., D’Agostino, R. B., Gibbons, R., Greenland, P., Lackland, D. T., Levy, D., O’Donnell, C. J., et al. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.11.005 · Cited by 4,945
Self-citationStone, N. J., Robinson, J. G., Lichtenstein, A. H., Bairey Merz, C. N., Blum, C. B., Eckel, R. H., Goldberg, A. C., Gordon, D., Levy, D., Lloyd-Jones, D. M., et al. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.11.002 · Cited by 3,845
Goff, D. C., Lloyd-Jones, D. M., Bennett, G., Coady, S., D’Agostino, R. B., Gibbons, R., Greenland, P., Lackland, D. T., Levy, D., O’Donnell, C. J., et al. (2014) · Circulation · doi:10.1161/01.cir.0000437741.48606.98 · Cited by 3,697
Self-citationDiagnosis and classification of diabetes mellitus
American Diabetes Association (2013) · Diabetes Care · doi:10.2337/dc13-s067 · Cited by 2,245
Authors Task Force Members, Rydén, L., Grant, P. J., Anker, S. D., Berne, C., Cosentino, F., Danchin, N., Deaton, C., Escaned, J., Hammes, H., et al. (2013) · European Heart Journal · doi:10.1093/eurheartj/eht108 · Cited by 1,994
Self-citation
Cited by
Sorted by citations
Items 201–232 of 232
Mahdavi, S. S. (2018) · TSpace (University of Toronto)
Volkova, T. V., & Kudinov, V. I. (2020) · Doctor Ru · doi:10.31550/1727-2378-2020-19-2-63-67
Ruquiyyah, K., & Hoda, Q. (2020) · World Journal of Advanced Research and Reviews · doi:10.30574/wjarr.2020.7.1.0242
“The relative risk of CVD increases by about 18 % for every percentage point increase in HbA1c in patients with overt Type 2 DM [6].”
BackgroundHailati, J., Chun, Y.-Y., Midilibieke, H., He, P., Liu, Z., & Muhuyati (2020) · All Life · doi:10.1080/26895293.2020.1848928
Cardiovascular risk and disease management in diabetes: differences between women and men.
de Jong, M. (2021) · Utrecht University Repository (Utrecht University) · doi:10.33540/590
Faster Aspart: a fast-acting insulin analog for an optimal glycemic control
Irace, C. (2021) · The Journal of AMD · doi:10.36171/jamd21.24.3.5
Paneni, F., & Cosentino, F. (2015) · Springer eBooks · doi:10.1007/978-3-319-17762-5_6
A Hawks for Feature Score Significance Analysis Using Learning AlgorithmsPreprint
SARAN, A., & Rekha, R. U. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4127702
A Hawks for Feature Score Significance Analysis Using Learning AlgorithmsPreprint
SARAN, A., & Rekha, R. U. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4127705
Richard Hoffman PhD RNutr, F. R. S. A. (2022) · Wiley eBooks · doi:10.1002/9781119826743.ch6
(2019) · REST Journal on Emerging trends in Modelling and Manufacturing · doi:10.46632/jemm/5/4/9
Tabák, Á. G., Sattar, N. A., & Mika Kivimaki, B. (2023) · Circulation · doi:10.1161/circulationaha.123.063545
Self-citationOtify, E. A. A. A., Mekki, M., Borucki, J. P., Dhatariya, K., & Stather, P. (2023) · medRxiv · doi:10.1101/2023.03.25.23287746
“These observations are contrary to the strong positive association of DM with other vascular diseases and their complications [5, 6, 7].”
ResultLi, S., Wang, Y., Wang, W., Zhang, Q., Wang, A., & Zhao, X. (2022) · Figshare · doi:10.6084/m9.figshare.20164720
Yang, L., & Zhang, L. (2025) · Preprints.org · doi:10.20944/preprints202508.0172.v1
Sinning, C., Makarova, N., Völzke, H., Schnabel, R. B., Ojeda, F., Dörr, M., Felix, S. B., Koenig, W., Peters, A., Rathmann, W., et al. (2021) · Figshare · doi:10.6084/m9.figshare.17021013
Self-citationLi, S., Wang, Y., Wang, W., Zhang, Q., Wang, A., & Zhao, X. (2022) · Figshare · doi:10.6084/m9.figshare.20164723
Li, L., Lip, G. Y. H., Li, S., Adachi, J. D., Thabane, L., & Li, G. (2022) · Figshare · doi:10.6084/m9.figshare.20329303
Cai, C., Wang, L., Chen, Q., Lin, M., Pan, X., Chen, W., Shi, D., & Chen, Y. (2024) · Figshare · doi:10.6084/m9.figshare.26660518
Cai, C., Wang, L., Chen, Q., Lin, M., Pan, X., Chen, W., Shi, D., & Chen, Y. (2024) · Figshare · doi:10.6084/m9.figshare.24941000
Giannella, A., Ceolotto, G., Radu, C. M., Cattelan, A., Iori, E., Benetti, A., Fabris, F., Simioni, P., Avogaro, A., & Vigili de Kreutzenberg, S. (2021) · Figshare · doi:10.6084/m9.figshare.14369948
Zheng, X., Zhang, W., Wan, X., Lv, X., Lin, P., Si, S., Xue, F., Wang, A., & Cao, Y. (2024) · Figshare · doi:10.6084/m9.figshare.26708834
Sharma, A., Nermoen, I., Qvigstad, E., Tran, A. T., Sommer, C., Sattar, N. A., Gill, J. M. R., Gulseth, H. L., Sollid, S. T., & Birkeland, K. I. (2022) · Figshare · doi:10.6084/m9.figshare.21192184
Self-citationCai, C., Wang, L., Chen, Q., Lin, M., Pan, X., Chen, W., Shi, D., & Chen, Y. (2024) · Figshare · doi:10.6084/m9.figshare.24940412
Sharma, A., Nermoen, I., Qvigstad, E., Tran, A. T., Sommer, C., Sattar, N. A., Gill, J. M. R., Gulseth, H. L., Sollid, S. T., & Birkeland, K. I. (2022) · Figshare · doi:10.6084/m9.figshare.21192181
Self-citationHuang, B., Zheng, M., Li, J., Fang, C., Wu, Y., Xiao, Y., Yu, P., Gu, W., Zhou, S., Zhang, Y., et al. (2026) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-025-02067-y
“Associations with vascular outcomes and mortality were identified in both DM patients and individuals without a prior diagnosis of DM [5, 6].”
Otify, E. A. A. A., Sanders, I., Borucki, J., Dhatariya, K., & Stather, P. (2026) · Annals of Vascular Surgery · doi:10.1016/j.avsg.2026.04.047
Iqbal, I., Akram, S., Lodhi, H. K., Hussain, A., Shahzad, M., & Amir, H. (2026) · Biological and Clinical Sciences Research Journal · doi:10.54112/bcsrj.v7i6.2346
Heterogeneity of effects of a mobile health disease management programme on glycaemic control
Shiraishi, R., Miki, T., Ishida, S., Kanai, M., Hagiwara, Y., & Ikeda, T. (2026) · BMJ Nutrition Prevention & Health · doi:10.1136/bmjnph-2025-001465
Diagnosis and ongoing evaluation
Bruggeman, B. S., Jacobsen, L. M., Foster, T. P., & Winter, W. E. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-21725-8.00015-9
Cai, X., Zhang, J., Huang, H., Tang, W., Lv, Q., Song, Y., Zhang, X., Cai, Q.-C., Zou, J., Shi, Y., et al. (2026) · MedComm · doi:10.1002/mco2.70967
“Chronic hyperglycemic state, represented by elevated HbA 1c , promotes the development of arteriosclerosis [ 23–25 ].”
Seidu, S., Kunutsor, S. K., & Khunti, K. K. (2026) · Mayo Clinic Proceedings Innovations Quality & Outcomes · doi:10.1016/j.mayocpiqo.2026.100756
“14-17 The few studies that have examined glycaemia in relation to cMLTC have predominantly been conducted in Asian populations and have often relied on composite indices, such as the HbA1c/ high-density lipoprotein cholesterol (HDL-C) ratio, rather than evaluating HbA1c or FPG as independent…”
Metadata
- Authors
- Di Angelantonio, E., Gao, P., Khan, H., Butterworth, A. S., Wormser, D., Kaptoge, S., Kondapally Seshasai, S. R., Thompson, A., Sarwar, N., Willeit, P., Ridker, P. M., Barr, E. L. M., Khaw, K.-T., Psaty, B. M., Brenner, H., Balkau, B., Dekker, J. M., Lawlor, D. A., Daimon, M., Willeit, J., Njølstad, I., Nissinen, A., Brunner, E. J., Kuller, L. H., Price, J. F., Sundström, J., Knuiman, M. W., Feskens, E. J. M., Verschuren, W. M. M., Wald, N., Bakker, S. J. L., Whincup, P. H., Ford, I., Goldbourt, U., Gómez-de-la-Cámara, A., Gallacher, J., Simons, L. A., Rosengren, A., Sutherland, S. E., Björkelund, C., Blazer, D. G., Wassertheil-Smoller, S., Onat, A., Marín Ibañez, A., Casiglia, E., Jukema, J. W., Simpson, L. M., Giampaoli, S., Nordestgaard, B. G., Selmer, R., Wennberg, P., Kauhanen, J., Salonen, J. T., Dankner, R., Barrett-Connor, E., Kavousi, M., Gudnason, V., Evans, D., Wallace, R. B., Cushman, M., D’Agostino, R. B., Umans, J. G., Kiyohara, Y., Nakagawa, H., Sato, S., Gillum, R. F., Folsom, A. R., van der Schouw, Y. T., Moons, K. G., Griffin, S. J., Sattar, N., Wareham, N. J., Selvin, E., Thompson, S. G., & Danesh, J.
- Affiliations
- University of Cambridge, Cambridge, United Kingdom
- University of Cambridge (GB)
- St George's University of London, London, United Kingdom
- Brigham and Women's Hospital (US)
- Baker Heart and Diabetes Institute (AU)
- University of Washington (US)
- German Cancer Research Center (DE)
- Inserm (FR)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
- University of Bristol (GB)
- Yamagata University (JP)
- Innsbruck Medical University (AT)
- UiT The Arctic University of Norway (NO)
- Finnish Institute for Health and Welfare (FI)
- University College London (GB)
- University of Pittsburgh (US)
- University of Edinburgh (GB)
- Uppsala University (SE)
- The University of Western Australia (AU)
- Wageningen University & Research (NL)
- National Institute for Public Health and the Environment (NL)
- Wolfson Institute of Preventive Medicine, London, United Kingdom
- University Medical Center Groningen (NL)
- St George's, University of London (GB)
- University of Glasgow (GB)
- Sheba Medical Center (IL)
- Hospital 12 de Octubre, Madrid, Spain
- Cardiff University (GB)
- UNSW Sydney (AU)
- University of Gothenburg (SE)
- Medical University of South Carolina (US)
- Duke Medical Center (US)
- Albert Einstein College of Medicine, New York, New York
- Istanbul University (TR)
- San Jose Norte Health Centre, Zaragoza, Spain
- University of Padua (IT)
- Leiden University Medical Center (NL)
- University of Texas School of Public Health, Houston
- Istituto Superiore di Sanità (IT)
- University of Copenhagen (DK)
- Norwegian Institute of Public Health (NO)
- Umeå University (SE)
- University of Eastern Finland (FI)
- University of Helsinki (FI)
- Feinstein Institute for Medical Research (US)
- University of California San Diego (US)
- Erasmus MC (NL)
- University of Iceland (IS)
- Rush University Medical Center (US)
- University of Iowa (US)
- University of Vermont (US)
- Boston University (US)
- Georgetown University (US)
- Kyushu University (JP)
- Kanazawa Medical University (JP)
- Chiba Prefectural Institute of Public Health (JP)
- Howard University (US)
- University of Minnesota (US)
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
- University Medical Center Utrecht (NL)
- Johns Hopkins University (US)
- Corresponding author
- Danesh, John
- ORCID
- Gao, Pei
- Khan, Hassan
- Butterworth, Adam S.
- Kaptoge, Stephen
- Thompson, Alex
- Sarwar, Nadeem
- Willeit, Peter
- Ridker, Paul M
- Barr, Elizabeth L. M.
- Khaw, Kay-Tee
- Psaty, Bruce M.
- Brenner, Hermann
- Balkau, Beverley
- Lawlor, Debbie A.
- Daimon, Makoto
- Willeit, Johann
- Njølstad, Inger
- Brunner, Eric J.
- Kuller, Lewis H.
- Price, Jackie F.
- Sundström, Johan
- Knuiman, Matthew W.
- Feskens, Edith J. M.
- Verschuren, W. M. M.
- Wald, Nicholas
- Bakker, Stephan J. L.
- Whincup, Peter H.
- Ford, Ian
- Gallacher, John
- Simons, Leon A.
- Rosengren, Annika
- Sutherland, Susan E.
- Blazer, Dan G.
- Onat, Altan
- Casiglia, Edoardo
- Jukema, J. Wouter
- Giampaoli, Simona
- Nordestgaard, Børge G.
- Selmer, Randi
- Wennberg, Patrik
- Dankner, Rachel
- Barrett-Connor, Elizabeth
- Kavousi, Maryam
- Gudnason, Vilmundur
- Evans, Denis
- Wallace, Robert B.
- Cushman, Mary
- D’Agostino, Ralph B.
- Umans, Jason G.
- Sato, Shinichi
- Gillum, Richard F.
- Folsom, Aaron R.
- Moons, Karel G.
- Griffin, Simon J.
- Sattar, Naveed
- Wareham, Nicholas J.
- Selvin, Elizabeth
- Thompson, Simon G.
- Danesh, John
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2014-03-26
- Volume
- 311
- Issue
- 12
- Pages
- 1225
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC4386007
- OpenAlex
- W2114008139
- Cited by
- 231
- References
- 32
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 17 · 2023: 12 · 2022: 20 · 2021: 14 · 2020: 22 · 2019: 13 · 2018: 20 · 2017: 22 · 2016: 23 · 2015: 34 · 2014: 12
- FWCI
- 24.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- National Institute for Health and Care Research (NF-SI-0512-10165, NF-SI-0512-10114)
- British Heart Foundation (RG/08/013/25942, RG/13/16/30528, PG/13/66/30442, RG/08/014/24067)
- National Institutes of Health (UL1TR000062)
- Medical Research Council (MC_UU_12015/4, MR/K013351/1, MR/L003120/1)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Keywords
- HbA1c, cardiovascular risk prediction, coronary artery disease, stroke, risk discrimination, net reclassification improvement, cardiovascular risk factors, J-shaped association, fasting blood glucose, post-load glucose, C-reactive protein, HDL cholesterol, estimated glomerular filtration rate, non-diabetic adults
- MeSH terms
- Aged, C-Reactive Protein, Coronary Disease, Diabetes Mellitus, Female, Glycated Hemoglobin, Humans, Cholesterol, HDL, Male, Middle Aged, Predictive Value of Tests, Prospective Studies, Risk Assessment, Stroke
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review