Glycated hemoglobin, prediabetes, and the links to cardiovascular disease: Data from UK Biobank

Claire Welsh; Paul Welsh; Carlos A. Celis-Morales; Patrick B. Mark; Daniel Mackay; Nazim Ghouri; Fredrick K. Ho; Lyn D. Ferguson; Rosemary Brown; James Lewsey; John G. Cleland; Stuart R. Gray; Donald M. Lyall; Jana J. Anderson; Pardeep S. Jhund; Jill P. Pell; Darren K. McGuire; Jason M.R. Gill; Naveed Sattar

doi:10.2337/dc19-1683

Glycated hemoglobin, prediabetes, and the links to cardiovascular disease: Data from UK Biobank

Claire Welsh, Paul Welsh, Carlos A. Celis-Morales, Patrick B. Mark, Daniel Mackay, Nazim Ghouri, Fredrick K. Ho, Lyn D. Ferguson, Rosemary Brown, James Lewsey, John G. Cleland, Stuart R. Gray, Donald M. Lyall, Jana J. Anderson, Pardeep S. Jhund, Jill P. Pell, Darren K. McGuire, Jason M.R. Gill, Naveed Sattar

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Abstract

OBJECTIVE: HbA_1c levels are increasingly measured in screening for diabetes; we investigated whether HbA_1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association(ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems. RESEARCH DESIGN AND METHODS: UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes. RESULTS: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0-47.9 mmol/mol [6.0-6.4%]) and 0.7% (n = 2,573) had un-diagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69-1.97) and 2.26 (95% CI 1.96-2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03-1.20) and 1.20 (1.04-1.38), respectively. Adding HbA_1c to the QRISK3 CVD risk prediction model(C-index0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001-0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models. CONCLUSIONS: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA_1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.

Original language	English (US)
Pages (from-to)	440-445
Number of pages	6
Journal	Diabetes care
Volume	43
Issue number	2
DOIs	https://doi.org/10.2337/dc19-1683
State	Published - Feb 1 2020

ASJC Scopus subject areas

Internal Medicine
Endocrinology, Diabetes and Metabolism
Advanced and Specialized Nursing

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10.2337/dc19-1683

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Welsh, C., Welsh, P., Celis-Morales, C. A., Mark, P. B., Mackay, D., Ghouri, N., Ho, F. K., Ferguson, L. D., Brown, R., Lewsey, J., Cleland, J. G., Gray, S. R., Lyall, D. M., Anderson, J. J., Jhund, P. S., Pell, J. P., McGuire, D. K., Gill, J. M. R., & Sattar, N. (2020). Glycated hemoglobin, prediabetes, and the links to cardiovascular disease: Data from UK Biobank. Diabetes care, 43(2), 440-445. https://doi.org/10.2337/dc19-1683

Welsh, C, Welsh, P, Celis-Morales, CA, Mark, PB, Mackay, D, Ghouri, N, Ho, FK, Ferguson, LD, Brown, R, Lewsey, J, Cleland, JG, Gray, SR, Lyall, DM, Anderson, JJ, Jhund, PS, Pell, JP, McGuire, DK, Gill, JMR & Sattar, N 2020, 'Glycated hemoglobin, prediabetes, and the links to cardiovascular disease: Data from UK Biobank', Diabetes care, vol. 43, no. 2, pp. 440-445. https://doi.org/10.2337/dc19-1683

@article{9c4b96e4fb8141a19cb16acc2fc4be9e,

title = "Glycated hemoglobin, prediabetes, and the links to cardiovascular disease: Data from UK Biobank",

abstract = "OBJECTIVE: HbA1c levels are increasingly measured in screening for diabetes; we investigated whether HbA1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association(ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems. RESEARCH DESIGN AND METHODS: UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes. RESULTS: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0-47.9 mmol/mol [6.0-6.4%]) and 0.7% (n = 2,573) had un-diagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69-1.97) and 2.26 (95% CI 1.96-2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03-1.20) and 1.20 (1.04-1.38), respectively. Adding HbA1c to the QRISK3 CVD risk prediction model(C-index0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001-0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models. CONCLUSIONS: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.",

author = "Claire Welsh and Paul Welsh and Celis-Morales, {Carlos A.} and Mark, {Patrick B.} and Daniel Mackay and Nazim Ghouri and Ho, {Fredrick K.} and Ferguson, {Lyn D.} and Rosemary Brown and James Lewsey and Cleland, {John G.} and Gray, {Stuart R.} and Lyall, {Donald M.} and Anderson, {Jana J.} and Jhund, {Pardeep S.} and Pell, {Jill P.} and McGuire, {Darren K.} and Gill, {Jason M.R.} and Naveed Sattar",

note = "Funding Information: Acknowledgments. This research was con ducted using the UK Biobank resource. The authors thank the participants of the UK Biobank. The work was performed under UK Biobank project number 9310. The authors thank Liz Coyle (University of Glasgow) for her excellent assistance in the preparation of this article. Funding. The work in this study was supported by a grant from Chest, Heart and Stroke Association Scotland (Res16/A165) and by the British Heart Foundation Research Excellence Award (RE/18/6/34217). Publisher Copyright: {\textcopyright} 2019 by the American Diabetes Association.",

year = "2020",

month = feb,

day = "1",

doi = "10.2337/dc19-1683",

language = "English (US)",

volume = "43",

pages = "440--445",

journal = "Diabetes care",

issn = "0149-5992",

publisher = "American Diabetes Association Inc.",

number = "2",

}

TY - JOUR

T1 - Glycated hemoglobin, prediabetes, and the links to cardiovascular disease

T2 - Data from UK Biobank

AU - Welsh, Claire

AU - Welsh, Paul

AU - Celis-Morales, Carlos A.

AU - Mark, Patrick B.

AU - Mackay, Daniel

AU - Ghouri, Nazim

AU - Ho, Fredrick K.

AU - Ferguson, Lyn D.

AU - Brown, Rosemary

AU - Lewsey, James

AU - Cleland, John G.

AU - Gray, Stuart R.

AU - Lyall, Donald M.

AU - Anderson, Jana J.

AU - Jhund, Pardeep S.

AU - Pell, Jill P.

AU - McGuire, Darren K.

AU - Gill, Jason M.R.

AU - Sattar, Naveed

N1 - Funding Information: Acknowledgments. This research was con ducted using the UK Biobank resource. The authors thank the participants of the UK Biobank. The work was performed under UK Biobank project number 9310. The authors thank Liz Coyle (University of Glasgow) for her excellent assistance in the preparation of this article. Funding. The work in this study was supported by a grant from Chest, Heart and Stroke Association Scotland (Res16/A165) and by the British Heart Foundation Research Excellence Award (RE/18/6/34217). Publisher Copyright: © 2019 by the American Diabetes Association.

PY - 2020/2/1

Y1 - 2020/2/1

N2 - OBJECTIVE: HbA1c levels are increasingly measured in screening for diabetes; we investigated whether HbA1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association(ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems. RESEARCH DESIGN AND METHODS: UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes. RESULTS: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0-47.9 mmol/mol [6.0-6.4%]) and 0.7% (n = 2,573) had un-diagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69-1.97) and 2.26 (95% CI 1.96-2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03-1.20) and 1.20 (1.04-1.38), respectively. Adding HbA1c to the QRISK3 CVD risk prediction model(C-index0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001-0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models. CONCLUSIONS: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.

AB - OBJECTIVE: HbA1c levels are increasingly measured in screening for diabetes; we investigated whether HbA1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association(ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems. RESEARCH DESIGN AND METHODS: UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes. RESULTS: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0-47.9 mmol/mol [6.0-6.4%]) and 0.7% (n = 2,573) had un-diagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69-1.97) and 2.26 (95% CI 1.96-2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03-1.20) and 1.20 (1.04-1.38), respectively. Adding HbA1c to the QRISK3 CVD risk prediction model(C-index0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001-0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models. CONCLUSIONS: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed.

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Glycated hemoglobin, prediabetes, and the links to cardiovascular disease: Data from UK Biobank

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