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 undiagnosed 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-index 0.7392) 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.
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 undiagnosed 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-index 0.7392) 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.
Authors: Michael C Honigberg; Seyedeh M Zekavat; James P Pirruccello; Pradeep Natarajan; Muthiah Vaduganathan Journal: J Am Coll Cardiol Date: 2021-05-17 Impact factor: 27.203
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Authors: Christoph Sinning; Nataliya Makarova; Stefan Söderberg; Marco M Ferrario; Barbara Thorand; Henry Völzke; Renate B Schnabel; Francisco Ojeda; Marcus Dörr; Stephan B Felix; Wolfgang Koenig; Annette Peters; Wolfgang Rathmann; Ben Schöttker; Hermann Brenner; Giovanni Veronesi; Giancarlo Cesana; Paolo Brambilla; Tarja Palosaari; Kari Kuulasmaa; Inger Njølstad; Ellisiv Bøgeberg Mathiesen; Tom Wilsgaard; Stefan Blankenberg Journal: Cardiovasc Diabetol Date: 2021-11-15 Impact factor: 9.951
Authors: Jessica R Zolton; Lindsey A Sjaarda; Sunni L Mumford; Tiffany L Holland; Keewan Kim; Kerry S Flannagan; Samrawit F Yisahak; Stefanie N Hinkle; Matthew T Connell; Mark V White; Neil J Perkins; Robert M Silver; Micah J Hill; Alan H DeCherney; Enrique F Schisterman Journal: F S Rep Date: 2022-01-20
Authors: Jana J Anderson; Paul Welsh; Frederick K Ho; Lyn D Ferguson; Claire E Welsh; Pierpaolo Pellicori; John G F Cleland; John Forbes; Stamatina Iliodromiti; James Boyle; Robert Lindsay; Carlos Celis-Morales; Stuart Robert Gray; Srinivasa Vittal Katikireddi; Jason Martin Regnald Gill; Jill P Pell; Naveed Sattar Journal: BMJ Open Diabetes Res Care Date: 2021-08