Michael C Honigberg1, Seyedeh M Zekavat2, James P Pirruccello3, Pradeep Natarajan4, Muthiah Vaduganathan5. 1. Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA. Electronic address: mhonigberg@mgh.harvard.edu. 2. Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA; Computational Biology and Bioinformatics Program, Yale University, New Haven, Connecticut, USA. Electronic address: https://twitter.com/zekavatm. 3. Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA. Electronic address: https://twitter.com/jpirruccello. 4. Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA. Electronic address: https://twitter.com/pnatarajanmd. 5. Harvard Medical School, Boston, Massachusetts, USA; Division of Cardiovascular Medicine, Brigham and Women's Hospital Heart and Vascular Center, Boston, Massachusetts, USA. Electronic address: https://twitter.com/mvaduganathan.
Abstract
BACKGROUND: Treatment guidelines for prediabetes primarily focus on glycemic control and lifestyle management. Few evidence-based cardiovascular and kidney risk-reduction strategies are available in this population. OBJECTIVES: This study sought to characterize cardiovascular and kidney outcomes across the glycemic spectrum. METHODS: Among participants in the UK Biobank without prevalent type 1 diabetes, cardiovascular disease, or kidney disease, Cox models tested the association of glycemic exposures (type 2 diabetes [T2D], prediabetes, normoglycemia) with outcomes (atherosclerotic cardiovascular disease [ASCVD], chronic kidney disease [CKD], and heart failure), adjusting for demographic, lifestyle, and cardiometabolic risk factors. RESULTS: Among 336,709 individuals (mean age: 56.3 years, 55.4% female), 46,911 (13.9%) had prediabetes and 12,717 (3.8%) had T2D. Over median follow-up of 11.1 years, 6,476 (13.8%) individuals with prediabetes developed ≥1 incident outcome, of whom only 802 (12.4%) developed T2D prior to an incident diagnosis. Prediabetes and T2D were independently associated with ASCVD (prediabetes: adjusted HR [aHR]: 1.11; 95% CI: 1.08-1.15; P < 0.001; T2D: aHR: 1.44; 95% CI: 1.37-1.51; P < 0.001), CKD (prediabetes: aHR: 1.08; 95% CI: 1.02-1.14; P < 0.001; T2D: aHR: 1.57; 95% CI: 1.46-1.69; P < 0.001), and heart failure (prediabetes: aHR: 1.07; 95% CI: 1.01-1.14; P = 0.03; T2D: aHR: 1.25; 95% CI: 1.14-1.37; P < 0.001). Compared with hemoglobin A1c (HbA1c) <5.0%, covariate-adjusted risks increased significantly for ASCVD above HbA1c of 5.4%, CKD above HbA1c of 6.2%, and heart failure above HbA1c of 7.0%. CONCLUSIONS: Prediabetes and T2D were associated with ASCVD, CKD, and heart failure, but a substantial gradient of risk was observed across HbA1c levels below the threshold for diabetes. These findings highlight the need to design risk-reduction strategies across the glycemic spectrum.
BACKGROUND: Treatment guidelines for prediabetes primarily focus on glycemic control and lifestyle management. Few evidence-based cardiovascular and kidney risk-reduction strategies are available in this population. OBJECTIVES: This study sought to characterize cardiovascular and kidney outcomes across the glycemic spectrum. METHODS: Among participants in the UK Biobank without prevalent type 1 diabetes, cardiovascular disease, or kidney disease, Cox models tested the association of glycemic exposures (type 2 diabetes [T2D], prediabetes, normoglycemia) with outcomes (atherosclerotic cardiovascular disease [ASCVD], chronic kidney disease [CKD], and heart failure), adjusting for demographic, lifestyle, and cardiometabolic risk factors. RESULTS: Among 336,709 individuals (mean age: 56.3 years, 55.4% female), 46,911 (13.9%) had prediabetes and 12,717 (3.8%) had T2D. Over median follow-up of 11.1 years, 6,476 (13.8%) individuals with prediabetes developed ≥1 incident outcome, of whom only 802 (12.4%) developed T2D prior to an incident diagnosis. Prediabetes and T2D were independently associated with ASCVD (prediabetes: adjusted HR [aHR]: 1.11; 95% CI: 1.08-1.15; P < 0.001; T2D: aHR: 1.44; 95% CI: 1.37-1.51; P < 0.001), CKD (prediabetes: aHR: 1.08; 95% CI: 1.02-1.14; P < 0.001; T2D: aHR: 1.57; 95% CI: 1.46-1.69; P < 0.001), and heart failure (prediabetes: aHR: 1.07; 95% CI: 1.01-1.14; P = 0.03; T2D: aHR: 1.25; 95% CI: 1.14-1.37; P < 0.001). Compared with hemoglobin A1c (HbA1c) <5.0%, covariate-adjusted risks increased significantly for ASCVD above HbA1c of 5.4%, CKD above HbA1c of 6.2%, and heart failure above HbA1c of 7.0%. CONCLUSIONS: Prediabetes and T2D were associated with ASCVD, CKD, and heart failure, but a substantial gradient of risk was observed across HbA1c levels below the threshold for diabetes. These findings highlight the need to design risk-reduction strategies across the glycemic spectrum.
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