Ambarish Pandey1, Muthiah Vaduganathan2, Kershaw V Patel3, Colby Ayers1, Christie M Ballantyne4, Mikhail N Kosiborod5, Mercedes Carnethon6, Christopher DeFilippi7, Darren K McGuire1, Sadiya S Khan6, Melissa C Caughey8, James A de Lemos1, Brendan M Everett9. 1. Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center and Parkland Health and Hospital System, Dallas, Texas, USA. 2. Brigham and Women's Hospital Heart and Vascular Center, Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA. Electronic address: mvaduganathan@bwh.harvard.edu. 3. Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center and Parkland Health and Hospital System, Dallas, Texas, USA; Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston, Texas, USA. 4. Department of Medicine, Baylor College of Medicine, Houston, Texas, USA. 5. Saint Luke's Mid America Heart Institute and University of Missouri-Kansas City, Kansas City, Missouri, USA. 6. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. 7. Inova Heart and Vascular Institute, Falls Church, Virginia, USA. 8. Joint Department of Biomedical Engineering, University of North Carolina and North Carolina State University, Chapel Hill, North Carolina, USA. 9. Divisions of Cardiovascular and Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Abstract
OBJECTIVES: This study evaluated the application of a biomarker-based risk score to identify individuals with dysglycemia who are at high risk for incident heart failure (HF) and to inform allocation of effective preventive interventions. BACKGROUND: Risk stratification tools to identify patients with diabetes and pre-diabetes at highest risk for HF are needed to inform cost-effective allocation of preventive therapies. Whether a biomarker score can meaningfully stratify HF risk is unknown. METHODS: Participants free of cardiovascular disease from 3 cohort studies (ARIC [Atherosclerosis Risk In Communities], DHS [Dallas Heart Study], and MESA [Multi-Ethnic Study of Atherosclerosis]) were included. An integer-based biomarker score included high-sensitivity cardiac troponin T ≥6 ng/l, N-terminal pro-B-type natriuretic peptide ≥125 pg/ml, high-sensitivity C-reactive protein ≥3 mg/l, and left ventricular hypertrophy by electrocardiography, with 1 point for each abnormal parameter. The 5-year risk of HF was estimated among participants with diabetes and pre-diabetes across biomarker score groups (0 to 4). RESULTS: The primary analysis included 6,799 participants with dysglycemia (diabetes: 33.2%; pre-diabetes: 66.8%). The biomarker score demonstrated good discrimination and calibration for predicting 5- and 10-year HF risk among pre-diabetes and diabetes cohorts. The 5-year risk of HF among subjects with a biomarker score of ≤1 was low and comparable to participants with euglycemia (0.78%). The 5-year risk for HF increased in a graded fashion with an increasing biomarker score, with the highest risk noted among those with scores of ≥3 (diabetes: 12.0%; pre-diabetes: 7.8%). The estimated number of HF events that could be prevented using a sodium-glucose cotransporter-2 inhibitor per 1,000 treated subjects over 5 years was 11 for all subjects with diabetes and ranged from 4 in the biomarker score zero group to 44 in the biomarker score ≥3 group. CONCLUSIONS: Among adults with diabetes and pre-diabetes, a biomarker score can stratify HF risk and inform allocation of HF prevention therapies.
OBJECTIVES: This study evaluated the application of a biomarker-based risk score to identify individuals with dysglycemia who are at high risk for incident heart failure (HF) and to inform allocation of effective preventive interventions. BACKGROUND: Risk stratification tools to identify patients with diabetes and pre-diabetes at highest risk for HF are needed to inform cost-effective allocation of preventive therapies. Whether a biomarker score can meaningfully stratify HF risk is unknown. METHODS:Participants free of cardiovascular disease from 3 cohort studies (ARIC [Atherosclerosis Risk In Communities], DHS [Dallas Heart Study], and MESA [Multi-Ethnic Study of Atherosclerosis]) were included. An integer-based biomarker score included high-sensitivity cardiac troponin T ≥6 ng/l, N-terminal pro-B-type natriuretic peptide ≥125 pg/ml, high-sensitivity C-reactive protein ≥3 mg/l, and left ventricular hypertrophy by electrocardiography, with 1 point for each abnormal parameter. The 5-year risk of HF was estimated among participants with diabetes and pre-diabetes across biomarker score groups (0 to 4). RESULTS: The primary analysis included 6,799 participants with dysglycemia (diabetes: 33.2%; pre-diabetes: 66.8%). The biomarker score demonstrated good discrimination and calibration for predicting 5- and 10-year HF risk among pre-diabetes and diabetes cohorts. The 5-year risk of HF among subjects with a biomarker score of ≤1 was low and comparable to participants with euglycemia (0.78%). The 5-year risk for HF increased in a graded fashion with an increasing biomarker score, with the highest risk noted among those with scores of ≥3 (diabetes: 12.0%; pre-diabetes: 7.8%). The estimated number of HF events that could be prevented using a sodium-glucose cotransporter-2 inhibitor per 1,000 treated subjects over 5 years was 11 for all subjects with diabetes and ranged from 4 in the biomarker score zero group to 44 in the biomarker score ≥3 group. CONCLUSIONS: Among adults with diabetes and pre-diabetes, a biomarker score can stratify HF risk and inform allocation of HF prevention therapies.
Authors: Kershaw V Patel; Matthew W Segar; Carl J Lavie; Nitin Kondamudi; Ian J Neeland; Jaime P Almandoz; Corby K Martin; Salvatore Carbone; Javed Butler; Tiffany M Powell-Wiley; Ambarish Pandey Journal: Circulation Date: 2021-12-03 Impact factor: 29.690
Authors: David D Berg; Ahmed A Kolkailah; Ashish Sarraju; Anne Marie Kerchberger; Mahmoud Eljalby; Darren K McGuire Journal: Curr Diab Rep Date: 2021-11-06 Impact factor: 4.810
Authors: Elliot J Stein; William F Fearon; Sammy Elmariah; Juyong B Kim; Samir Kapadia; Dharam J Kumbhani; Linda Gillam; Brian Whisenant; Nishath Quader; Alan Zajarias; Frederick G Welt; Anthony A Bavry; Megan Coylewright; Robert N Piana; Ravinder R Mallugari; Daniel E Clark; Jay N Patel; Holly Gonzales; Deepak K Gupta; Anna Vatterott; Natalie Jackson; Shi Huang; Brian R Lindman Journal: J Am Heart Assoc Date: 2022-03-18 Impact factor: 6.106
Authors: Matthew W Segar; Kershaw V Patel; Anne S Hellkamp; Muthiah Vaduganathan; Yuliya Lokhnygina; Jennifer B Green; Siu-Hin Wan; Ahmed A Kolkailah; Rury R Holman; Eric D Peterson; Vaishnavi Kannan; Duwayne L Willett; Darren K McGuire; Ambarish Pandey Journal: J Am Heart Assoc Date: 2022-06-03 Impact factor: 6.106