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Heart failure risk prediction in the Multi-Ethnic Study of Atherosclerosis
  1. Harjit Chahal1,
  2. David A Bluemke2,
  3. Colin O Wu3,
  4. Robyn McClelland4,
  5. Kiang Liu5,
  6. Steven J Shea6,
  7. Gregory Burke7,
  8. Pelbreton Balfour8,
  9. David Herrington8,
  10. PeiBei Shi3,
  11. Wendy Post1,
  12. Jean Olson9,
  13. Karol E Watson10,
  14. Aaron R Folsom11,
  15. Joao A C Lima1
  1. 1Department of Cardiology, Johns Hopkins University, Baltimore, Maryland, USA
  2. 2Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Maryland, USA
  3. 3Offices of Biostatistics Research, National Heart Lung and Blood Institute, Bethesda, Maryland, USA
  4. 4Collaborative Health Studies Coordinating Center, University of Washington, Seattle, Washington, USA
  5. 5Department of Preventive Medicine, Northwestern University Medical School, Chicago, Illinois, USA
  6. 6Department of Epidemiology, Columbia University, New York, New York, USA
  7. 7Department of Public Health Sciences, Wake Forest University, Winston-Salem, North Carolina, USA
  8. 8Department of Cardiology, Wake Forest University, Winston-Salem, North Carolina, USA
  9. 9Division of Prevention and Population Sciences, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
  10. 10Division of Cardiology, UCLA-School of Medicine, Los Angeles, California, USA
  11. 11Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, USA
  1. Correspondence to Dr Joao A C Lima, Department of Cardiology, Johns Hopkins Hospital, 600 North Wolfe Street, Blalock 524D1, Baltimore, MD 21287, USA; jlima{at}jhmi.edu

Abstract

Objective Heart failure (HF) is a leading cause of mortality especially in older populations. Early detection of high-risk individuals is imperative for primary prevention. The purpose of this study was to develop a HF risk model from a population without clinical cardiac disease.

Methods The Multi-Ethnic Study of Atherosclerosis is a multicentre observational cohort study following 6814 subjects (mean age 62±10 years; 47% men) who were free of clinical cardiovascular disease at baseline. Median follow-up was 4.7 years. HF events developed in 176 participants. Cox proportional hazards models and regression coefficients were used to determine independent risk factors and generate a 5-year risk score for incident HF. Bootstrapping with bias correction was used for internal validation.

Results Independent predictors for HF (HR, p value) were age (1.30 (1.10 to 1.50) per 10 years), male gender (2.27 (1.53 to 3.36)), current smoking (1.97 (1.15 to 3.36)), body mass index (1.40 (1.10 to 1.80) per 5 kg/m2), systolic blood pressure (1.10 (1.00 to 1.10) per 10 mm Hg), heart rate (1.30) (1.10 to 1.40) per 10 bpm), diabetes (2.27 (1.48 to 3.47)), N-terminal pro-B-type natriuretic peptide (NT proBNP) (2.48 (2.16 to 2.84) per unit log increment) and left ventricular mass index (1.40 (1.30 to 1.40) per 10 g/m2). A parsimonious model based on age, gender, body mass index, smoking status, systolic blood pressure, heart rate, diabetes and NT proBNP natriuretic peptide predicted incident HF risk with a c-statistic of 0.87.

Conclusions A clinical algorithm based on risk factors readily available in the primary care setting can used to identify individuals with high likelihood of developing HF without pre-existing cardiac disease.

  • HEART FAILURE

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