title: Health 2000 score - development and validation of a novel cardiovascular risk score.
abstract: Previous risk scores for predicting myocardial infarctions and strokes have mainly been based on conventional risk factors. We aimed to develop a novel improved risk score that would incorporate other widely available clinical variables for predicting the broadest range of endpoints, including revascularizations.
  
  
  
  A nationwide sample of 5843 Finns underwent a clinical examination in 2000-2001. The participants were followed for a median of 11.2 years for incident cardiovascular events. Model discrimination and calibration were assessed and internal validation was performed.
  
  
  
  Sex, age, systolic blood pressure, total cholesterol, HDL cholesterol, smoking status, parental death from cardiovascular disease, left ventricular hypertrophy, hemoglobin A1c, and educational level remained significant predictors of cardiovascular events (p ≤ 0.005 for all). The share of participants with ≥10% estimated cardiovascular risk was 28.9%, 18.5%, 36.9% and 23.8% with the Health 2000, Finrisk, Framingham and Reynolds risk scores. The Health 2000 score (c-statistic: 0.850) showed superior discrimination to the Framingham (c-statistic improvement: 0.021) and Reynolds (c-statistic improvement: 0.007) scores (p < 0.001 for both comparisons). Model including left ventricular hypertrophy, hemoglobin A1c, and educational level improved the model prediction (c-statistic improvement: 0.006, p = 0.003).
  
  
  
  The Health 2000score improves cardiovascular risk prediction in the current study population. KEY MESSAGES Previous risk scores for predicting myocardial infarctions and strokes have mainly been based on conventional risk factors. We aimed to develop a novel improved risk score that would incorporate other widely available clinical variables (including left ventricular hypertrophy, hemoglobin A1c, and education level) for predicting the broadest range of endpoints, including revascularizations. The Health 2000 score improved cardiovascular risk prediction in the current study population compared with traditional cardiovascular risk prediction scores.
authors.affiliation: a Department of Health , National Institute for Health and Welfare , Turku , Finland.|b Department of Medicine , Turku University Hospital , Turku , Finland.
authors.forename: Jouni K
authors.initials: JK
authors.lastname: Johansson
authors.affiliation: a Department of Health , National Institute for Health and Welfare , Turku , Finland.
authors.forename: Pauli J
authors.initials: PJ
authors.lastname: Puukka
authors.affiliation: a Department of Health , National Institute for Health and Welfare , Turku , Finland.|c The Framingham Heart Study , Boston University , Framingham , MA , USA.
authors.forename: Teemu J
authors.initials: TJ
authors.lastname: Niiranen
authors.affiliation: b Department of Medicine , Turku University Hospital , Turku , Finland.
authors.forename: Juha
authors.initials: J
authors.lastname: Varis
authors.affiliation: a Department of Health , National Institute for Health and Welfare , Turku , Finland.
authors.forename: Markku
authors.initials: M
authors.lastname: Peltonen
authors.affiliation: a Department of Health , National Institute for Health and Welfare , Turku , Finland.
authors.forename: Veikko
authors.initials: V
authors.lastname: Salomaa
authors.affiliation: a Department of Health , National Institute for Health and Welfare , Turku , Finland.
authors.forename: Antti M
authors.initials: AM
authors.lastname: Jula
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood*; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000378:metabolism; D005260:Female; D005387:Finland / Q000453:epidemiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D018570:Risk Assessment; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects / Q000453:epidemiology*
chemical_list: D015415:Biomarkers
keywords: Cardiovascular diseases; coronary revascularization; prevention; risk assessment; risk prediction; statistical models