title: A prediction model for left ventricular mass in patients at high cardiovascular risk.
abstract: BACKGROUND
  Left ventricular (LV) mass has a continuous relation with cardiovascular risk, and regression of LV mass induced by pharmacological treatment is associated with improved prognosis. Therefore, early identification of patients with a large LV mass is desired. We developed a model to predict LV mass in individual hypertensives at high cardiovascular risk.
  
  
  METHODS
  We analyzed data of 536 hypertensives with symptomatic extracardiac atherosclerotic disease or marked risk factors for atherosclerosis from a cross-sectional study in a tertiary referral center. LV mass was measured by cardiac MRI. We developed the prediction rule with multivariable linear regression analysis and stepwise backward elimination. Internal validation was assessed with bootstrap sampling to obtain an estimate of model performance (R²) that may be expected for new patients.
  
  
  RESULTS
  Important predictors for LV mass included sex, height, body mass index, systolic blood pressure, and previous aneurysm of the abdominal aorta. R² of the prediction model was 45% after internal validation, which was considerably higher than the R² of previously reported models (range 1-38%). Addition of electrocardiography data showed limited improvement of the model performance (R²=47%).
  
  
  CONCLUSIONS
  We present a prediction model for LV mass in hypertensives at high cardiovascular risk. After external validation, this model may be used in clinical practice to estimate LV mass for early identification of large LV mass. The predictions of the model may support appropriate medical care in the prevention of cardiovascular disease.
authors.affiliation: Department of Cardiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, The Netherlands.
authors.forename: Matthijs F L
authors.initials: MF
authors.lastname: Meijs
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Vergouwe
authors.forename: Maarten J M
authors.initials: MJ
authors.lastname: Cramer
authors.forename: Evert-Jan A
authors.initials: EJ
authors.lastname: Vonken
authors.forename: Birgitta K
authors.initials: BK
authors.lastname: Velthuis
authors.forename: David J
authors.initials: DJ
authors.lastname: Verton
authors.forename: Yolanda
authors.initials: Y
authors.lastname: van der Graaf
authors.forename: Frank L
authors.initials: FL
authors.lastname: Visseren
authors.forename: Willem P
authors.initials: WP
authors.lastname: Mali
authors.forename: Pieter A
authors.initials: PA
authors.lastname: Doevendans
authors.forename: Michiel L
authors.initials: ML
authors.lastname: Bots
mesh_terms: D000328:Adult; D000368:Aged; D002318:Cardiovascular Diseases / Q000209:etiology*; D003430:Cross-Sectional Studies; D004562:Electrocardiography; D005260:Female; D006352:Heart Ventricles / Q000473:pathology; D006801:Humans; D006973:Hypertension / Q000150:complications* / Q000473:pathology; D017379:Hypertrophy, Left Ventricular / Q000175:diagnosis* / Q000209:etiology; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D009426:Netherlands; D011379:Prognosis; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors