title: siMS Score: Simple Method for Quantifying Metabolic Syndrome.
abstract: OBJECTIVE
  To evaluate siMS score and siMS risk score, novel continuous metabolic syndrome scores as methods for quantification of metabolic status and risk.
  
  
  METHODS
  Developed siMS score was calculated using formula: siMS score = 2*Waist/Height + Gly/5.6 + Tg/1.7 + TAsystolic/130-HDL/1.02 or 1.28 (for male or female subjects, respectively). siMS risk score was calculated using formula: siMS risk score = siMS score * age/45 or 50 (for male or female subjects, respectively) * family history of cardio/cerebro-vascular events (event = 1.2, no event = 1). A sample of 528 obese and non-obese participants was used to validate siMS score and siMS risk score. Scores calculated as sum of z-scores (each component of metabolic syndrome regressed with age and gender) and sum of scores derived from principal component analysis (PCA) were used for evaluation of siMS score. Variants were made by replacing glucose with HOMA in calculations. Framingham score was used for evaluation of siMS risk score.
  
  
  RESULTS
  Correlation between siMS score with sum of z-scores and weighted sum of factors of PCA was high (r = 0.866 and r = 0.822, respectively). Correlation between siMS risk score and log transformed Framingham score was medium to high for age groups 18+,30+ and 35+ (0.835, 0.707 and 0.667, respectively).
  
  
  CONCLUSIONS
  siMS score and siMS risk score showed high correlation with more complex scores. Demonstrated accuracy together with superior simplicity and the ability to evaluate and follow-up individual patients makes siMS and siMS risk scores very convenient for use in clinical practice and research as well.
authors.affiliation: Institute of Medical Statistics and Informatics, Belgrade, Serbia.|School of Medicine, University of Belgrade, Belgrade, Serbia.
authors.forename: Ivan
authors.initials: I
authors.lastname: Soldatovic
authors.affiliation: Mother and Child Health Care Institute of Serbia "Dr Vukan Cupic", Belgrade, Serbia.
authors.forename: Rade
authors.initials: R
authors.lastname: Vukovic
authors.affiliation: Clinic of Gastroenterology and Hepatology, Clinical Center of Serbia, Belgrade, Serbia.|School of Medicine, University of Belgrade, Belgrade, Serbia.
authors.forename: Djordje
authors.initials: D
authors.lastname: Culafic
authors.affiliation: Institute of Medical Statistics and Informatics, Belgrade, Serbia.|School of Medicine, University of Belgrade, Belgrade, Serbia.
authors.forename: Milan
authors.initials: M
authors.lastname: Gajic
authors.affiliation: Clinic of Endocrinology, Diabetes and Metabolism Disorders, Clinical Center of Serbia, Belgrade, Serbia.|School of Medicine, University of Belgrade, Belgrade, Serbia.
authors.forename: Vesna
authors.initials: V
authors.lastname: Dimitrijevic-Sreckovic
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D019540:Area Under Curve; D015992:Body Mass Index; D002648:Child; D005260:Female; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D024821:Metabolic Syndrome / Q000150:complications / Q000378:metabolism / Q000473:pathology*; D008875:Middle Aged; D009765:Obesity / Q000150:complications; D025341:Principal Component Analysis; D012372:ROC Curve; D012189:Retrospective Studies; D012307:Risk Factors; D012720:Severity of Illness Index; D055105:Waist Circumference; D055815:Young Adult