We have recently presented an algorithm to compute metabolic syndrome (MetS) as a continuous variable, called MetS score . It summarizes waist circumference, BMI, blood pressure, blood glucose, HDL-cholesterol and triglycerides into one quantitative phenotype that is both clinically interpretable and useful for evaluating the association with cardiovascular diseases and for investigating the MetS genetic component . We first evaluated its performance assessing the area under the receiver operating characteristics (ROC) curve, which was 0.88, indicating excellent discrimination

Graziano, F., Grassi, M., Bonati, M., Zanchetti, A., Biino, G. (2016). External validation of the MetS score, a prediction tool for metabolic syndrome. NMCD. NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES, 26(4), 359-360 [10.1016/j.numecd.2015.12.014].

External validation of the MetS score, a prediction tool for metabolic syndrome

Graziano, F;
2016

Abstract

We have recently presented an algorithm to compute metabolic syndrome (MetS) as a continuous variable, called MetS score . It summarizes waist circumference, BMI, blood pressure, blood glucose, HDL-cholesterol and triglycerides into one quantitative phenotype that is both clinically interpretable and useful for evaluating the association with cardiovascular diseases and for investigating the MetS genetic component . We first evaluated its performance assessing the area under the receiver operating characteristics (ROC) curve, which was 0.88, indicating excellent discrimination
Lettera in rivista
metabolic syndrome; ROC curve
English
359
360
2
Graziano, F., Grassi, M., Bonati, M., Zanchetti, A., Biino, G. (2016). External validation of the MetS score, a prediction tool for metabolic syndrome. NMCD. NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES, 26(4), 359-360 [10.1016/j.numecd.2015.12.014].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/222971
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