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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/33092
Title: Towards the insulin resistance and obesity diagnosis: A dimensional analysis approach
Other Titles: 
Authors: Velásquez, Jesús
Severeyn, Erika
Herrera, Hector Antonio
Utrera, Nestor
Encalada Torres, Lorena Esperanza
Wong de balzan , Sara Null
Keywords: Bmi
Dimensional Analysis
Homa-Ir
Insulin Resistance
Obesity
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 3. Ciencias Médicas y de la Salud
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 3.2.20 Endocrinología y Metabolismo
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 3.2 Medicina Clínica
metadata.dc.ucuenca.areaconocimientounescoamplio: 09 - Salud y Bienestar
metadata.dc.ucuenca.areaconocimientounescodetallado: 0914 - Tecnologías de Diagnóstico y Tratamiento Médico
metadata.dc.ucuenca.areaconocimientounescoespecifico: 091 - Salud
Issue Date: 2018
metadata.dc.ucuenca.embargoend: 31-Dec-2050
metadata.dc.ucuenca.volumen: volumen 00
metadata.dc.source: 2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018. Proceeding
metadata.dc.identifier.doi: 10.1109/ETCM.2018.8580313
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.dc.description.city: 
Cuenca
metadata.dc.type: ARTÍCULO DE CONFERENCIA
Abstract: 
Diabetes mellitus and cardiovascular diseases are ailments related to insulin resistance (IR) and obesity. The existing methods for IR and obesity diagnosis are the HOMA-IR and body mass index (BMI), respectively. Those methods have limitations in the diagnosis. The aim of this research is to propose dimensionless indexes that can diagnose subjects with IR and obesity using anthropometrics and biochemical variables (waist circumference, height, weight, systolic blood pressure, diastolic blood pressure and triglycerides). Three dimensionless indexes, designed from the π Vaschy-Buckingham theorem, were assessed using receiver operating characteristic (ROC) curves and a database of 829 subjects. The index π 1 , constructed with the variables: waist circumference, triglycerides height and weight; obtained a better performance as classifier of IR and obesity, presenting an area under the ROC curve of 0.78, sensitivity of 0.82 and specificity of 0.68 for IR diagnosis, and an area under the ROC curve of 0.68, sensitivity of 0.66 and specificity of 0.65 for obesity diagnosis. The π 1 dimensionless index designed in this study is a simple method that allows diagnosing two pathologies from variables that can be collected in a routine medical examination.
Description: 
Diabetes mellitus and cardiovascular diseases are ailments related to insulin resistance (IR) and obesity. The existing methods for IR and obesity diagnosis are the HOMA-IR and body mass index (BMI), respectively. Those methods have limitations in the diagnosis. The aim of this research is to propose dimensionless indexes that can diagnose subjects with IR and obesity using anthropometrics and biochemical variables (waist circumference, height, weight, systolic blood pressure, diastolic blood pressure and triglycerides). Three dimensionless indexes, designed from the π Vaschy-Buckingham theorem, were assessed using receiver operating characteristic (ROC) curves and a database of 829 subjects. The index π 1 , constructed with the variables: waist circumference, triglycerides height and weight; obtained a better performance as classifier of IR and obesity, presenting an area under the ROC curve of 0.78, sensitivity of 0.82 and specificity of 0.68 for IR diagnosis, and an area under the ROC curve of 0.68, sensitivity of 0.66 and specificity of 0.65 for obesity diagnosis. The π 1 dimensionless index designed in this study is a simple method that allows diagnosing two pathologies from variables that can be collected in a routine medical examination.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060711823&origin=inward
metadata.dc.ucuenca.urifuente: https://ieeexplore.ieee.org/xpl/conhome/8561378/proceeding
ISBN: 978-153866657-9
ISSN: 0000-0000
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