Prediction of metabolic syndrome using artificial neural network system based on clinical data including insulin resistance index and serum adiponectin

2011 ◽  
Vol 41 (11) ◽  
pp. 1051-1056 ◽  
Author(s):  
Hiroshi Hirose ◽  
Tetsuro Takayama ◽  
Shigenari Hozawa ◽  
Toshifumi Hibi ◽  
Ikuo Saito
2004 ◽  
Vol 89 (1) ◽  
pp. 87-90 ◽  
Author(s):  
Yukihiro Yamamoto ◽  
Hiroshi Hirose ◽  
Ikuo Saito ◽  
Kanako Nishikai ◽  
Takao Saruta

It has been reported that the serum adiponectin level was negatively correlated with body mass index (BMI), insulin resistance index, and triglycerides and was positively correlated with high-density lipoprotein cholesterol in several cross-sectional studies. However, the causal relationship has not been elucidated. We investigated whether the baseline adiponectin level could predict subsequent changes in insulin resistance, lipid profile, or body weight in a 2-yr longitudinal study. This study included 590 male Japanese subjects, aged 30–65 yr, who received annual health checkups in both 2000 and 2002. Blood pressure, heart rate, and anthropometric and metabolic parameters, including serum insulin and adiponectin levels, were determined. The insulin resistance index was calculated based on homeostasis model assessment. Baseline adiponectin level was not correlated with the subsequent change in lipid profile or BMI in 2 yr after adjustment for each baseline value. However, the baseline adiponectin level was negatively correlated with subsequent changes in insulin and insulin resistance index based on homeostasis model assessment, even after adjustment for change in BMI (r = −0.162 and r = −0.140, respectively). These findings suggest that the serum adiponectin concentration predicts subsequent changes in insulin resistance, but not in lipid profile or body weight.


1997 ◽  
Vol 7 (Supplement 1) ◽  
pp. S58 ◽  
Author(s):  
M Burroni ◽  
G Dell??Eva ◽  
P Puddu ◽  
F Atzori ◽  
R Bono ◽  
...  

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