ABSTRACT
@#Objective To investigate the relationship between subclinical hypothyroidism (SCH) and visceral adipose tissue. Methods A total of 68 SCH subjects from medical examination center and inpatient department of our hospital and 100 healthy controls matched for age and sex were enrolled in this study. The patient gender, blood pressure (SBP/DBP), anthropometric measurements, lipid profile, lipid accumulation product (LAP) and visceral adipose area (VA) were compared between two groups. The Sperman’s correlation was used to analyze the correlation between thyroid stimulating hormone (TSH) and variables, and the Binary logistic regression analysis was used to analyze the impact of variables on SCH. Results The waist circumference (WC), waist to hip ratio (WHR), non high density lipoprotein cholesterol (nonHDL-C), three acylglycerol (TG), TSH, LAP and VA were higher in SCH subjects than that in the healthy controls (P＜0.05), while HDL-C was lower in SCH subjects (P＜0.05). There were no significant differences in sex, age, body mass index (BMI), SBP, DBP, total cholesterol (TC) and low density lipoprotein cholesterol (LDL-C) between two groups (P<0.05). Correlation analysis showed that TSH was positively correlated with WC, TG, nonHDL-C, LAP and VA, and negatively correlated with HDL-C (P＜0.05). There was no significant correlation between TSH and age, BMI, WHR, TC and LDL-C (P> 0.05). Binary logistic regression analysis showed that female and low level of HDL-C were risk factors of SCH, while the effects of VA and LAP on SCH were not statistically significant. Conclusion Our findings show that the dyslipidemia and VA increase are more serious in subjects with SCH than those with normal thyroid function and healthy controls, which suggest that SCH is closely related to abdominal obesity.
ABSTRACT
Taking abstracts of Chinese medical papers as corpus,the paper adopts the combination of 3 feature selection methods and 2 topic modeling methods to carry out topic modeling.The result shows that in the modeling methods,prediction ability and fitting degree of LDA are better than that of CTM,but in the feature selection methods,fitting degree of IDF and prediction ability of TF are better.