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Predictive capability of fasting-state glucose and insulin measurements for abnormal glucose tolerance in women with polycystic ovary syndrome / 대한생식의학회지
Clinical and Experimental Reproductive Medicine ; : 156-162, 2021.
Article in English | WPRIM | ID: wpr-897614
ABSTRACT
Objective@#The aim of the present study was to evaluate the predictive capability of fasting-state measurements of glucose and insulin levels alone for abnormal glucose tolerance in women with polycystic ovary syndrome (PCOS). @*Methods@#In total, 153 Korean women with PCOS were included in this study. The correlations between the 2-hour postload glucose (2-hr PG) level during the 75-g oral glucose tolerance test (OGTT) and other parameters were evaluated using Pearson correlation coefficients and linear regression analysis. The predictive accuracy of fasting glucose and insulin levels and other fasting-state indices for assessing insulin sensitivity derived from glucose and insulin levels for abnormal glucose tolerance was evaluated using receiver operating characteristic (ROC) curve analysis. @*Results@#Significant correlations were observed between the 2-hr PG level and most fasting-state parameters in women with PCOS. However, the area under the ROC curve values for each fasting-state parameter for predicting abnormal glucose tolerance were all between 0.5 and 0.7 in the study participants, which falls into the “less accurate” category for prediction. @*Conclusion@#Fasting-state measurements of glucose and insulin alone are not enough to predict abnormal glucose tolerance in women with PCOS. A standard OGTT is needed to screen for impaired glucose tolerance and type 2 diabetes mellitus in women with PCOS.
Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: English Journal: Clinical and Experimental Reproductive Medicine Year: 2021 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: English Journal: Clinical and Experimental Reproductive Medicine Year: 2021 Type: Article