Relationship between hematologic parameters related to systemic inflammation and insulin resistance-associated metabolic parameters in women with polycystic ovary syndrome

多囊卵巢综合征女性全身炎症相关血液学参数与胰岛素抵抗相关代谢参数之间的关系

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Abstract

OBJECTIVE: The aim of the present study was to evaluate the associations between hematologic parameters related to systemic inflammation and insulin resistance-associated metabolic parameters in women with polycystic ovary syndrome (PCOS). METHODS: Eighty-two women between the ages of 18 and 35 years who were diagnosed with PCOS were included in this study. A 2-hour 75-g oral glucose tolerance test (OGTT) was administered to all study participants; fasting and postprandial glucose and insulin levels were measured simultaneously during the 2-hour OGTT. Hematologic parameters were derived from a standard complete blood count and a differential count of fasting-state blood samples. The correlations between hematologic parameters and insulin resistance-associated clinical and metabolic parameters were evaluated using the Spearman rank correlation and partial correlation coefficients. Hematologic parameters related to systemic inflammation were compared between the two groups, categorized by the presence or absence of insulin resistance. RESULTS: Significant differences in the absolute neutrophil count, absolute monocyte count, platelet count, and neutrophil-lymphocyte ratio were found between the insulin-resistant group and insulin-nonresistant group. Correlation analysis found that all hematological parameters, except for the platelet-lymphocyte ratio, were associated with at least one insulin resistance-associated metabolic parameter. However, these significant correlations between hematological and metabolic parameters were attenuated after controlling for the effects of other covariates using partial correlation analysis. CONCLUSION: The association between hematologic parameters indicative of systemic inflammation and insulin resistance-associated metabolic parameters seems to be strongly influenced by other anthropometric covariates in women with PCOS.

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