Correlation and predictive value of systemic immune-inflammation index for dyslipidemia in patients with polycystic ovary syndrome.

Background: Polycystic ovary syndrome(PCOS) is one of the main factors leading to infertility in women of reproductive age, which is often accompanied by metabolic changes such as obesity and chronic low-grade inflammation. Chronic inflammation may play an important role in the occurrence and development of metabolic diseases. Therefore, it is of great significance to explore the relationship between abnormal lipid metabolism and inflammation in PCOS patients. This study aims to analyze the correlation between systemic immune-inflammatory(SII) markers and dyslipidemia in patients with PCOS and their value in early diagnosis. Methods: A total of 617 PCOS patients aged 20–35 years (according to the Rotterdam diagnostic criteria) who visited the Reproductive Center of the First Hospital of Lanzhou University from January 2020 to December 2022 were included. According to the presence or absence of dyslipidemia, the patients were divided into normal lipid metabolism group and abnormal lipid metabolism group. The clinical data of the patients were collected and analyzed by SPSS software. Results: There were 454 patients with normal lipid metabolism and 163 patients with abnormal lipid metabolism. The SII level of the abnormal lipid metabolism group was higher than that of the normal group. As the SII quartile increased, TC, TG and LDL increased, while HDL decreased accordingly. The SII level was positively correlated with TC, TG and LDL, and negatively correlated with HDL (all P < 0.05). Among them, SII had the best predictive efficiency for dyslipidemia of polycyctic ovary syndrome at 489.375 (AUC: 0.718, 95%CI: 0.672–0.764), and SII was still associated with the increased occurrence of PCOS dyslipidemia after excluding confounding factors (P < 0.05). Conclusion: The high level of SII has a correlation with the occurrence of dyslipidemia in PCOS patients, and it has a value in the early diagnosis of PCOS. [ABSTRACT FROM AUTHOR]