Unveiling Systemic Immune Inflammation Index Correlations in Women with Polycystic Ovary Syndrome: A Cross-sectional Study

Wisam Akram; Amenah Fadhil; Wassan Nori

doi:10.54133/ajms.v6i2.934

Authors

Wisam Akram Department of Obstetrics and Gynecology, College of Medicine, Mustansiriyah University, Baghdad, Iraq https://orcid.org/0000-0002-1968-7004
Amenah Fadhil Department of Obstetrics and Gynecology, College of Medicine, Mustansiriyah University, Baghdad, Iraq https://orcid.org/0000-0002-9962-2197
Wassan Nori Department of Obstetrics and Gynecology, College of Medicine, Mustansiriyah University, Baghdad, Iraq https://orcid.org/0000-0002-8749-2444

DOI:

https://doi.org/10.54133/ajms.v6i2.934

Keywords:

Clinical biomarkers, Hormonal Parameter, Polycystic ovary syndrome, Screening

Abstract

Background: Polycystic ovary syndrome (PCOS) is a common endocrinopathy of reproductive-age women that imposes metabolic and cardiovascular risks. Systemic immune inflammation index (SII), an inflammatory biomarker calculated from a complete blood count, was linked to many metabolic and cardiovascular illnesses. Objective: To evaluate the SII correlation with clinical, biochemical, and hormonal parameters characteristic of PCOS cases for screening and diagnostic values. Methods: For fifty PCOS patients who were eligible, we did a cross-sectional study and collected three types of information on each person: demographic information like age, menstrual cycle length, and body mass index (BMI); hormonal information like LH/FSH ratio, testosterone, and fasting insulin; and biochemical information like the homeostasis model assessment of insulin resistance (HOMA-IR), serum cholesterol, serum HDL, and serum LDL. The systemic inflammatory index (SII) was calculated from a complete blood count. Results: We found a strong positive correlation between SII and BMI, LH/FSH ratio, testosterone, fasting serum insulin, HOMA-IR, cholesterol, and LDL. However, the correlation between SII, HDL and menstrual cycle days was negative. Regarding the other parameters (HOMA-IR, testosterone, cholesterol, BMI, and LH/FSH ratio), the best subset regression model figures out how strongly SII is linked to each one. Conclusions: SII was strongly and significantly correlated to PCOS clinical, biochemical, and hormonal parameters, which makes it recommendable for screening. Its feasibility, affordability, and meaningful correlation inspired therapeutic and prognostic applications in practice.

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