Metabolic and Cardiovascular Risks in Women with Polycystic Ovary Syndrome: Focus on Type 2 Diabetes, MASLD, and Cardiovascular Disease
DOI:
https://doi.org/10.53350/pjmhs2023176538Abstract
Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women of reproductive age, associated not only with reproductive dysfunction but also with a significantly increased risk of metabolic complications.
Objective: This study aims to assess the prevalence and risk predictors of these comorbidities among women with PCOS, with emphasis on phenotypic variation.
Methods: This cross-sectional observational study was conducted at Shalamar institute of health sciences Lahore during march 2022 to march 2023. A total of 455 women with PCOS, aged between 18 and 45 years, were enrolled using consecutive sampling technique. All participants underwent a thorough clinical evaluation that included documentation of medical history, physical examination, and anthropometric measurements. Body mass index (BMI) was calculated from measured height and weight.
Results: Among 455 participants, the prevalence of T2DM was 22.4%, impaired glucose tolerance was 14.9%, MASLD was present in 31.4%, and 18.9% showed elevated CIMT. The classic PCOS phenotype (hyperandrogenism and anovulation) showed significantly higher rates of all metabolic complications. Independent predictors of T2DM included BMI ≥30 kg/m² (OR 2.31, p<0.001), HOMA-IR ≥2.5 (OR 1.84, p=0.015), and low HDL-C (OR 1.47, p=0.042). MASLD was independently associated with elevated ALT and obesity. Cardiovascular risk was strongly linked to central obesity, high LDL-C, and elevated hs-CRP.
Conclusions: It is concluded that women with PCOS, particularly those with the classic phenotype, are at high risk for T2DM, MASLD, and early CVD. These findings support the need for early metabolic screening, phenotype-based risk stratification, and multidisciplinary management to mitigate long-term complications.
Keywords: POCS, Type 2 Diabetes Mellitus, Cardiovascular Disease, MASLD
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Copyright (c) 2023 Irfan Ullah, Ali Raza Ahmad, Kiran Khan, Lata Devi Sajnani, Atif Ahmed Khan, Shakeel Akhtar

This work is licensed under a Creative Commons Attribution 4.0 International License.
