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<p>We aimed to explore the factors affecting polycystic ovary syndrome (PCOS) with metabolic syndrome (MetS) in Chinese women of reproductive age, and to evaluate the predictive value of neck circumference (NC), TyG index, and other composite indexes. A retrospective analysis was performed on 517 patients admitted to the Second Hospital of Shandong University and Qilu Hospital of Shandong University from January 2017 to January 2024. The research included 150 normal control cases (29.01%), 175 PCOS cases (33.85%), and 192 PCOS + MetS cases (37.14%). Anthropometric indices, blood pressure, and biochemical parameters such as blood glucose, blood lipids, and related hormones were detected. ANOVA, multi-factor logistic regression analysis and ROC curve prediction analysis were performed. The adjusted odds ratios (OR) for PCOS + MetS predicted by NC and TyG were 3.516 (95%CI 1.910, 6.742) and 3.386 (95%CI 2.013, 6.208), respectively (all <i>P</i> &lt; 0.05). ROC curve analysis identified optimal cut-off values of 35.9&#xa0;cm for NC (sensitivity 84.8%, specificity 72%, <i>P</i> &lt; 0.05) and 9.04 for TyG index (sensitivity 89.6%, specificity 65.5%, <i>P</i> &lt; 0.05), respectively. Our study suggests NC and TyG are significant predictors for PCOS + MetS, and compared to TyG index, NC is more convenient, intuitive, economical, and practical.</p>

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Predictive values of neck circumference and TyG index on polycystic ovary syndrome with metabolic syndrome

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月5日

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  • Yixuan Liu,
  • Aihong Liu,
  • Xiangyu Xu,
  • Huali Wang,
  • Qinghai Wang,
  • Xianwei Huang,
  • Ping Liu

摘要

We aimed to explore the factors affecting polycystic ovary syndrome (PCOS) with metabolic syndrome (MetS) in Chinese women of reproductive age, and to evaluate the predictive value of neck circumference (NC), TyG index, and other composite indexes. A retrospective analysis was performed on 517 patients admitted to the Second Hospital of Shandong University and Qilu Hospital of Shandong University from January 2017 to January 2024. The research included 150 normal control cases (29.01%), 175 PCOS cases (33.85%), and 192 PCOS + MetS cases (37.14%). Anthropometric indices, blood pressure, and biochemical parameters such as blood glucose, blood lipids, and related hormones were detected. ANOVA, multi-factor logistic regression analysis and ROC curve prediction analysis were performed. The adjusted odds ratios (OR) for PCOS + MetS predicted by NC and TyG were 3.516 (95%CI 1.910, 6.742) and 3.386 (95%CI 2.013, 6.208), respectively (all P < 0.05). ROC curve analysis identified optimal cut-off values of 35.9 cm for NC (sensitivity 84.8%, specificity 72%, P < 0.05) and 9.04 for TyG index (sensitivity 89.6%, specificity 65.5%, P < 0.05), respectively. Our study suggests NC and TyG are significant predictors for PCOS + MetS, and compared to TyG index, NC is more convenient, intuitive, economical, and practical.