PCOS患者发生高同型半胱氨酸血症的危险因素分析及预测模型构建OA

Objective We aimed to identify risk factors and develop a prediction model for hyperhomocysteinemia(HHcy)in patients with polycystic ovary syndrome(PCOS).Methods This study retrospectively reviewed 306 PCOS patients from Nanyang Cen-tral Hospital(Jan 2022-Jan 2025).Patients were categorized into HHCY(n=97)and non-HHCY(n=209)groups based on a homo-cysteine(Hcy)cutoff of≥15 µmol/L.After collecting baseline data,we employed logistic regression to identify risk factors for HHCY,built a composite index from these factors,and evaluated its predictive performance using ROC curve analysis.Results Age,body mass index(BMI),gestational diabetes,testosterone(T),bilirubin(TBil),direct bilirubin(DBil),fasting insulin(FINS),and insulin resistance(HOMA-IR)are influencing factors for the development of HHCY in patients with polycystic ovary syndrome(PCOS)(P<0.05).Multivariate Logistic regression analysis revealed that high BMI,high T level,and high HOMA-IR value were independent risk factors for the occurrence of HHCY in PCOS patients(P<0.05).A low DBil level was an independent protective factor against the occurrence of HHCY in PCOS patients(P<0.05).ROC curve analysis showed that the area under the curve(AUC)values for BMI,T,DBil,HOMA-IR,and the comprehensive index in predicting HHCY occurrence in PCOS patients were 0.892,0.766,0.743,0.762,and 0.992,respectively.The comprehensive index had the highest predictive value.Conclusion High BMI,insulin resistance,and elevated testosterone levels are independent risk factors for the development of HHCY in patients with PCOS,whereas DBil serves as an independent protective factor.The comprehensive prediction model constructed based on these factors demon-strates high predictive value.