论文部分内容阅读
目的:探讨不孕患者血清抗苗勒管激素水平与基础性激素水平的关系。方法:检测武汉大学中南医院生殖中心治疗的297例不孕患者血清抗苗勒管激素(AMH)、孕酮(PROG)、黄体生成素(LH)、促卵泡生成激素(FSH)、泌乳素(PRL)、睾酮(TESTO)及雌二醇(E2)水平,通过单因素线性回归分析及多元线性回归分析,找出血清AMH与年龄、PROG、LH、FSH、PRL、TESTO及E2的相关性。结果:AMH水平与年龄、LH、FSH、PRL、TESTO和E2的回归系数均差异有统计学意义(均P<0.05),与PROG的回归系数无统计学意义(P=0.767)。将单因素线性回归分析筛选出的因素(年龄、LH、FSH、PRL、TESTO和E2)进行多元线性回归分析,采用逐步回归向后法进行回归方程的拟合,得出回归方程YAMH=9.357-0.025XE2+0.324XLH-0.294XFSH+1.331XTESTO-0.145X年龄。即其他条件相同的情况下,血清AMH水平与LH、TESTO水平呈正相关,与E2、FSH、年龄的水平均呈负相关(均P<0.05)。结论:不孕患者血清AMH水平受LH、TESTO、E2和FSH的影响,联合检测血清基础性激素和AMH水平对预测不孕患者的卵巢功能有重要意义。
Objective: To investigate the relationship between serum anti-mullerian hormone and basic hormone levels in infertile patients. Methods: A total of 297 infertile patients treated by Reproductive Center of Zhongnan Hospital of Wuhan University were enrolled in this study. Serum anti-Mullerian hormone (AMH), progesterone (PROG), luteinizing hormone (LH), follicle stimulating hormone (FSH) PRL, TESTO and E2, and the relationship between serum AMH and age, PROG, LH, FSH, PRL, TESTO and E2 was found by one-way linear regression analysis and multiple linear regression analysis. Results: The regression coefficients of AMH, age, LH, FSH, PRL, TESTO and E2 were all significantly different (all P <0.05), but not significantly different from PROG (P = 0.767). Multiple linear regression analysis was carried out on the factors screened by single factor linear regression analysis (age, LH, FSH, PRL, TESTO and E2), and the regression equation was fitted by stepwise regression to the backward method. The regression equation was YAMH = 9.357- 0.025XE2 + 0.324XLH-0.294XFSH + 1.331XTESTO-0.145X Age. That is to say, under the same conditions, serum AMH levels were positively correlated with LH and TESTO levels, negatively correlated with E2, FSH and age (all P <0.05). CONCLUSIONS: The level of serum AMH in infertile patients is affected by LH, TESTO, E2 and FSH. Combined detection of serum essential hormones and AMH levels is of great significance in predicting ovarian function in infertile patients.