Prediction of ovarian response in IVF/ICSI cycles.

IF 1.9
Alfredo Cortés-Vazquez, Guillermo A Goitia-Landeros, Miguel A Regalado, Saúl R León-Hernández, Alfredo L Cortés-Algara, Cindy Bandala, Jesús D Moreno-García, Panagiotis Drakopoulos
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Abstract

Objective: Our study aims to evaluate the various correlations between demographic, biochemical, ultrasound, and ovarian stimulation parameters with the percentage of mature oocytes in conventional stimulation for IVF/ICSI cycles in order to develop a predictive model to improve our understanding of the oocyte maturation process.

Methods: This is a retrospective cohort study; patients underwent conventional antagonist ovarian stimulation protocols for fresh IVF/ICSI cycles. A total of 256 IVF/ICSI cycles were included. Age, antral follicle count (AFC), baseline serum follicle-stimulating hormone (FSH) levels, baseline serum luteinizing hormone (LH) levels, baseline serum estradiol (E2) levels, peak estradiol, P4 on hCG day, the body mass index (BMI), and stimulation length were measured. The variables were tested for correlations with the number of retrieved oocytes (#RO) and the number of mature oocytes (#MO). A backward stepwise regression was performed to identify the variables that correlated more strongly with percentage of mature oocytes (%MO).

Results: A predictive equation was obtained with the variables that were not excluded in the model. % MO = 72.700 - 0.910 (Age) + 0.979 (BMI) + 1.209 (Baseline serum LH) - 0.647 (Progesterone on human Chorionic Gonadotropin day).

Conclusions: We concluded that age, the BMI, baseline serum LH, and progesterone level on hCG day may predict %MO. Prospective studies are required to validate this predictive equation.

Abstract Image

IVF/ICSI周期卵巢反应的预测。
目的:我们的研究旨在评估人口统计学、生化、超声和卵巢刺激参数与IVF/ICSI周期常规刺激中成熟卵母细胞百分比之间的各种相关性,以建立预测模型,以提高我们对卵母细胞成熟过程的理解。方法:回顾性队列研究;患者在新的IVF/ICSI周期中接受常规的卵巢拮抗剂刺激方案。共纳入256个IVF/ICSI周期。测定年龄、窦腔卵泡计数(AFC)、基线血清促卵泡激素(FSH)水平、基线血清促黄体生成素(LH)水平、基线血清雌二醇(E2)水平、雌二醇峰值、hCG日P4、体重指数(BMI)、刺激时间。检验各变量与检索卵母细胞数(#RO)和成熟卵母细胞数(#MO)的相关性。进行了反向逐步回归,以确定与成熟卵母细胞百分比(%MO)相关性更强的变量。结果:利用模型中未排除的变量得到预测方程。% MO = 72.700 - 0.910(年龄)+ 0.979 (BMI) + 1.209(基线血清LH) - 0.647(人绒毛膜促性腺激素日黄体酮)。结论:我们的结论是年龄、BMI、基线血清LH和hCG日黄体酮水平可以预测%MO。需要前瞻性研究来验证这一预测方程。
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