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墨西哥女性的生化、超声和人口统计学参数与 IVF/ICSI 治疗卵巢反应的相关性。

Correlation between biochemical, ultrasonographic and demographic parameters with ovarian response to IVF/ICSI treatments in Mexican women.

机构信息

Centro Médico Nacional 20 de Noviembre, Mexico City, Mexico.

出版信息

JBRA Assist Reprod. 2021 Feb 2;25(1):4-9. doi: 10.5935/1518-0557.20200040.

Abstract

OBJECTIVE

Ovarian response from a conventional ovarian stimulation protocol is a crucial step in IVF/ICSI treatments. This ovarian response encompasses a wide range of outcomes at the extremes, leading to either excessive responses with the risk of life-threatening conditions like ovarian hyperstimulation syndrome (OHSS), or poor ovarian response (POR) with poor outcomes. This study aims to integrate biochemical, ultrasonographic and demographic parameters into a mathematical formula able to predict ovarian response to stimulation in IVF/ICSI in gonadotropin-releasing hormone (GnRH) antagonist protocols.

METHODS

This retrospective analysis included 147 patients submitted to an ovarian stimulation protocol combining recombinant FSH and gonadotropin-releasing hormone antagonist. All the parameters were correlated with the Spearman Rho and Pearson´s correlation coefficient. Once the data was normalized, we used the multiple linear regression models, checking the results with the progressive discriminating analysis.

RESULTS

We classified the database according to the correlation with the number of oocytes retrieved; the progressive discriminating analysis resulted in the following equation: oocytes retrieved = 2.312-0.130 (FSH) + 0.562 (AFC).

CONCLUSIONS

The incorporation of 2 ovarian reserve parameters into a regression equation enables knowing the number of retrieved oocytes in each patient with 80.5% sensitivity and 55.4% specificity.

摘要

目的

在体外受精/卵胞浆内单精子注射(IVF/ICSI)治疗中,常规卵巢刺激方案的卵巢反应是一个关键步骤。这种卵巢反应在极端情况下涵盖了广泛的结果,导致过度反应,存在危及生命的卵巢过度刺激综合征(OHSS)等风险,或者卵巢反应不良(POR)导致不良结局。本研究旨在将生化、超声和人口统计学参数整合到一个数学公式中,以预测 GnRH 拮抗剂方案中 IVF/ICSI 中卵巢对刺激的反应。

方法

本回顾性分析纳入了 147 名接受重组 FSH 和 GnRH 拮抗剂联合卵巢刺激方案的患者。所有参数均与 Spearman Rho 和 Pearson 相关系数相关。在对数据进行归一化后,我们使用多元线性回归模型,并通过逐步判别分析检查结果。

结果

我们根据与获得的卵母细胞数量的相关性对数据库进行分类;逐步判别分析得出以下方程:获得的卵母细胞数=2.312-0.130(FSH)+0.562(AFC)。

结论

将 2 个卵巢储备参数纳入回归方程,可以以 80.5%的敏感性和 55.4%的特异性预测每位患者获得的卵母细胞数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c1ee/7863092/f4f7784ef612/jbra-25-01-0004-g01.jpg

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