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通过体外受精,利用卵巢体积和窦卵泡计数预测低反应者和高反应者。

Ovarian volume and antral follicle count for the prediction of low and hyper responders with in vitro fertilization.

作者信息

Kwee Janet, Elting Mariet E, Schats Roel, McDonnell Joseph, Lambalk Cornelis B

机构信息

Vrije Universiteit Medical Center, Amsterdam, The Netherlands.

出版信息

Reprod Biol Endocrinol. 2007 Mar 15;5:9. doi: 10.1186/1477-7827-5-9.

Abstract

BACKGROUND

The current study was designed to compare antral follicle count (AFC) and basal ovarian volume (BOV), the exogenous FSH ovarian reserve test (EFORT) and the clomiphene citrate challenge test (CCCT), with respect to their ability to predict poor and hyper responders.

METHODS

One hundred and ten regularly menstruating patients, aged 18-39 years, participated in this prospective study, randomized, by a computer designed 4-blocks system study into two groups. Fifty six patients underwent a CCCT, and 54 patients underwent an EFORT. All patients underwent a transvaginal sonography to measure the basal ovarian volume and count of basal antral follicle. In all patients, the test was followed by a standard IVF treatment. The result of ovarian hyperstimulation during IVF treatment, expressed by the total number of follicles, was used as gold standard.

RESULTS

The best prediction of ovarian reserve (Y) was seen in a multiple regression prediction model that included, AFC, Inhibin B-increment in the EFORT and BOV simultaneously (Y = -3.161 + 0.805 x AFC (0.258-1.352) + 0.034 x Inh. B-incr. (0.007-0.601) + 0.511 BOV (0.480-0.974) (r = 0.848, p < 0.001). Univariate logistic regression showed that the best predictors for poor response were the CCCT (ROC-AUC = 0.87), the bFSH (ROC-AUC = 0.83) and the AFC (ROC-AUC = 0.83). Multiple logistic regression analysis did not produce a better model in terms of improving the prediction of poor response. For hyper response, univariate logistic regression showed that the best predictors were AFC (ROC-AUC = 0.92) and the inhibin B-increment in the EFORT (ROC-AUC = 0.92), but AFC had better test characteristics, namely a sensitivity of 82% and a specificity 89%. Multiple logistic regression analysis did not produce a better model in terms of predicting hyper response.

CONCLUSION

In conclusion AFC performs well as a test for ovarian response being superior or at least similar to complex expensive and time consuming endocrine tests. It is therefore likely to be the test for general practise.

摘要

背景

本研究旨在比较窦卵泡计数(AFC)、基础卵巢体积(BOV)、外源性促卵泡激素卵巢储备试验(EFORT)和克罗米芬激发试验(CCCT)预测低反应者和高反应者的能力。

方法

110例年龄在18 - 39岁、月经周期规律的患者参与了这项前瞻性研究,通过计算机设计的4区组系统随机分为两组。56例患者接受了CCCT,54例患者接受了EFORT。所有患者均接受经阴道超声检查以测量基础卵巢体积和基础窦卵泡计数。所有患者在检查后均接受标准的体外受精治疗。体外受精治疗期间卵巢过度刺激的结果,以卵泡总数表示,用作金标准。

结果

在一个多元回归预测模型中观察到对卵巢储备(Y)的最佳预测,该模型同时纳入了AFC、EFORT中的抑制素B增加值和BOV(Y = -3.161 + 0.805×AFC(0.258 - 1.352)+ 0.034×抑制素B增加值(0.007 - 0.601)+ 0.511×BOV(0.480 - 0.974)(r = 0.848,p < 0.001)。单因素逻辑回归显示,低反应的最佳预测指标是CCCT(ROC - AUC = 0.87)、基础促卵泡激素(bFSH)(ROC - AUC = 0.83)和AFC(ROC - AUC = 0.83)。多元逻辑回归分析在改善低反应预测方面未产生更好的模型。对于高反应,单因素逻辑回归显示最佳预测指标是AFC(ROC - AUC = 0.92)和EFORT中的抑制素B增加值(ROC - AUC = 0.92),但AFC具有更好的检测特征,即敏感性为82%,特异性为89%。多元逻辑回归分析在预测高反应方面未产生更好的模型。

结论

总之,AFC作为卵巢反应的检测方法表现良好,优于或至少类似于复杂、昂贵且耗时的内分泌检测方法。因此,它很可能成为一般临床实践中的检测方法。

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