Predictive factors for pregnancy during the first four intrauterine insemination cycles using gonadotropin

2013 ◽  
Vol 29 (9) ◽  
pp. 834-838 ◽  
Author(s):  
Young Eun Jeon ◽  
Ji Ann Jung ◽  
Hye Yeon Kim ◽  
Seok Kyo Seo ◽  
SiHyun Cho ◽  
...  
2016 ◽  
Vol 8 (2) ◽  
pp. 140-144
Author(s):  
Azadeh Pravin Patel ◽  
Megha Snehal Patel ◽  
Sushma Rakesh Shah ◽  
Shashwat Kamal Jani

ABSTRACT Objectives To determine the predictive factors for pregnancy after stimulated intrauterine insemination (IUI). Materials and methods A retrospective analysis of 136 patients undergoing 443 stimulated IUI cycles was done in an attempt to identify significant variables predictive of treatment success. The primary outcome measures were clinical pregnancy and live birth rates. Predictive factors evaluated were female age, duration of infertility, indication for IUI, number of preovulatory follicles, and postwash total motile fraction (TMF). Results The overall clinical pregnancy rate and live birth rate were 7.2% and 5.1 per cycle respectively. The mean number of IUI cycles per patient was 3.2, the miscarriage rate was 15%, and the multiple pregnancy rate was 3.1%. Among the predictive factors evaluated, female age (age > 37 years; p = 0.039), the duration of infertility (5.36 vs 6.71 years, p = 0.032), and the TMF (between 10 and 20 million, p = 0.003) significantly influenced the clinical pregnancy rate. Conclusion The clinical management of the selected infertile couple should be performed in an expedited manner taking into consideration the age of the woman, etiology, and duration of infertility and motile fraction of sperms. How to cite this article Patel AP, Patel MS, Shah SR, Jani SK. Predictive Factors for Pregnancy after Intrauterine Insemination: A Retrospective Study of Factors Affecting Outcome. J South Asian Feder Obst Gynae 2016;8(2):140-144.


2010 ◽  
Vol 93 (1) ◽  
pp. 79-88 ◽  
Author(s):  
Philippe Merviel ◽  
Marie Hélène Heraud ◽  
Nadège Grenier ◽  
Emmanuelle Lourdel ◽  
Pierre Sanguinet ◽  
...  

1997 ◽  
Vol 68 ◽  
pp. S112
Author(s):  
C Keck ◽  
C Gerber-Schäfer ◽  
M Breckwoldt

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Azadeh Akbari Sene ◽  
Zahra Zandieh ◽  
Mojgan Soflaei ◽  
Hamid Mokhtari Torshizi ◽  
Kourosh Sheibani

Abstract Background To evaluate the use of artificial intelligence (AI) in predicting the success rate of intrauterine insemination (IUI) treatment among infertile couples and also to determine the importance of each of the parameters affecting IUI success. This study was a retrospective cohort study in which information from 380 infertile couples undergoing IUI treatment (190 cases resulting in positive pregnancy test and 190 cases of failed IUI) including underlying factors, female factors, sperm parameters at the beginning of the treatment cycle, and fertility results were collected from 2013 to 2019 and evaluated to determine the effectiveness of AI in predicting IUI success. Results We used the most important factors influencing the success of IUI as a neural network input. With the help of a three-layer neural network, the accuracy of the AI to predict the success rate of IUI was 71.92% and the sensitivity and specificity were 76.19% and 66.67%, respectively. The effect of each of the predictive factors was obtained by calculating the ROC curve and determining the cut-off point. Conclusions The morphology, total motility, and progressive motility of the sperm were found to be the most important predictive factors for IUI success. In this study, we concluded that by predicting IUI success rate, artificial intelligence can help clinicians choose individualized treatment for infertile couples and to shorten the time to pregnancy.


Sign in / Sign up

Export Citation Format

Share Document