PREDICTION MODEL IN OPTIMAL COUNSELING ON CHANCESOF A PREGNANCY AFTER IN VITRO FERTILIZATION


Cite item

Full Text

Abstract

A total of 318 couples undergoing IVF were observed. The multinomial logistic regression model was specified for global process. The main outcome measures were: ongoing pregnancy, miscarriage before and after 12 weeks gestation, live birth. The significant explanatory variables for global process were female age (odds ratio 1,064), previous live births (odds ratio 0,488), diminished ovarian reserve (odds ratio 2,589).

Keywords

About the authors

Y A ZAZULINA

Самарский государственный медицинский университет

Email: chary@yandex.ru

References

  1. Anti-Mullerian hormone-based prediction model for a live birth in assisted reproduction. A. La Marca [et al.] // Reproductive BioMedicine Online. - 2011. №22. - P. 341-349.
  2. Antral follicle count is a significant predictor of livebirth in in vitro fertilization cycles. P. B. Maseelall [et al.] // Fertil. Steril. - 2009. Vol. 91. № 4. -P. 1595-1597.
  3. A simple multivariate score could predict ovarian reserve, as well as pregnancy rate, in infertile women. J.S. Younis [et al.] // Fertil. Steril. - 2010. Vol. 94. № 2. - P. 655-661.
  4. External validation of anti-Müllerian hormone based prediction of live birth in assisted conception. A. Khader [et al.] // Journal of Ovarian Research. -2013.Vol. 6. № 3. - P.1-6.
  5. Prediction models in in vitro fertilization; where are we? A mini review. L.L. Loendersloot [et al.] // Journal of advanced research. - 2014. № 5. -P. 295-301.
  6. Role of Baseline Antral Follicle Count and Anti-Mullerian Hormone in Prediction of Cumulative Live Birth in the First In Vitro Fertilisation Cycle: A Retrospective Cohort Analysis. H.W.R. Li [et al.] // PLoS ONE. - 2013. Vol. 8. № 4: e61095. doi: 10.1371/journal.pone.0061095.

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2016 ZAZULINA Y.A.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).