Vaginal microflora as a factor influencing the success of embryo cryotransfer in women with repeated art failures

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Background: To date, the pregnancy rate in assisted reproductive technology (ART) programs does not exceed 45%, which emphasizes the need to search for new methods to improve the effectiveness of infertility treatment. Particular attention is paid to the study of vaginal opportunistic microflora (OMF) in patients planning pregnancy using ART. In Russia, the study of the urogenital flora of the reproductive tract before the in vitro fertilization (IVF) program is not provided, although such studies are conducted in other countries.

Objective: Evaluation of the clinical significance of OMF for predicting pregnancy after thawed embryo transfer in women with IVF failures.

Materials and methods: This retrospective cohort study included 66 patients aged 20 to 42 years with tubal-peritoneal factor of infertility, with 2 or more unsuccessful IVF attempts, without contraindications to infertility treatment using ART methods, who underwent thawed embryo transfer into the uterine cavity on day 18–21 of the menstrual cycle. OMF was assessed using the on-site polymerase chain reaction method. Before this, all women underwent scraping of epithelial cells from the vaginal walls on day 5–6 of the menstrual cycle. 14 days after embryo transfer, a retrospective analysis of ART programs was performed and a relationship between UPMF and pregnancy rate was revealed.

Results: A prognostic model was developed to determine the probability of pregnancy during thawed embryo transfer based on data on bacteria (Candida spp., Staphylococcus spp., Enterobacterium spp., Eubacterium spp., Gardnerella, Lachnobacterium spp., Lactobacillus spp., Megasphaera spp. and Mobiluncus spp.) using binary logistic regression. It was found that these types of bacteria make the greatest contribution to the outcomes of thawed embryo transfer programs (AUC = 0.698, 95% CI 0.572–0.824; p = 0.006).

Conclusion: The study showed that in women with unsuccessful IVF attempts, a combination of opportunistic microorganisms is significant in predicting the outcome of ART. Their ratio is important for the onset of pregnancy and fetal gestation. Including microflora analysis in preparation for IVF programs can improve the results of infertility treatment.

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作者简介

Alina Karmakova

National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov

编辑信件的主要联系方式.
Email: maksimovnalina@gmail.com

Obstetrician-Gynecologist, Postgraduate Student, Department of Assisted Technologies in the Treatment of Infertility named after B.V. Leonov

俄罗斯联邦, Moscow

E. Kulakova

National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov

Email: e_kulallokav@oprina4.ru
ORCID iD: 0000-0002-4433-4163

Dr. Sci. (Med.), Obstetrician-Gynecologist, Senior Researcher, Department of Assisted Technologies in the Treatment of Infertility named after B.V. Leonov

俄罗斯联邦, Moscow

N. Makarova

National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov

Email: np_makarova@oparina4.ru

Dr. Sci. (Biol.), Senior Embryologist, Leading Researcher, Department of Assisted Technologies in Infertility Treatment named after B.V. Leonov

俄罗斯联邦, Moscow

D. Boris

National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov

Email: dayana_boris@mail.ru
ORCID iD: 0000-0002-0387-4040

Cand. Sci. (Med.), Obstetrician-Gynecologist, Ultrasound Diagnostician, Researcher. Department of Aesthetic Gynecology

俄罗斯联邦, Moscow

E. Kalinina

National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov

Email: e_kalinina@oparina4.ru
ORCID iD: 0000-0002-8922-2878

Dr. Sci. (Med.), Professor, Head of the Department of Assisted Technologies in Infertility Treatment named after B.V. Leonov

俄罗斯联邦, Moscow

参考

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2. Figure 1. Design of a retrospective cohort study

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3. Figure 2. Estimation of the odds ratio with 95% Cl for the studied predictors of pregnancy

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4. Figure 3. ROC curve characterizing the discriminatory ability of the regression model in predicting pregnancy

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