Clinical and anamnestic predictors of the effectiveness of in vitro fertilization

DOI

https://dx.doi.org/10.18565/aig.2025.243

Krasilnikova A.K., Malyshkina A.I., Panova I.A., Boyko E.L.
V.N. Gorodkov Ivanovo Research Institute of Maternity and Childhood, Ministry of Health of Russia, Ivanovo, Russia

Objective: to systematize current data on key clinical and anamnestic factors determining the success of in vitro fertilization (IVF) and to assess the potential of artificial intelligence (AI) technologies for their integral analysis and application in personalized reproductive medicine.
Despite significant advances in assisted reproductive technologies (ART), the IVF efficacy remains limited, and the rates of recurrent implantation failure (RIF) and pregnancy loss are still high. This determines the need for a comprehensive analysis of the factors affecting the reproductive outcome and the search for new approaches to personalized treatment.
The outcome of IVF is determined by the interaction of non-modifiable and modifiable factors. Non-modifiable factors include patient age (which diminishes ovarian reserve and gamete quality), duration and type of infertility, as well as gynecological and general medical history (endometriosis, PCOS, thyroid pathology, thrombophilia, chronic diseases). Modifiable factors are related to lifestyle and include deviations in body mass index (obesity and underweight), nutritional status (micronutrient deficiencies), harmful habits (smoking), occupational risks, stress levels, and sleep quality. Correcting these modifiable factors forms the basis of preconception care. AI and machine learning technologies are capable of analyzing large amounts of clinical and anamnestic data, revealing hidden patterns and complex relationships to build predictive models and optimize treatment protocols.
Conclusion: The transition towards personalized reproductive medicine, based on the integration of clinical experience and AI technologies, is a key direction for improving the efficacy of IVF and improving reproductive outcomes.

Authors’ contributions: Krasilnikova A.K., Panova I.A., Boyko E.L., Malyshkina A.I. – developing the concept and design of the study; Krasilnikova A.K. – collecting the material, writing the text; Panova I.A., Boyko E.L., Malyshkina A.I. – editing the article.
Conflicts of interest: Authors declare lack of the possible conflicts of interest.
Funding: The study was conducted without sponsorship.
For citation: Krasilnikova A.K., Malyshkina A.I., Panova I.A., Boyko E.L.
Clinical and anamnestic predictors of the effectiveness of in vitro fertilization.
Akusherstvo i Ginekologiya/Obstetrics and Gynecology. 2025; (3): 30-36 (in Russian)
https://dx.doi.org/10.18565/aig.2025.243

in vitro fertilization

efficacy

modifiable and non-modifiable risk factors

prediction

artificial intelligence

Full text (in Russian)

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Received 01.09.2025

Accepted 13.02.2026

Angelina K. Krasilnikova, Dr. Med. Sci., Senior Researcher at the Department of Obstetrics and Gynecology, V.N. Gorodkov Ivanovo Research Institute of Maternity and Childhood, Ministry of Health of Russia, 153045, Russia, Ivanovo, Pobedy str., 20, +7(920)345-68-09, brasilia71@mail.ru, https://orcid.org/0000-0001-7839-3893
Anna I. Malyshkina, Dr. Med. Sci., Professor, Director, V.N. Gorodkov Ivanovo Research Institute of Maternity and Childhood, Ministry of Health of Russia, 153045, Russia, Ivanovo, Pobedy str., 20, +7(910)982-24-19, anna_im@mail.ru, https://orcid.org/0000-0002-1145-0563
Irina А. Panova, Dr. Med. Sci., Professor, Head of the Department of Obstetrics and Gynecology, Neonatology, Anesthesiology and Resuscitation, V.N. Gorodkov Ivanovo Research Institute of Maternity and Childhood, Ministry of Health of Russia, 153045, Russia, Ivanovo, Pobedy str., 20, +7(910)689-06-00, ia_panova@mail.ru,
https://orcid.org/0000-0002-0828-6547
Еlena L. Boyko, Dr. Med. Sci., Senior Researcher at the Department of Obstetrics and Gynecology, V.N. Gorodkov Ivanovo Research Institute of Maternity and Childhood, Ministry of Health of Russia, 153045, Russia, Ivanovo, Pobedy str., 20, +7(920)670-74-14, Dr-Boyko@mail.ru, https://orcid.org/0000-0002-8907-4860
Corresponding author: Angelina K. Krasilnikova, brasilia71@mail.ru

Clinical and anamnestic predictors of the effectiveness of in vitro fertilization

Krasilnikova A.K., Malyshkina A.I., Panova I.A., Boyko E.L.

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