Research of Predictive Factors of in Vitro Fertilization (IVF) Outcome AI-IVF Study

Institute of Hospitalization and Scientific Care (IRCCS)

Status

Enrolling

Conditions

Autoimmune Diseases

Study type

Observational

Funder types

Other

Identifiers

NCT06872294

AI-IVF

Details and patient eligibility

About

Infertility is the failure to achieve a clinical pregnancy after 12 months or more of regular unprotected intercourse, while subfertility means a delay in achieving pregnancy. Several factors can contribute to these conditions, such as autoimmune diseases like systemic thyroid and celiac diseases, rheumatoid arthritis, systemic lupus erythematosus, and endometriosis. Some of them may overlap, sharing a common immunological milieu.

In this scenario, medically ART can help women carry on pregnancies if they are in stable disease remission and receive adequate treatment. However, the number of oocytes that can be ovulated under stimulation is highly variable, so the outcome of any IVF is linked to many factors, not only biological but also connected to the mean success rate of the fertility center.

For these reasons, the need to find methods for identifying the best gametes and embryos to guarantee a successful pregnancy is becoming pressing. AI can be essential to develop prediction models for pregnancy outcomes for patients undergoing ART treatments.

AI currently represents a modern way to obtain algorithms from a set of observable data that could help clinical decisions

Enrollment

200 estimated patients

Sex

Female

Ages

18 to 43 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

Women with age below 43 years old
IVF cycle with fresh semen sample that could be used
progressive motile spermatozoa expected count of minimum 1 million following density gradient purification on the day of oocyte pick up

Exclusion criteria