In vitro fertilization (IVF) success involves ovarian stimulation with conventional or mild stimulation protocols aimed to yield an adequate number of mature oocytes. These oocytes can be further fertilized and generate good quality embryos to be transferred, ideally in the same cycle. Since 2013, following the results of a metaanalysis including more than 60,000 IVF cycles, the negative effects of premature progesterone elevation on reproductive outcomes have been demonstrated. Nowadays, evidence is emerging on the limited regulation on serum progesterone values, demonstrating significantly lower live birth rates in patients with either low (<0.5ng/ ml) late follicular phase progesterone or higher levels decreasing sharply. This review discusses and summarizes the different mechanisms of progesterone elevation and its impact on IVF treatments. Different approaches to diminish the impact of progesterone on fertility outcomes are also addressed.

Objective: Our study aims to evaluate the various correlations between demographic, biochemical, ultrasound, and ovarian stimulation parameters with the percentage of mature oocytes in conventional stimulation for IVF/ICSI cycles in order to develop a predictive model to improve our understanding of the oocyte maturation process.Methods: This is a retrospective cohort study; patients underwent conventional antagonist ovarian stimulation protocols for fresh IVF/ICSI cycles. A total of 256 IVF/ ICSI cycles were included. Age, antral follicle count (AFC), baseline serum follicle-stimulating hormone (FSH) levels, baseline serum luteinizing hormone (LH) levels, baseline serum estradiol (E2) levels, peak estradiol, P4 on hCG day, the body mass index (BMI), and stimulation length were measured. The variables were tested for correlations with the number of retrieved oocytes (#RO) and the number of mature oocytes (#MO). A backward stepwise regression was performed to identify the variables that correlated more strongly with percentage of mature oocytes (%MO).Results: A predictive equation was obtained with the variables that were not excluded in the model. % MO = 72.700 -0.910 (Age) + 0.979 (BMI) + 1.209 (Baseline serum LH) -0.647 (Progesterone on human Chorionic Gonadotropin day).Conclusions: We concluded that age, the BMI, baseline serum LH, and progesterone level on hCG day may predict %MO. Prospective studies are required to validate this predictive equation.