ArticleJBRA assisted reproduction2021
Prediction of ovarian response in IVF/ICSI cycles.
Article in JBRA assisted reproduction, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- An explainable machine learning model for identifying the risk of suboptimal oocyte maturation in patients with polycystic ovary syndrome undergoing GnRH-antagonist protocol.Journal of ovarian research · 2026Article
- Predicting factors of ovarian responses in infertile women with polycystic ovary syndrome undergoing IVF/ICSI.Journal of assisted reproduction and genetics · 2025Article
- Progesterone levels on hCG day and oocyte maturation in a Mexican IVF program.JBRA assisted reproduction · 2024Observational
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveOur 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.
methodsThis 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).
resultsA 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).
conclusionsWe 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.
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