ArticleFrontiers in endocrinology2021
Development and Validation of a Clinical Pregnancy Failure Prediction Model for Poor Ovarian Responders During IVF/ICSI.
Article in Frontiers in endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- TransrectalFrontiers in medicine · 2026Article
- Breaking barriers in male infertility: the power of artificial intelligence-driven solutions.Frontiers in urology · 2026Review
- Effect of body mass index on pregnancy outcomes in young women with low-prognosis POSEIDON criteria after in vitro fertilization/intracytoplasmic sperm injection.Journal of ovarian research · 2025Article
- Introducing artificial intelligence and sperm epigenetics in the fertility clinic: a novel foundation for diagnostics and prediction modelling.Frontiers in reproductive health · 2025Article
- Comparative efficacy of r-hFSH Alfa + r-LH versus r-hFSH delta + hMG in poor ovarian responders.Frontiers in endocrinology · 2025Article
- Artificial Intelligence, Clinical Decision Support Algorithms, Mathematical Models, Calculators Applications in Infertility: Systematic Review and Hands-On Digital Applications.Mayo Clinic proceedings. Digital health · 2024Review
- Article
- Development and validation of a live birth prediction model for expected poor ovarian response patients during IVF/ICSI.Frontiers in endocrinology · 2023Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Backgrounds: Despite the great advances in assisted reproductive technology (ART), poor ovarian response (POR) is still one of the most challenging tasks in reproductive medicine. This predictive model we developed aims to predict the individual probability of clinical pregnancy failure for poor ovarian responders (PORs) under Methods: The nomogram was developed in 281 patients with POR according to the Bologna criteria from January 2016 to December 2019, with 179 in the training group and 102 in the validation group. Univariate and multivariate logistic regression analyses were used to identify characteristics that were associated with clinical pregnancy failure. The nomogram was constructed based on regression coefficients. Performance was evaluated using both calibration and discrimination. Results: Age >35 years, body mass index (BMI) >24 kg/m Conclusion: Our nomogram can predict the probability of clinical pregnancy failure in PORs before embryo transfer in IVF/ICSI procedure, to help practitioners make appropriate clinical decisions and to help infertile couples manage their expectations.
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