ArticleFrontiers in endocrinology2022
Prediction of Fertilization Disorders in the
Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 18 citations in OpenAlex.
- Nomogram models to predict low fertilisation rate and total fertilisation failure in patients undergoing conventional IVF cycles.BMJ open · 2022Trial
- ICSI shows no advantage over conventional IVF in patients with unexpected low oocyte yield.Annals of medicine · 2026Article
- Exploring the related factors of fertilization failure in in-vitro fertilization-embryo transfer.Pakistan journal of medical sciences · 2026Article
- Influencing factors of fertilization failure duringFrontiers in endocrinology · 2026Article
- AMH as a Predictor of Follicle Turnover, Embryo Quality, and Pregnancy Outcomes: A Retrospective Analysis.Biomedicines · 2025Article
- Effect of early rescue ICSI in multiple cycles of couples with successful fertilization in the initial cycle of conventional IVF.Journal of ovarian research · 2025Article
- Intracytoplasmic sperm injection hampers fertilization rate and pregnancy per initiated cycle in patients with extremely poor ovarian response.Archives of gynecology and obstetrics · 2025Article
- The clinical value of short-term insemination: a retrospective analysis of 3496 patients.BMC pregnancy and childbirth · 2025Article
- Commentary: Comparison of conventional ICSI and rescue ICSI in patients without severe male factor and poor oocyte yield.Frontiers in endocrinology · 2025Article
- Automatic identification of human spermatozoa with zona pellucida-binding capability using deep learning.Human reproduction open · 2025Article
- Comparison of conventional ICSI and rescue ICSI in patients without severe male factor and poor oocyte yield.Frontiers in endocrinology · 2025Article
- Indications affect neonatal outcomes following early rescue ICSI: a retrospective study.Journal of assisted reproduction and genetics · 2024Article
- A Bayesian network model for prediction of low or failed fertilization in assisted reproductive technology based on a large clinical real-world data.Reproductive biology and endocrinology : RB&E · 2023Article
- Predicting the unexpected total fertilization failure in conventionalFrontiers in cell and developmental biology · 2023Article
- Opportunities and Limits of Conventional IVF versus ICSI: It Is Time to Come off the Fence.Journal of clinical medicine · 2022Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aimed to develop a risk prediction of fertilization disorders during the Methods: A retrospective study was performed with 106,728 fresh embryo IVF/ICSI cycles from 2009 to 2019. Basic characteristics of patients, clinical treatment data, and laboratory parameters were involved. The associations between the selected variables and risks for low fertilization rate (LFR) and total fertilization failure (TFF) were investigated. Ordinal logistic regression and the receiver operating characteristic curves (ROCs) were used to construct and evaluate the prediction models. Results: A total of 97,181 controls, 4,343 LFR and 5,204 TFF cases were involved in this study. The model based on clinical characteristics (the ages of the couples, women's BMI, types of infertility, ART failure history, the diminished ovarian reserve, sperm quality, insemination method, and the number of oocytes retrieved) had an AUC of 0.743 for TFF. The laboratory model showed that primary infertility, ART failure history, minimal-stimulation cycle/natural cycle, numbers of oocyte retrieved < 5, IVF, and Anti-Mullerian hormone (AMH) level < 1.1ng/ml are predictors of TFF, with an AUC of 0.742. Conclusion: We established a clinical and a laboratory prediction model for LFR/TFF. Both of the models showed relatively high AUCs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.