ArticleJournal of assisted reproduction and genetics2023
Development and validation of a conventional in vitro total fertilization failure prediction model.
Article in Journal of assisted reproduction and genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 3 citations in OpenAlex.
- Exploring the related factors of fertilization failure in in-vitro fertilization-embryo transfer.Pakistan journal of medical sciences · 2026Article
- Development of a single-center predictive model for conventional in vitro fertilization outcomes excluding total fertilization failure: implications for protocol selection.Journal of ovarian research · 2025Article
- Comparison of conventional ICSI and rescue ICSI in patients without severe male factor and poor oocyte yield.Frontiers in endocrinology · 2025Article
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Authors and funding
7 authors at 1 institution in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundConventional total fertilization failure (TFF) is a challenging problem for clinicians. The predictive model developed in this study aims to predict the individual probability of conventional in vitro total fertilization failure.
methodsThe prediction model was developed based on 1635 patients who underwent first-attempt in vitro fertilization (IVF) cycles from January 2018 to January 2020. Total fertilization failure and normal fertilization occurred in 218 and 1417 cycles, respectively. Multivariate logistic regression analyses were used to develop the prediction model. Performance of our model was evaluated using calibration (Hosmer-Lemeshow test) and discrimination (area under the receiver operating characteristic curve [AUC]).
resultsThirteen risk factors for TFF were included in the prediction model, as follows: female age; female body mass index; infertility duration; number of oocytes retrieved; stimulation protocol; infertility etiology; infertility diagnosis; male age; sperm concentration; total sperm motility; normal sperm morphology percentage; swim-up sperm motility; and swim-up sperm concentration. The AUC of our model was 0.815 (95% CI: 0.783-0.846), indicating satisfactory discrimination performance.
conclusionConsidering female and male factors (especially sperm parameters), we established a model that predicts the probability of TFF in conventional IVF procedures that will be helpful in the laboratory supporting IVF to facilitate physicians in determining optimal treatment.
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