ArticleTranslational pediatrics2022
Predicting the probability of a live birth after a freeze-all based in vitro fertilization-embryo transfer (IVF-ET) treatment strategy.
Article in Translational pediatrics, 2022. 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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Who cites it
3 citing papers in PubMed, 13 citations in OpenAlex.
- Interpretable machine learning prediction of live birth after freeze-all FET cycles across transfer-order subgroups.Frontiers in endocrinology · 2026Article
- Predicting personalized cumulative live birth rate after a complete in vitro fertilization cycle: an analysis of 32,306 treatment cycles in China.Reproductive biology and endocrinology : RB&E · 2024Article
- Construction of the machine learning-based live birth prediction models for the first in vitro fertilization pregnant women.BMC pregnancy and childbirth · 2023Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The predictors for live birth rate (LBR) following one episode of in vitro fertilization (IVF) cycle for patients using a "freeze-all" strategy are not entirely clear. Methods: A retrospective cohort study utilizing a prediction model was developed to assess the relationship to the LBR. Women undergoing IVF with a freeze-all strategy were screened. Univariate models were first fitted for female age at oocytes retrieval/frozen-thawed embryo transfer (FET), body mass index (BMI), duration and etiology of infertility, previous IVF failures, total dose and duration of gonadotrophin, ovarian sensitivity index (OSI), number of oocytes collected, method of fertilization, number of embryos created, number and stage of embryos frozen, type and number of FET cycles, endometrial thickness (EMT)/pattern, hormone level on transplantation day, storage duration, number of embryos thawed and damaged thawed embryos, number and stage of embryos transferred and number of different quality embryos transferred. Variables with P<0.05 in the univariate model were selected for further analysis of the final multivariate discrete-time logistic regression model. Results: A total of 7,602 women undergoing one ovarian stimulation resulted in 9,964 FETs, of whom 3,066 (40.33%) had a live-birth after their first FET and 3,929 (51.68%) after total FETs. The EMT and woman's age at oocyte retrieval were the most important predictors. In the first FET, the LBR of women with an EMT ≤8 mm [27.40%; 95% confidence interval (CI): (21.60-33.81%)] was significantly lower than that of women with EMT between 9 and 11 mm [36.51%; 95% CI: (34.25-38.81%)] and thicker than 12 mm [44.23%; 95% CI: (42.22-46.25%)] (P<0.05). The optimistic and conservative cumulative LBRs of women younger than 31 years [87.5%; 95% CI: (86.32-88.61%) and 63.04%; 95% CI: (61.36-64.69%)] were significantly decreased in women aged 31-35, 36-40 and >40 (P<0.001). Conclusions: Our study provides an effective prediction model for a woman's chance of having a baby after a "freeze-all" policy. The use of EMT and female age as tools to identify LBR are shown to be justified, and repeated FETs cannot reverse the age-dependent decline in fertility.
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