ArticleFrontiers in endocrinology2021
The Development of Nomograms to Predict Blastulation Rate Following Cycles of
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 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Progress of the application clinical prediction model in polycystic ovary syndrome.Journal of ovarian research · 2023Pooled it
- Review
- Nomograms based on clinical factors to predict abnormal metabolism of psychotropic drugs.Biomedical reports · 2025Article
- The Role of Artificial Intelligence in Female Infertility Diagnosis: An Update.Journal of clinical medicine · 2025Review
- A cycle-based model to predict no usable blastocyst formation following cycles of in vitro fertilization in patients with normal ovarian reserve.Reproductive biology and endocrinology : RB&E · 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
- [Establishment of a predictive nomogram for clinical pregnancy rate in patients with endometriosis undergoing fresh embryo transfer].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Embryo Cryopreservation in a Patient with Sickle Cell Disease Utilizing Letrozole and Enoxaparin: A Case Report.Hematology reports · 2023Article
- Nomogram for predicting the risk of preterm delivery after IVF/ICSI treatment: an analysis of 11513 singleton births.Frontiers in endocrinology · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is well known that the transfer of embryos at the blastocyst stage is superior to the transfer of embryos at the cleavage stage in many respects. However, the rate of blastocyst formation remains low in clinical practice. To reduce the possibility of wasting embryos and to accurately predict the possibility of blastocyst formation, we constructed a nomogram based on range of clinical characteristics to predict blastocyst formation rates in patients with different types of infertility. We divided patients into three groups based on female etiology: a tubal factor group, a polycystic ovary syndrome group, and an endometriosis group. Multiple logistic regression was used to analyze the relationship between patient characteristics and blastocyst formation. Each group of patients was divided into a training set and a validation set. The training set was used to construct the nomogram, while the validation set was used to test the performance of the model by using discrimination and calibration. The area under the curve (AUC) for the three groups indicated that the models performed fairly and that calibration was acceptable in each model.
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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 OpenQuestion graph.