ArticleHeliyon2024
Multivariate analyses on male factors and construction of a nomogram for predicting low in vitro fertilization rate.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- LOW FERTILIZATION: statistical definition and clinical relevance.Journal of assisted reproduction and genetics · 2025Article
- Associations between serum 25- hydroxyvitamin D concentrations and assisted reproductive technology outcomes in women with polycystic ovary syndrome: a cohort study.Frontiers in endocrinology · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Low fertilization rate (LFR) and total fertilization failure (TFF) are often encountered in routine in vitro fertilization (IVF) procedure. To solve this problem, multivariate analyses on the relationship between male factors and in vitro fertilization rate were performed, and a nomogram for prediction of LFR was constructed. This retrospective study contained 2011 couples who received IVF treatment from January 2017 to December 2021. Man factors and in vitro fertilization rate were collected. Among these couples, 1347 cases had in vitro fertilization rates ≥30 % (control group), and 664 cases had in vitro fertilization rates <30 % (LFR group). Univariate analyses of male factors found that between the two groups there were significant differences (p < 0.05) in sperm progressive motility (SPR), sperm concentration (SC), total sperm number, normal sperm morphology rate (NSMR), DNA fragmentation index (DFI), sperm acrosin activity (SAA) and the clinical diagnosis of primary or secondary infertility. Multivariate logistic regression analyses showed that SPR, SAA, and SC were independent risk factors for LFR. An algorithm and a correspondent nomogram for predicting high LFR risk were constructed using data from the training cohort. The LFR nomogram exhibited an excellent discrimination power and a high fitting degree in both the training cohort (AUC = 0.90, 95 % CI: 0.88-0.92), (H-L: x
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