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A Diagnostic Model to Improve the Predictability of Natural Pregnancy Potential in Patients with Oligoasthenospermia

BACKGROUND: Oligoasthenospermia is one of the major reasons for male infertility in clinical practice. Nevertheless, some patients with oligoasthenospermia show normal fertility. Currently, there is a lack of an effective method to distinguish patients with oligoasthenospermia showing normal fertili...

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Detalles Bibliográficos
Autores principales: Zhang, Tiancheng, Wang, Xin, Wang, Zhikai, Xu, Zhiming, Chen, Liang, Miao, Maohua, Wu, Bin, Wang, Xuemei, Shen, Xiaorong, Wu, Jun, Wang, Ke, Shi, Huijuan, Li, Jianhui, Zheng, Jufen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7491230/
https://www.ncbi.nlm.nih.gov/pubmed/32890392
http://dx.doi.org/10.12659/MSM.922316
Descripción
Sumario:BACKGROUND: Oligoasthenospermia is one of the major reasons for male infertility in clinical practice. Nevertheless, some patients with oligoasthenospermia show normal fertility. Currently, there is a lack of an effective method to distinguish patients with oligoasthenospermia showing normal fertility from those who lack natural fertility and should participate in in vitro fertilization and assisted reproduction. MATERIAL/METHODS: In this study, we collected semen and blood samples from 153 males of Shui nationality at reproductive age in Guizhou Province, southwest China. We measured the routine parameters for semen and some serological indicators. A clinical diagnosis model was then constructed to evaluate the fertility potential of oligoasthenospermia patients using a logistic stepwise regression method, which was then visualized with a nomogram. RESULTS: Our results showed that this model could effectively assess the natural pregnancy potential of patients with oligoasthenospermia, and its sensitivity and specificity were superior to those of a traditional model that used only sperm motility and count to assess male fertility potential (area under the curve=0.7626 vs. 0.6677). Additionally, we evaluated the clinical net benefit for patients with oligoasthenospermia at different risk scores in our model using decision curve analysis. The results showed that the net benefit was obtained at scores ranging from 0.1 to 0.6. CONCLUSIONS: This comprehensive clinical prediction model can be used to determine whether infertile oligoasthenospermia patients lack natural fertility.