AbstractObjective: To explore the influencing factors of fertilization failure (FF) during in vitro fertilization (IVF) to prevent and manage it in clinical practice and improve treatment efficiency. Methods: IVF cycles were included and grouped according to the fertilization rate. There were 75 cycles with a fertilization rate of 0, i.e., complete FF, and 98 cycles with a fertilization rate of <30%, i.e., partial FF, and these cycles were included in the FF group; and there were 2301 cycles with a fertilization rate of ≥30%, and included in the normal fertilization(NF) group. Sperm quality of males, basic conditions of females, clinical ovulation induction and laboratory fertilization were compared between the two groups, and no differences were observed. Multivariate logistic regression analysis was performed using FF in the IVF process as the dependent variable, and the indicators with statistically significant differences in the univariate analysis as independent variables to screen the independent risk factors for FF in IVF. Results: There were significant differences in female age, infertile duration, initial dose of Gn, Gn dose/egg, sperm concentration before treatment, sperm motility, percentage of normal sperm morphology, sperm concentration after treatment, and fertilization concentration(10,000 sperms/ml), and the differences were statistically significant(all P<0.05). Multivariate logistic regression analysis showed that a high percentage of primary infertility, a low percentage of tubal factors, a low percentage of normal sperm morphology, and low sperm concentration after treatment were independent risk factors for FF, and the differences were statistically significant (all P<0.05). Logistic binary regression fitting was used to construct a ROC curve prediction model for combined prediction of fertilization failure using various indicators, and the AUC was 74.6%. Conclusion: A high percentage of primary infertility, a low percentage of tubal factors, a low percentage of normal sperm morphology, and low sperm concentration after treatment are independent risk factors for FF. The ROC curve model using combined indicators to predict FF constructed by logistic binary regression fitting is valuable in FF prediction.
Objective: To explore the influencing factors of polyspermy in long-term fertilization during in vitro fertilization (IVF) with antagonist protocol. Methods: This was a retrospective case-control study. Patients with secondary infertility undergoing assisted reproductive treatment in the Department of Reproductive Medicine of Maternity & Child Care Center of Qinhuangdao between January 2020 and May 2023 were selected. Five hundred and thirty-six ovulation induction cycles with antagonist protocol were included and divided into the control group (multiple pronuclei(PN) rate= 0%, n=347) and the polyspermy group (multiple PN: 2PN ≥20%, n=189) according to the incidence of polyspermy. The general data and embryonic development of the two groups were statistically analyzed. Results: There were no statistically significant differences in male age, infertile duration, body mass index (BMI), basal follicle-stimulating hormone (FSH) level, number of follicles with a diameter of ≥16mm, total dose of gonadotropin (Gn), total Gn stimulation days, and sperm concentration between the two groups (all P>0.05). Similarily no statistically significant differences in female age, levels of estradiol (E2), LH, and progesterone (P) and number of follicles with a diameter of ≥14 mm on human chorionic gonadotropin (hCG) injection day, the total number of eggs retrieved, amount of Gn/egg, and fertilization concentration (sperms/egg) were observed between the two groups (all P<0.05). The results of logistic binary regression analysis showed that the level of LH on hCG injection day was an independent risk factor for the incidence of polyspermy in antagonist protocol. Conclusion: In the process of ovulation induction in antagonist protocol, the appropriate addition of LH can improve embryo outcomes. doi: https://doi.org/10.12669/pjms.41.2.9832 How to cite this: Shi H, Song Q, Liu J, Li C, Liu R. Influencing factors of polyspermy during in vitro fertilization with antagonist protocol. Pak J Med Sci. 2025;41(2):575-579. doi: https://doi.org/10.12669/pjms.41.2.9832 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)