EFFECTS OF SEMEN CHARACTERISTICS ON IUI COMBINED WITH MILD OVARIAN STIMULATION

Comparison of RNA content from hydrophobic interaction chromatography-isolated seminal plasma exosomes from intrauterine insemination (IUI) pregnancies

Male factors account for roughly half of infertility cases, with most male infertility diagnosed as idiopathic. Researchers predicting intrauterine insemination success rates have identified multiple prognostic factors, including semen parameters and seminal fluid composition. Seminal plasma contains extracellular exosomes, which contain RNAs and proteins involved in spermatogenesis. The contents of seminal plasma exosomes may be an indicator of overall sperm quality or fertility potential; therefore, analysis of exosomes may provide a measure for sperm viability and fertilization potential. In our study, exosomes were isolated and purified from seminal plasma obtained from IUI treatments with known pregnancy outcomes. We used a unique method to isolate the exosomes which made use of the hydrophobic interaction chromatography method. RNASeq was performed on RNAs from the purified exosomes. This analysis revealed holistic trends, including increased expression associated with RNA originating from chromosomes 1, 10, 12, 16 and 21. Overall, total RNA was significantly decreased and rRNA was significantly increased in successful IUI attempts. Furthermore, we found specific mRNAs and lincRNAs associated with positive versus negative pregnancy outcomes. Our study isolated and purified seminal plasma exosomes without ultracentrifugation, and it provides further evidence for differences in seminal plasma exosome molecular contents associated with pregnancy status.

Predictive value of sperm motility before and after preparation for the pregnancy outcomes of intrauterine insemination

Objective

This study aimed to investigate sperm motility and its changes after preparation as predictors of pregnancy in intrauterine insemination (IUI) cycles.

Methods

In total, 297 IUI cycles from January 2012 to December 2017 at a single tertiary hospital were retrospectively analyzed. Patient and cycle characteristics, and sperm motility characteristics before and after processing were compared according to clinical pregnancy or live birth as outcomes.

Results

The overall clinical pregnancy rate per cycle was 14.5% (43/297) and the live birth rate was 10.4% (30/289). Patient and cycle characteristics were similar between pregnant and non-pregnant groups. Sperm motility after preparation and the total motile sperm count before and after processing were comparable in terms of pregnancy outcomes. Pre-preparation sperm motility was significantly higher in groups with clinical pregnancy and live birth than in cycles not resulting in pregnancy (71.4%±10.9% vs. 67.2%±11.7%, p=0.020 and 71.6%±12.6% vs. 67.3%±11.7%, p=0.030, respectively). The change in sperm motility after processing was significantly fewer in the non-pregnant cycles, both when the comparison was conducted by subtraction (post-pre) and division (post/pre). These relationships remained significant after adjusting for the female partner’s age, anti-Müllerian hormone level, and number of pre-ovulatory follicles. According to a receiver operating characteristic curve analysis, an initial sperm motility of ≥72.5% was the optimal threshold value for predicting live birth after IUI.

Conclusion

Initial sperm motility, rather than the motility of processed sperm or the degree of change after preparation, predicted live birth after IUI procedures.

Factors Affecting Artificial Insemination Pregnancy Outcome

Objective

The aim of the present study was to explore related clinical pregnancy outcome factors in intrauterine insemination (IUI).

Materials and Methods

The clinical data of 3984 IUI cycles in 1862 couples experiencing infertility who attended the Reproductive Center of Binzhou Medical University Hospital between July 2006 and July 2017 were retrospectively analyzed. Female and male patient age, endometrial thickness (EMT), the post-wash total motile sperm count (PTMC), artificial insemination timing, insemination frequency, and ovarian stimulation protocols were compared between the study’s pregnant group and non-pregnant group in order to explore any correlation.

Results

There were statistically significant differences in female and male age, EMT, artificial insemination timing, insemination frequency, and ovarian stimulation protocols between the two groups (p < 0.05). The clinical pregnancy rate was significantly higher in ovarian stimulation cycles than in natural cycles (21.2% and 11.6%, respectively; p < 0.01), the clinical pregnancy rate was significantly higher in double IUI than in single IUI (17.8% and 12.1%, respectively; p < 0.01), and EMT was significantly greater in the pregnant group than in the control group (p < 0.05). However, the differences in clinical pregnancy rates among the PTMC groups were not statistically significant (14.8%, 14.4%, 17.3%, and 17.3%, respectively; p > 0.05).

Conclusion

The results of the present study demonstrate that the clinical IUI pregnancy rate is correlated with the factors of female age, male age, EMT, artificial insemination timing, insemination frequency, and ovarian stimulation protocols; the ovarian stimulation protocol can noticeably improve the patient pregnancy outcome. Furthermore, compared with single IUI, double IUI can significantly increase the clinical pregnancy rate.

Relationship between sperm parameters and clinical outcomes of Intra Uterine Insemination (IUI)

Background:

Intrauterine insemination (IUI) is a widely utilized method for treating the infertile couples. The aim of the present study was to determine the pregnancy and abortion rates after IUI and to examine the relationship of sperm parameters with these rates.

Methods:

This retrospective study was performed on 911 infertile couples undergoing IUI treatment in Shahid Akbarabadi IVF Centre from May 2017 to May 2019. To evaluate the correlation of sperm parameters with the clinical pregnancy and abortion rates, odds ratio (OR) with 95% confidence intervals (CI) was calculated.

Results:

In this study, the pregnancy rate following IUI was 15.7% (143/911), and among women who achieved pregnancy, the abortion rate was 42.0% (60/143). According to the multiple logistic regression analysis, none of the sperm parameters was associated with the pregnancy rate. Couples with either male or female factor infertility etiologies were more likely to get pregnant than those with unexplained infertility. Regarding the abortion rate, multiple logistic regression analysis revealed that normal sperm count was related to a lower abortion rate (adjusted OR=0.25, 95% CI=0.07–0.91).

Conclusion:

The present study did not reveal a significant relationship between none of the sperm parameters and pregnancy rate after IUI treatment. However, among women who got pregnant, continuation of the pregnancy was associated with the normal sperm count. Furthermore, analysis of all semen parameters together in comparison to one parameter alone might be more accurate to predict pregnancy or abortion. Further prospective cohort studies with a large number of couples are required.

Pregnancy rates with intrauterine insemination: comparing 1999 and 2010 World Health Organization semen analysis norms

Over the past 30 years, The World Health Organization has serially measured norms for human sperm. In this study, 1999 and 2010 semen analysis norms as predictors of pregnancy were compared during intrauterine insemination (IUI). A retrospective cohort study was conducted using data collected from the Stanford Fertility Center, between 2005 and 2007, with 981 couples undergoing 2231 IUI cycles. Collected semen was categorized according to total motile sperm counts (TMSC): 'normal (N.) 1999 TMSC', 'abnormal (AbN.) 1999/N. 2010 TMSC', or 'AbN. 2010 TMSC'. Sample comparison was also based on individual semen parameters: 'N. 1999 WHO', 'AbN. 1999/N. 2010 WHO', or 'AbN. 2010 WHO'. Pregnancy (defined by beta-HCG concentration) rates were calculated. Data were compared using correlation coefficients, t-tests and chi-squared tests, with and without adjusting for confounders. Pregnancy rate comparison based on TMSC ('N. 1999 TMSC', 'AbN. 1999/N. 2010 TMSC' and 'AbN. 2010 TMSC') showed a negative correlation (r = -0.41, P = 0.05). Pregnancy rate did not differ when comparisons were based on the presence of abnormal parameters, even when controlling for confounders. Therefore, TMSC based on the 1999 parameters shows best correlation with pregnancy rate for IUI; updating these norms in 2010 has little clinical implication in infertile populations.

Semen quality and prediction of IUI success in male subfertility: a systematic review

Many variables may influence success rates after intrauterine insemination (IUI), including sperm quality in the native and washed semen sample. A literature search was performed to investigate the threshold levels of sperm parameters above which IUI pregnancy outcome is significantly improved and/or the cut-off values reaching substantial discriminative performance in an IUI programme. A search of MEDLINE, EMBASE and Cochrane Library revealed a total of 983 papers. Only 55 studies (5.6%) fulfilled the inclusion criteria and these papers were analysed. Sperm parameters most frequently examined were: (i) inseminating motile count after washing: cut-off value between 0.8 and 5 million; (ii) sperm morphology using strict criteria: cut-off value ⩾5% normal morphology; (iii) total motile sperm count in the native sperm sample: cut-off value of 5-10 million; and (iv) total motility in the native sperm sample: threshold value of 30%. The results indicate a lack of prospective studies, a lack of standardization in semen testing methodology and a huge heterogeneity of patient groups and IUI treatment strategies. More prospective cohort trials and prospective randomized trials investigating the predictive value of semen parameters on IUI outcome are urgently needed. It is generally believed that intrauterine insemination (IUI) with homologous semen should be a first-choice treatment to more invasive and expensive techniques of assisted reproduction in cases of cervical, unexplained and moderate male factor subfertility. The rationale for the use of artificial insemination is to increase gamete density at the site of fertilization. Scientific validation of this strategy is difficult because literature is rather confusing and inconclusive. Many variables may influence success rates after IUI treatment procedures. It seems logical that sperm quality has to be one of the main determinants to predict IUI success. Clinical practice would benefit from the establishment of threshold levels for sperm parameters above which IUI pregnancy outcome is significantly improved and below which a successful outcome is unlikely. We performed a literature search to investigate if such threshold levels are known. Most striking were the lack of standardization in semen-testing methodology and the huge heterogeneity of patient groups and IUI treatment strategies. The four sperm parameters most frequently examined were: (i) inseminating motile count after washing: cut-off value between 0.8 and 5 million; (ii) sperm morphology using strict criteria: cut-off value >4% normal morphology; (iii) total motile sperm count in native sperm sample: cut-off value of 5-10 million; and (iv) total motility in native sperm sample: threshold value of 30%. This review identified an urgent need for more and better prospective cohort trials investigating the predictive value of semen parameters on IUI pregnancy rate.