Do pregnancy rates differ with intra-uterine insemination when different combinations of semen analysis parameters are abnormal?

Longitudinal semen parameter assessments and live birth: variability and implications for treatment strategies

OBJECTIVE

To examine whether semen parameters are associated with live birth among couples seeking infertility treatment after accounting for semen parameter variability.

DESIGN

Folic Acid and Zinc Supplementation Trial (FAZST) prospective cohort.

SETTING

Four US reproductive endocrinology and infertility care study centers, 2013-2017.

PATIENT(S)

Couples (n = 2,369) seeking fertility consultations at 4 US infertility care study centers.

INTERVENTION(S)

Semen volume, pH, sperm viability, morphology, progressive and total motility, concentration, count, and total and progressive motile count assessed at baseline and at 2, 4, and 6 months after enrollment.

MAIN OUTCOME MEASURE(S)

Log-binomial models stratified by fertility treatment received (in vitro fertilization [IVF], intrauterine insemination [IUI], ovulation induction [OI], or no treatment) estimated risk differences (RDs) between semen parameter quartiles and live birth and accounted for multiple semen assessments per person. We accounted for abstinence time, the biological interdependence of semen parameters, and potential selection bias because of loss to follow-up.

RESULT(S)

Among couples using OI only or no treatment, 39% had a live birth, and relative to the highest quartile, the lowest quartiles of morphology (RD, -19 [95% CI, -23 to -15] per 100 couples), motility (RD, -13 [95% CI, -17 to -9]), concentration (RD, -22 [95% CI, -26 to -19]), and total motile count (RD, -18 [95% CI, -22 to -14]) were associated with fewer live births. For IUI, 26% had a live birth, and the lowest quartiles of volume (RD, -6 [95% CI, -11 to -0.4]), concentration (RD, -6 [95% CI, -11 to -0.1]), count (RD, -10 [95% CI, -15 to -4]), and total motile count (RD, -7 [95% CI, -13 to -1]) were associated with fewer live births. For IVF, 61% had a live birth, and only morphology (Q1 RD, -7 [95% CI, -14 to 0.2]; Q2 RD, -10 [95% CI, -17 to -2.2]) was associated with live birth.

CONCLUSION(S)

Semen parameters are critical in couples undergoing OI/IUI. Only low morphology was important for live birth after IVF. Although data supporting the use of semen parameters are fragmented across differing populations, current findings are generalizable across the range of male fertility and couple fertility treatments, providing evidence about which semen parameters are most relevant in which settings.

CLINICAL TRIAL REGISTRATION NUMBER

NCT#01857310.

Evaluation of selected semen parameters and biomarkers of male infertility - preliminary study

Background: Because the etiopathogenesis of male infertility is multifactorial our study was designed to clarify the relationship between standard semen parameters, testicular volume, levels of reproductive hormones and the fragmentation of sperm nuclear DNA (SDF). Methods: Patients (n = 130) were clustered as subjects: 1) with an abnormal volume (utrasonography) of at least one testis (<12 mL) or with a normal volume of testes and 2) with abnormal levels of at least one of the reproductive hormones (FSH, LH, PRL, TSH, total T - electrochemiluminescence method) or with normal hormonal profiles and 3) with high level of SDF (>30%), moderate (>15-30%) or low (≤15%) (sperm chromatin dispersion test). Results: In subjects with a decreased testicular volume and in subjects with abnormal levels of reproductive hormones, decreased basic semen parameters were found. Participants with abnormal testicular volume had a higher percentage of SDF and a higher level of FSH (Mann-Whitney U test). In turn, men with a high level of SDF had lower testicular volume and conventional sperm parameters than men with a low level of SDF (Kruskal-Wallis test). Conclusions: We showed that spermatogenesis disorders coexisted with decreased testicular volume and increased FSH levels. The disorders of spermatogenesis were manifested by reduced basic sperm characteristics and a high level of sperm nuclear DNA damage.

CNFE-SE: a novel approach combining complex network-based feature engineering and stacked ensemble to predict the success of intrauterine insemination and ranking the features

Background

Intrauterine Insemination (IUI) outcome prediction is a challenging issue which the assisted reproductive technology (ART) practitioners are dealing with. Predicting the success or failure of IUI based on the couples' features can assist the physicians to make the appropriate decision for suggesting IUI to the couples or not and/or continuing the treatment or not for them. Many previous studies have been focused on predicting the in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) outcome using machine learning algorithms. But, to the best of our knowledge, a few studies have been focused on predicting the outcome of IUI. The main aim of this study is to propose an automatic classification and feature scoring method to predict intrauterine insemination (IUI) outcome and ranking the most significant features.

Methods

For this purpose, a novel approach combining complex network-based feature engineering and stacked ensemble (CNFE-SE) is proposed. Three complex networks are extracted considering the patients' data similarities. The feature engineering step is performed on the complex networks. The original feature set and/or the features engineered are fed to the proposed stacked ensemble to classify and predict IUI outcome for couples per IUI treatment cycle. Our study is a retrospective study of a 5-year couples' data undergoing IUI. Data is collected from Reproductive Biomedicine Research Center, Royan Institute describing 11,255 IUI treatment cycles for 8,360 couples. Our dataset includes the couples' demographic characteristics, historical data about the patients' diseases, the clinical diagnosis, the treatment plans and the prescribed drugs during the cycles, semen quality, laboratory tests and the clinical pregnancy outcome.

Results

Experimental results show that the proposed method outperforms the compared methods with Area under receiver operating characteristics curve (AUC) of 0.84 ± 0.01, sensitivity of 0.79 ± 0.01, specificity of 0.91 ± 0.01, and accuracy of 0.85 ± 0.01 for the prediction of IUI outcome.

Conclusions

The most important predictors for predicting IUI outcome are semen parameters (sperm motility and concentration) as well as female body mass index (BMI).

Associated factors to pregnancy in intrauterine insemination

Objective

To define the factors associated with clinical pregnancy after intrauterine insemination.

Methods

Retrospective study involving 633 infertility couples, which made up to 1053 cycles of intrauterine insemination. We analyzed the clinical pregnancy rate associated with different factors through the Chi-square test or Fisher's exact test.

Results

The clinical pregnancy rate was 8.2% per insemination cycle and 13.6% per treated couple. The factors with greater association to clinical pregnancy were to have more than two follicles, to perform the procedure without difficulty, to have 3 years or less of infertility, cervical factor as indication, use of gonadotropins and age less than 38 years.

Conclusion

Intrauterine insemination requires to be accompanied by proper selection and couples' preparation.