Clinical Pregnancy Rate in Intrauterine Insemination and Associated Prognostic Factors.

In the modern world, infertility is on a rising trend. Nearly 10%–15% of couples suffer from infertility. Among them, 20% of cases are caused by male factors, and 30%–40% are caused by both male and female factors. Tubo-peritoneal disease, cervical factor, ovulatory dysfunctions, endometriosis, and idiopathic causes are common causes of female infertility and unexplained infertility is also found in some infertile couples. One of the most commonly accepted Assisted Reproductive Techniques (ART) is intrauterine insemination (IUI).[ 1 ] A couple is typically diagnosed with infertility after trying to conceive for 1 year or after 6 months in the case of women over 35.[ 2 3 ] Subfertility is frequently treated with a combination of dietary adjustments, medical procedures, and assisted reproductive technologies. However, less invasive and more economical procedures like IUI have gained popularity due to the high cost of in vitro Fertilization.[ 4 ] IUI is frequently used in ART by couples who are having trouble getting pregnant in unexplainable infertility. This method entails timely injection of cleaned, ready sperm into the uterus ovulation.[ 5 6 ] Several factors work together to determine successful IUI. One of the key factors for infertility is the women’s age as fertility declines with increasing age, making conception more challenging. The semen quality significantly influences the success rate of IUI in terms of sperm count and motility, used in the cycle. The likelihood of conception can be lowered if the sperm quality is poor. The success rate of IUI can also be impacted by ovulatory function.[ 4 7 8 ] Insemination concerning ovulation is also crucial for success because doing so will increase the likelihood of conception. To choose the best course, studies will offer insightful information about the elements that contribute to successful IUI outcomes and assist couples undergoing this treatment in making clinical decisions of treatment for each couple and raising the success rates of IUI cycles, a thorough evaluation of these and other variables is required.[ 9 10 11 ] This study will offer insightful information about the elements that contribute to successful IUI outcomes and assist couples undergoing this treatment in making clinical decisions. This study aims to determine clinical pregnancy rate in infertile patients undergoing IUI concerning age of the patient, cause, duration and type of infertility, presence of dominant ovarian follicles, and sperm count.

The present study was done to investigate the rate of clinical pregnancy in IUI cycles at this center and their correlation with various prognostic factors among infertile women treated over a period from July 2022 to January 2024. In this prospective observational study, a total of 167 participants were included. The mean age of participants was 30.58 ± (SD) 4.43 years. Table 1 shows that pregnancy rate was 18.2% in the 45 years age group, no positive pregnancy was reported. Statistical analysis revealed no statistical significance in IUI and clinical pregnancy rates among the age categories ( P = 0.775). Relationship of age, BMI, physical activity, addiction of male and female partner USG=Ultrasonography, BMI=Body mass index Depicted in Table 2 results showed no significant association between BMI categories (underweight, normal weight, and overweight) and clinical pregnancy rates ( P = 0.292). Similarly, physical activity levels (active, moderate, sedentary) did not significantly affect pregnancy outcomes ( P = 0.708). Furthermore, the addiction status of either spouse (no addiction, alcohol, tobacco, cigarettes) did not show a significant impact on clinical pregnancy rates ( P = 0.837 for husband; P = 0.486 for wife). Relationship of type of infertility and etiology with clinical pregnancy rate USG=Ultrasonography The study analyzed the association between the type of infertility (primary or secondary) and clinical pregnancy rates in IUI cycles. Results revealed no significant difference in clinical pregnancy rates between couples with primary and secondary infertility ( P = 0.489), suggesting that whether the primary or secondary type of infertility, did not influence the success of IUI cycles in achieving pregnancy. For patients with apparently normal endometrium, successful pregnancy was found in 28 patients, indicating a more favorable outcome ( P = 0.646). For those with identified endometrial causes, 14 tested negative and 5 tested positive, suggesting a lower success rate than those with no specific endometrial issues ( P = 0.659). In the cervical cause, without any specific cause had 127 negative and 29 positive results, whereas cases with an identified cause showed 6 negative and 3 positive outcomes ( P = 0.513). Among the patients with no specific ovarian causes, 119 tested negative, and 31 tested positive for pregnancy, reflecting a relatively higher pregnancy rate. Conversely, in the group with identified ovarian causes, 14 tested negative and 2 tested positive, indicating a significantly lower success rate in achieving pregnancy, the relationship was not significant ( P = 0.654). Tubal causes showed 128 negative and 32 positive outcomes for confirmed cases, and 4 negative and 1 positive outcome for those without confirmed causes ( P = 0.9999). Other causes saw 92 negative and 23 positive outcomes when specific causes were identified, and 42 negative and 10 positive when no specific causes were noted ( P = 0.9999). Figure 1 outlines patients based on the presence of male factor infertility and post-wash sperm count, juxtaposed with their respective Ultrasonography (USG) outcomes for pregnancy in IUI cycles. Patients were categorized into groups based on the absence or presence of male factor infertility, including specific conditions such as azoospermia, donor sperm usage, and premature ejaculation. In addition, patients were classified based on post-wash sperm count, with a threshold set at <10 or ≥10 million sperm per ml. Within each category, the table showcases the number and percentage of patients testing negative or positive for pregnancy. Statistical analysis reveals a nonsignificant difference in clinical pregnancy rates between couples who have or does not have male factor infertility ( P = 0.148) and among different post-wash sperm count thresholds. Male factor and post wash sperm count in husband with clinical pregnancy rates. USG = Ultrasonography Figure 2 presents patients categorized by their anti-müllerian hormone (AMH) levels, along with corresponding ultrasound (USG) outcomes for pregnancy in IUI cycles. Patients were grouped based on AMH levels, with a <4 or ≥4 ng/ml threshold. Statistical analysis reveals a trend toward significance, though P value (0.088) is not reaching statistical significance, in pregnancy rates between patients with AMH levels <4 and ≥4 ng/ml. Anti-mullerian hormone with clinical rate of pregnancy. USG = Ultrasonography, AMH = Anti-Müllerian hormone Figure 3 presents patients stratified by HSG results, dominant follicle presence, and endometrial thickness, as per their corresponding ultrasound (USG) outcomes for pregnancy in IUI cycles. Patients were categorized based on whether their HSG results were normal or abnormal, the presence or absence of a dominant follicle, and their endometrial thickness (<8 mm or ≥8 mm). Statistical analysis indicates a statistically significant association between endometrial thickness and rate of clinical pregnancies ( P = 0.001). Hysterosalpingography results, dominant follicle presence, and endometrial thickness with clinical pregnancy rates

Overall, the findings of this study as well as others highlight the significance of thorough patient assessment and customized IUI procedures. To increase the likelihood of conception, follicular development monitoring and maintaining ideal endometrial thickness should take precedence. HSG is still a useful diagnostic technique for determining tubal patency, but the success of an IUI should not be predicted solely by its findings. These results support the use of a multifactorial approach to patient management in IUI to enhance clinical outcomes. Limitation of the study is that the small sample size. Multicentric study with larger sample size could have predicted outcome in better way. There are no conflicts of interest.

IUI is indicated for almost all categories of unexplained infertility with or without ovarian stimulation, especially for couples with minimal and mild endometriosis.[ 9 ] Jeong M et al . observed initial sperm motility of more than equal to 72.5% was the optimal threshold value for predicting live birth after IUI.[ 12 ] Infertility is a frequently found public health problem that needs assisted reproductive technology (ART) therapies and due to less invasive, cost-effective and affordable procedure, IUI is the first and most acceptable and popular method among the couples.[ 13 ] The findings of our study indicate a significant reduction in the incidence of pregnancy with aging. Specifically, among women under 30 and women between 30 and 45, positive ultrasound (USG) results were found in 18.2% and 21.3% of cases, respectively, while no pregnancies were found in those over 45. This is consistent with earlier studies showing how age affects fertility. Age has a substantial impact on pregnancy rates when using assisted reproductive technologies, such as IUI, according to Sahakyan et al .[ 14 ] Aging is associated with reduced egg quality and decreased ovarian reserve which necessitates inclusion of age factor in present study. According to our data, there appears to be a noteworthy pattern where women with BMIs over 24.9 have the highest positive USG rate 25.0%. This goes against the widely accepted theory that a high BMI has a detrimental effect on fertility. Higher body weight has been linked to an increased incidence of ovulatory infertility, according to Green et al .[ 15 ] Whynott et al .[ 16 ] reemphasizes the association of infertility with BMI. Nonetheless, obesity (BMI >30) is generally associated with poorer reproductive results; however, the association between BMI and pregnancy rates in IUI cycles can be complicated, as noted by several researchers.[ 17 18 ] Factors such as hormonal imbalances and metabolic disturbances may affect these outcomes differently, and it is possible that other confounding factors were at play in our study. Women who engaged in moderate physical activity had the greatest positive USG confirmed pregnancy rate (21.7%), whereas women who were sedentary had the lowest rate (13.6%), according to this study. This result confirms previous research that suggests moderate physical activity has a positive impact on fertility. Frequent exercise has been linked to better metabolic and hormonal health, which can improve the results of conception.[ 18 ] The benefits of moderate exercise are consistent with study conducted by Sicchieri et al .[ 5 ] who found that physical health was a strong predictor of success with IUI. The influence of addiction on fertility outcomes revealed in our study highlights the negative effects of certain addictions on pregnancy rates. Husbands with alcohol addiction had no positive pregnancy, and those with tobacco addiction showed a lower positive pregnancy rate of 12.5% than non-users. In contrast, wives with tobacco addiction had a notably higher positive pregnancy rate of 33.3%. These findings reflect the complex interplay between addiction and fertility. Alcohol and tobacco are known to impair reproductive health, which aligns with Green et al ., who noted that lifestyle factors such as smoking and alcohol consumption adversely affect fertility.[ 15 ] However, the higher positive rate among wives with tobacco addiction could be due to confounding factors or result from a small sample size, and further research is needed to clarify these results. In summary, while age, BMI, and physical activity levels align with established research on their impact on fertility, our findings on BMI and addiction present interesting deviations from expected patterns. These results emphasize the need for individualized treatment approaches and further research to better understand the factors influencing IUI success. The complexity of fertility outcomes necessitates a comprehensive evaluation of all contributing factors, including lifestyle and health conditions, to optimize treatment strategies. Pregnancy rates did not significantly differ between primary and secondary infertility ( P = 0.489) in the present study which is consistent with the study conducted by Yu et al . and Cabry-Goubet et al .[ 19 20 ] He et al .[ 21 ] reported that secondary infertility may be associated with a higher chance of live births, especially in younger patients (<35 years old) undergoing IUI and ovarian stimulation. These results highlight how crucial it is to customize fertility treatment plans by taking the patient’s unique characteristics and the type of infertility into account. Optimizing the effectiveness of fertility treatment plans and enhancing the results for couples undergoing ART, such as IUI, require a thorough understanding of the causes of infertility and how they affect pregnancy rates.[ 22 ] Numerous factors can lead to infertility: male factors like sperm quality and quantity, and female factors such as uterine abnormalities, tubal blockages, and ovulatory dysfunction.[ 23 ] According to Starosta et al .,[ 8 ] women with ovulatory dysfunction and infertility that cannot be explained benefit from IUI the most, while those with tubal factor and stage III-IV endometriosis benefit the least from it. Different correlation among the causes of infertility and pregnancy rates in IUI cycles was derived in the present study in contrast to several researchers, who reported lower cumulative pregnancy rates in endometriosis and tubal factors, whereas higher cumulative pregnancy rates in ovulatory dysfunction and cervical factors.[ 14 24 ] Pregnancy rates with and without male factor infertility ( P = 0.148) and among various post-wash sperm count thresholds ( P = 0.129) were found to be non-significantly different in this study as supported by Yu and Mukhtar et al .[ 19 25 ] In contrast to the present study, Montanaro Gauci et al .[ 26 ] reported that sperm motility and morphology were found to be significant predictors of success for pregnancy rates. It is crucial to carefully assess and optimize male factors to increase the likelihood of pregnancy for couples receiving IUI as reported by various researchers. A crucial indicator of ovarian reserve and potential for conception in women is the level of AMH.[ 27 ] AMH levels in this study had a trend toward significance, but they fell short of statistical significance ( P = 0.088) whereas Stalzer et al .[ 28 ] reported higher clinical pregnancy correlation with higher mean AMH values with 2.1 ng/mL optimal AMH cut-off. Moreau et al .[ 29 ] discovered that there was no discernible effect of AMH levels on the success of IUI cycles in terms of pregnancy outcomes supports our study. Women with optimal age-specific AMH levels might have more healthy ovarian follicles available for ovulation, increasing their chances of conceiving successfully and developing a clinical pregnancy following IUI. On the other hand, decreased ovarian reserve may be indicated by lower AMH levels, which may lead to a lower success rate in reproduction after IUI.[ 28 30 ] HSG is not a useful therapeutic strategy, but it may be beneficial as a diagnostic technique for women experiencing early infertility, according to Sanei Sistani et al .[ 31 ] HSG results analysis in the current study showed no significant correlation ( P = 0.789) with clinical pregnancy rates in IUI cycles. The time between HSG and IUI has a substantial influence on pregnancy outcomes, according to Ling et al .[ 32 ] They discovered that when IUI was carried out within 6 months of HSG, clinical pregnancy rate, and live births were at their highest. Significantly higher clinical pregnancy rates were linked to the presence of a dominant follicle ( P = 0.015) in our study as with research by Dickey et al .[ 33 ] and Yavuz et al .[ 34 ] highlight the significance of follicular development for successful IUI outcomes. Yu et al .[ 19 ] observed no discernible variation in the prevalence of a dominant follicle between women undergoing IUI cycles who were pregnant and nonpregnant. This suggests that the predictive value of the presence of dominant follicles varies among studies, likely due to differences in patient demographics, sample sizes, or treatment schedules. The present research has shown that among women undergoing IUI, the endometrial thickness of 8 mm or more is linked to increased clinical pregnancy rates. Habibzadeh et al .[ 35 ] discovered that although endometrial thickness was thinner in older patients, there was no discernible relationship between endometrial thickness and gonadotropin ampoules, age, or follicle count. In contrast, they observed that endometrial thickness between 6 and 10 mm was associated with an increased chance of conception in all age groups. The current investigation revealed that endometrial thickness was a significant predictor of clinical pregnancy rates ( P = 0.001), with significantly higher pregnancy rates observed in patients with an endometrial thickness of ≥8 mm. The study performed by Kamath et al .[ 36 ] exposed that the complexity of factors influencing the success of IUI is highlighted by the fact that endometrial thickness did not affect pregnancy rates in IUI cycles ( P = 0.787).

This prospective observational study was conducted at the department of obstetrics and gynecology at a tertiary care hospital from July 2022 to January 2024. The study population was all infertile women undergoing IUI treatment at this center. There were no exclusion criteria. Convenience sampling. Formula for calculation of sample size for qualitative data, n = Z α 2 × p × q / d 2 P = 12.4 d = allowable error in % = 5 power of test (1− B) = 80% confidence interval = 95% estimated sample size = 167. Clinical pro forma which includes variables such as age, body mass index (BMI), physical activity, addiction of both partners, type of infertility, male factors and post-wash sperm count in the husband, serum anti-mullerian hormone estimation of female, hysterosalpingography (HSG) results, follicular study for dominant follicle, and endometrial thickness. The recorded data were entered and coded into a Microsoft Excel Sheet. Data Analysis was done using Statical Package for Social Science (SPSS) version 26.0 or above (International Business Machines Corporation (IBM), Armonk, New York, United States). The final results were represented in tables and charts. Data were represented by frequency (number), proportion (%), mean, median, and standard deviation (SD), Chi-square test, and P values were derived. The variables considered for analysis were the total number of cycles, successful pregnancy, and prognostic factors were considered for analysis.