Analysis of factors associated with IUI pregnancy outcomes in elderly and young patients.

A total of 2110 couples underwent 4221 cycles in this study. The mean age was 30 years old, and the mean duration of infertility was about three years. The clinical pregnancy rate (CPR) was 13.6% per cycle ; The abortions rate about 10.3% and the ectopic pregnancy rate about 1.84%; 90.8% children were singleton pregnancies and 4.52% children were twins.The proportion of the first cycle is about 49.6%(2093/4221),the proportion of the second cycle is 33.4%(1410/4221) and the proportion of the third cycle is 13.0%(550/4221). The couple age in the pregnancy group is younger than the non-pregnancy group( P <0.001) ( P  = 0.003),and the BMI in the pregnancy group is higher than the non-pregnancy group( P  = 0.003).The normal morphology rate in the pregnancy group was higher than the non-pregnancy group ( P  = 0.023) .There was no difference in other indicators, including the woman’s infertility diagnosis, infertility years, infertility types, treatment options, and male body mass index and other semen parameters (Table  1 ). Table 1 Compared the cycle characteristics of patients between the pregnancy and non-pregnancy group Variables Non-pregnant( n  = 3646) Pregnant( n  = 575) P Female age (years) 30.86 ± 3.31 30.20 ± 3.29 < 0.001 AMH(ng/ml) 3.02 [1.84,5.26] 3.28 [1.81,5.96] 0.191 Male age (years) 32.04 ± 4.03 31.50 ± 3.92 0.003 Female BMI( kg/m2) 22.53 ± 3.51 23.00 ± 3.71 0.003 Male BMI( kg/m2) 28.61 ± 93.92 25.37 ± 4.05 0.600 Cycle number(n)  1 1802 (49.42) 291 (50.61) 0.859  2 1223 (33.54) 187 (32.52)  3 621 (17.03) 97 (16.87) Duration of infertility(years) 3.00 [2.00, 4.00] 2.00 [2.00, 4.00] 0.063 Female diagnosis (%)  Male 1165 (31.95) 173 (30.31) 0.12  Unexplained infertility 1738 (47.69) 261(45.45)  Endometriosis 69 (1.90) 8 (1.48)  Ovulation disorder 600 (16.46) 125 (21.77) Infertility type (%)  Primary infertility 2750 (75.43) 434 (75.35) 1.000  Second infertility 896 (24.57) 142 (24.65) Number of the dominant follicle (n) 1(1,2) 1(1,2) 0.66 Endometial thickness(cm) 0.87 ± 0.15 0.94 ± 0.18 0.310 Treatment methods (%) Ovarian stimulation cycle 3504 (96.11) 556 (96.70) 0.569 Natural cycle 142 (3.89) 19 (3.30) Total sperm count(million) 159.76 [98.49, 255.20] 154.90 [96.50, 253.98] 0.707 Normal morphology rate(%) 4.40 [4.10, 4.80] 4.40 [4.10, 4.90] 0.023 Progressive motility(million) 42.12 ± 16.86 42.91 ± 17.13 0.293 Total motile sperm count(million) 61.54 [31.95, 111.31] 61.50 [32.31, 115.36] 0.805 Compared the cycle characteristics of patients between the pregnancy and non-pregnancy group The couple age in the pregnancy group is younger than the non-pregnancy group( P  < 0.001)( P  = 0.04),and the women BMI in the pregnancy group is higher than the non-pregnancy group( P  = 0.01);The duration of infertility in the pregnancy group is lower than the in the pregnancy group ( P  = 0.033).The normal morphology rate in the pregnancy group was higher than the non-pregnancy group ( P  = 0.01).The proportion of the secondary infertility in the pregnancy group higher than the non-pregnancy group.There was no difference in other indicators, including the woman’s infertility diagnosis, treatment options, and male body mass index and other semen parameters (Table  2 ). Table 2 Compared the cycle characteristics of young patients between the pregnancy and non-pregnancy group Variables Non-pregnant( n  = 3177) Pregnant( n  = 522) P Female age (years) 29.99 ± 2.49 29.54 ± 2.62 < 0.001 AMH(ng/ml) 3.98(1.85,5.34) 4.11(1.95,5.82) 0.724 Male age (years) 31.17 ± 3.13 30.87 ± 3.26 0.040 Female BMI( kg/m2) 22.51 ± 3.55 22.95 ± 3.72 0.010 Male BMI( kg/m2) 29.11 ± 100.50 25.45 ± 4.12 0.599 Cycle number (n)  1 1562 (49.17) 274 (52.49) 0.355  2 1065 (33.52) 166 (31.80)  3 550 (17.31) 82 (15.71) Duration of infertility (years) 3.00 [2.00, 4.00] 2.00 [2.00, 3.00] 0.033 Female diagnosis (%)  Male 1026 (32.32) 157 (30.16) 0.13  Unexplained infertility 1450 (45.65) 251 (48.16)  Endometriosis 62 (1.95) 6 (1.22)  Ovulation disorder 543 (17.08) 102 (19.45) Infertility type (%)  Primary infertility 2482 (78.12) 397 (75.91) 0.283  Second infertility 695 (21.88) 126 (24.09) Number of the dominant follicle (n) 1(1,2) 1(1,2) 0.75 Endometial thickness(cm) 0.84 ± 0.16 0.95 ± 0.17 0.33 Treatment methods (%) 3053 (96.10) 503 (96.36) 0.868 Ovarian stimulation cycle Natural cycle 124 (3.90) 19 (3.64) Total sperm count(million) 159.67 [99.00, 253.12] 158.24 [97.98, 254.94] 0.990 Normal morphology rate(%) 4.40 [4.10, 4.80] 4.40 [4.10, 4.90] 0.010 Progressive motility(million) 42.35 ± 16.93 42.98 ± 16.97 0.424 Total motile sperm count(million) 62.25 [31.97, 112.34] 62.83 [33.11, 117.44] 0.629 Compared the cycle characteristics of young patients between the pregnancy and non-pregnancy group The women BMI in the pregnancy group is higher than the non-pregnancy group( P  = 0.03).There was significant difference in the ratio of cycles between the two groups( P  = 0.011).There was no difference in other indicators, including the woman’s infertility diagnosis, infertility years, treatment options, and male body mass index and semen parameters (Table  3 ). Table 3 Compared the cycle characteristics of aged patients between the pregnancy and non-pregnancy group Variables Non-pregnant( n  = 469) Pregnant( n  = 53) P Female age (years) 36.78 ± 1.77 36.70 ± 1.85 0.756 AMH(ng/ml) 3.01 [1.54,5.26] 3.19 [1.77,5.82] 0.38 Male age (years) 37.92 ± 4.51 37.74 ± 4.45 0.776 Female BMI( kg/m2) 22.64 ± 3.23 23.53 ± 3.57 0.030 Male BMI( kg/m2) 25.23 ± 3.45 24.63 ± 3.29 0.437 Cycle number (%)  1 240 (51.17) 17 (32.08) 0.011  2 158 (33.69) 21 (39.62)  3 71 (15.14) 15 (28.30) Duration of infertility (years) 3.00 [2.00, 5.00] 3.00 [2.00, 5.00] 0.300 Female diagnosis (%)  Unexplained infertility 152(32.45) 20 (37.23) 0.761  Male 210 (44.80) 22 (41.54)  Endometriosis 7 (1.53) 2 (3.85)  Ovulation disorder 52 (11.22) 8 (15.38) Infertility type (%)  Primary infertility 268 (57.14) 35 (66.04) 0.273  Second infertility 201 (42.86) 18 (33.96) Number of the dominant follicle (n) 1(1,2) 1(1,2) 0.82 Endometial thickness(cm) 0.87 ± 0.16 0.90 ± 0.17 0.43 Treatment methods (%)  Ovarian stimulation cycle 451 (96.16) 53 (100.00) 0.292  Natural cycle 18 (3.84) 0 (0.00) Total sperm count(million) 162.90 [92.10, 258.45] 129.90 [77.76, 248.00] 0.215 Normal morphology rate(%) 4.30 [4.10, 4.80] 4.20 [3.70, 4.90] 0.414 Progressive motility(million) 40.57 ± 16.36 42.22 ± 18.76 0.493 Total motile sperm count(million) 57.91 [31.84, 99.84] 50.64 [27.41, 83.84] 0.364 Compared the cycle characteristics of aged patients between the pregnancy and non-pregnancy group Multivariate logistic regression analysis showed that the age and BMI of total IUI patients are closed related to the pregnancy outcome( P <0.001)( P  = 0.002),the number of cycles were not associated with the pregnancy outcome(Fig.  1 -A); In the younger group reached the same conclusion, with women age having a negative effect on IUI pregnancy outcomes and women BMI having a positive effect( P <0.001)(Fig.  1 -B).The BMI and the cycle number of aged IUI patients are related with the pregnancy outcome, the pregnancy rate of the second cycle is about 1.9 times that of the first cycle( P  = 0.06), and the third cycle is about 3 times that of the first cycle ( P  = 0.06)(Fig.  1 -C). Fig. 1 Multivariate logistic regression analysis of factors associated with pregnancy outcomes in total IUI patients ,younger and aged IUI patients (total patients ( A ) younger patients ( B ) aged patients ( C )) Multivariate logistic regression analysis of factors associated with pregnancy outcomes in total IUI patients ,younger and aged IUI patients (total patients ( A ) younger patients ( B ) aged patients ( C ))

The present study revealed significant associations between women’s age and BMI with pregnancy outcomes. Additionally, the BMI of women and the time of IUI cycles were found to be associated with the pregnancy outcome among older women. These results highlight the importance of considering both age and BMI as potential factors influencing pregnancy outcomes in different age groups of women. Our study supports previous research findings that the age of women is closely related to the pregnancy outcome in the general population. It is well-known that female fertility gradually declines starting from the age of 30, with a significant drop in pregnancy rates after the age of 40. Consequently, it is generally not recommended to undergo IUI after the age of 40 [ 12 , 13 ]. A randomized trial comparing the clinical pregnancy rates of natural conception and ovulation induction with IUI cycles in couples with unexplained or male factor infertility found age to be the sole predictor. The study reported a 50% lower chance of pregnancy for 38-year-old women compared to those who were 28 years old [ 10 ]. In women, as they age, telomerase shortening and age-related mitochondrial mtDNA instability can lead to the accumulation of mtDNA mutations in oocytes, resulting in a decline in the quality of the ovarian reserve and a decrease in the implantation rate [ 14 , 15 ]. Our study also confirmed a negative correlation between age and the pregnancy outcome of IUI, with the effect being more pronounced in the younger group and less pronounced in the older group. This may be attributed to the fact that patients in the older group are typically over 35 years old, where the age range is relatively concentrated, and ovarian function experiences a sharp decline. Therefore, the slight difference of a year or two in age may not have a significant impact due to the limited variation among patients in this age group. The findings of our study indicate that women with higher BMI had higher pregnancy rates compared to women with lower BMI, regardless of their age group. This consistent relationship between BMI and the pregnancy outcome of IUI is noteworthy.It is known that cholesterol in fat cells serves as the raw material for the synthesis of sex hormones. Women with low BMI and low subcutaneous fat have lower cholesterol content and lower levels of sex hormones in their bodies. This can have a dual impact on ovarian function and endometrial development, ultimately affecting the pregnancy outcome of IUI [ 16 ]. Research has shown that women with relatively low BMI have lower concentrations of serum hCG and progesterone, which can affect endometrial thickness and lead to early pregnancy loss [ 17 ]. Studies have also found that being underweight is associated with infertility due to anovulation and hypothalamic amenorrhea. Underweight patients have an increased risk of delivering small-for-gestational-age babies, especially when undergoing ovulation induction [ 18 , 19 ]. On the other hand, there is a positive correlation between BMI and endometrial thickness. However, obesity increases reproductive risks, including infertility due to menstrual dysfunction and oligo-anovulation [ 20 – 23 ]. In our study, the average BMI of patients was around 23, with most patients falling within the normal BMI range, and only a relatively small proportion of patients being obese. Therefore, within the normal BMI range, higher BMI values were found to be more favorable for the outcome of IUI in our study. Most experts recommend considering a switch to in vitro fertilization (IVF) after three or four intrauterine insemination (IUI) cycles because the majority of pregnancies resulting from IUI occur within the first few cycles. Studies have demonstrated that up to 95% of pregnancies achieved through IUI with gonadotropins or clomiphene citrate (CC) occur within the first three cycles, and up to 98% occur within the first four cycles [ 8 ]. However, these recommendations may not meet the individual needs of patients, especially considering factors such as age. It is important for doctors and patients to understand the potential benefits of continuing with different numbers of IUI cycles, and there is no theoretical support for a specific cutoff. Our study found that the number of IUI cycles was not related to pregnancy outcomes in the younger group, but it was closely related to outcomes in the older group. Previous research has also confirmed that women under 30 years old required an average of 1.99 cycles to conceive, while those over 40 years old required an average of 2.24 cycles [ 3 ]. Comparing the second cycle to the first cycle, the pregnancy rate was 1.9 times higher, and the third cycle had a pregnancy rate over 3 times higher than the first cycle. In other words, for younger patients, increasing the number of IUI cycles may not significantly improve the pregnancy outcome. However, for older patients, it may be beneficial to increase the number of IUI cycles to improve the pregnancy rate. It is possible that for younger patients, switching to IVF after one or two IUI failures may be sufficient, while for older patients, increasing the number of IUI cycles to four before considering IVF could be considered. However, it is important to note that older patients also face the risk of premature ovarian failure, so a comprehensive assessment is needed before making a decision. This assessment should consider factors such as the patient’s age, ovulation status, cost of treatment, and the patient’s goals. When interpreting the results of the study, it is important to consider both the advantages and limitations. Some of the advantages of the study include analyzing the correlation between the number of IUI cycles and outcomes in patients of different ages, which has not been extensively studied before. Additionally, the study benefits from having complete medical records and accurate follow-up data. The large sample size (around 4,000) and the study period of about three years also contribute to the study’s strength.However, there are several limitations that should be acknowledged. Firstly, the study is a retrospective study conducted at a single center. While the sample size is large, and efforts were made to control for confounding factors using multivariate logistic regression, there may still be residual confounding factors. Therefore, further validation using a large multi-center sample is necessary.Secondly, due to expert consensus and strict management of assisted reproductive technology, there is a lack of data on the fourth and fifth cycles of IUI. However, the data from the first three cycles can still provide a certain theoretical basis. In conclusion, the study found associations between women’s age and BMI with the clinical outcomes of IUI. The number of cycles in young women was not significantly associated with the pregnancy outcome in IUI. However, in older women, the number of cycles was related to the pregnancy outcome, with higher pregnancy rates observed in the second and third cycles compared to the first cycle.

Approximately 10% of couples worldwide experience infertility [ 1 ]. While assisted reproductive technology (ART) is a common and effective treatment for infertile couples, intrauterine insemination (IUI) remains a popular option due to its effectiveness, affordability, and safety [ 2 ]. IUI is primarily used to address mild male factor infertility, anovulation, endometriosis, and unexplained infertility. Among these, patients with anovulation tend to have the best treatment outcomes [ 3 ]. Despite advancements in IUI techniques, such as ovulation stimulation, the clinical pregnancy rate of IUI still lags behind that of in vitro fertilization (IVF). Numerous studies have identified several factors associated with the pregnancy outcomes of IUI, including female age, female BMI, duration of infertility, and dominant follicles [ 4 , 5 ]. Many scholars and experts in the field of assisted reproductive technology recommend considering IVF treatment after three to four cycles of IUI. This recommendation is based on the observation that the majority of pregnancies occur within the first four cycles, and subsequent cycles may offer little additional benefit [ 6 – 8 ]. Currently, there is a consensus among experts in assisted reproductive technology that IUI should be attempted for three to four cycles, and if unsuccessful, patients should consider transitioning to IVF treatment. This approach is widely adopted as a diagnostic and treatment guideline in most reproductive centers. However, it is important to note that the optimal number of IUI cycles may vary for each individual patient. Due to the variability in patient characteristics and underlying infertility issues, a fixed recommendation of three or four cycles may not be appropriate for everyone. Clinical research has not yet provided guidelines that can be easily adapted to address the specific needs and challenges of each patient. Therefore, it is crucial for healthcare providers to carefully evaluate each patient’s unique circumstances and consider personalized treatment plans based on factors such as age, fertility history, and response to previous cycles. Age is indeed a significant indicator of female fertility and plays a crucial role in assisted reproductive technology [ 9 ]. As women age, their fertility declines due to factors such as diminished ovarian reserve and an increased risk of chromosomal abnormalities in oocytes (aneuploidy) [ 10 , 11 ]. It is uncertain whether factors related to pregnancy outcomes differ between older and younger patients undergoing IUI. Therefore, the purpose of the study you mentioned is to explore the correlation between various factors and IUI pregnancy outcomes in both young and older patients. By examining these associations, the study aims to provide a theoretical basis for clinical consultations and guidance when considering IUI as a treatment option.

This study is a retrospective analysis of IUI cycles (4221)at the reproductive center of the Changzhou Maternal and Child Health Hospital from January 2016 to December 2020. The patients were categorized into two groups according to age, the elder group (≥ 35 years)and the young group (<35 years). The exclusion criteria were: (1) chromosomal abnormalities in either partner of the couple, (2) presence of ovarian cysts at the start of the ovarian stimulation procedure, (3) abnormal uterine cavity, ovarian deficiency, or other organic diseases;(4) The patients with PCOS ,BMI ≥ 30 kg/m 2 . The study and the protocols used were approved by the Ethics Committee of the Changzhou Maternal and Child Health Care Hospital (17,020,490,718).Written informed consent was obtained from the infertility couple. According to the literature reports, the pregnancy rate of IUI cycle is higher than that of natural cycle, and most patients in our center were performed the Letrozole (LE, Jiangsu Hengrui Pharmaceutical Company), human menopausal gonadotropin (hMG,Livzon Pharm), or hMG with LE.The dosages were determined by BMI, ovarian reserve assessment, and the historical ovarian reactivity. The monitor of follicles and endometrium were performed by the transvaginal ultrasound (TVUS). IUI was canceled if more than three dominant follicles. Ovulation was triggered with hCG (hCG, Livzon Pharm) 10,000 IU or Triptorelinacetate (GnRH-a,Ferring Pharmaceuticals) 0.1 mg when the mean diameter reached 18 mm. IUI performed after 26–36 h of trigger injection. The man’s semen is removed by gradient centrifugation in the laboratory and then injected directly into the woman’s uterus through a soft IUI catheter. Luteal phase support was provided with Progesterone Soft Capsules 100 mg twice daily for 14 days after ovulation was determined. Sperm parameters strictly follow the fifth WHO edition(2010).Patients with 2–5 days of abstinence ejaculated semen into a sterilized cup by masturbation. After liquefaction, 10 ml of semen sample was drawn on the slide to roughly estimate sperm parameters (concentration and motile) including the percentage of progressive motility (PR) sperm, non-PR (NP) and immobile (IM) sperm. Te remaining sample was placed on a density gradient column consisting of 1.5 ml of lower layer and 1.5 ml of upper layer (Irvine, USA) and centrifuged at. 1750 rpm for 15 min. After that, the sperm pellet was re-suspended in 2.7 ml of medium and and centrifuged at 1500 rpm for 9 min after absorbing the supernatant and leaving 0.5 ml for mixing.Sperm analysis was performed by the same laboratory technician according to the a quality control program. The blood test carried out to determine pregnancy. TVUS was performed one month after IUI. Professionals followed up the condition of pregnancy and childbirth. Statistical analyses were performed using SPSS software version 26.0 (IBM, Armonk, NY, USA). Quantitative variables with normal distribution were expressed as mean ± standard deviation, and Students’ t test was used to compare means. Quantitative variables with abnormal distribution or heterogeneous variance were expressed as M(P25,P75), and the median was compared by Mann-Whitney U-test. Chi-square test was used to compare the differences between the two groups. Fisher exact test was used to compare differences in rates when the expected count was < 5or the total sample size was < 40. P  < 0.05 was considered statistically significant. Multi-factor logistic regression analysis of factors associated with IUI pregnancy outcomes was presented as forest maps,an OR value of 1 indicates no correlation, an OR value greater than 1 indicates a positive correlation, and an OR value less than 1 indicates a negative correlation.