Abstract
Purpose
To evaluate the association between body mass index (BMI) and pregnancy outcomes in women receiving intrauterine insemination (IUI) treatment.
Methods
The study included 6407 women undergoing 13,745 IUI cycles stratified by BMI. Cox regression was used to analyze the association between BMI and cumulative live births across multiple IUI cycles. A generalized estimating equation (GEE) was used to analyze the live birth rate per cycle.
Results
Compared with normal-weight women (n = 4563), underweight women (n = 990) had a lower cumulative pregnancy and live birth rate (20.71% vs 25.93% and17.17% vs 21.61%, respectively), while overweight women (n = 854) had a higher cumulative pregnancy and live birth rate (31.97%, 26.58%). Adjusted for confounders, the hazard ratio (HR) for achieving live birth following up to a maximum of four IUI cycles was 0.80 (95% CI: 0.67–0.95), comparing underweight with normal weight. In the GEE analyses, low BMI was also associated with a lower per-cycle birth rate (OR 0.79, 95% CI: 0.66–0.95), with adjustment for cycle-specific parameters, including ovarian stimulation, endometrial thickness, and follicular diameter.
Conclusion
Low BMI is associated with poor IUI outcomes.
Supplementary information
The online version contains supplementary material available at 10.1007/s10815-022-02658-y.
Keywords: Intrauterine insemination, Body mass index, Underweight, Cumulative live birth
Introduction
Infertility is known to affect approximately 10–15% of couples. Given its simplicity and affordability, intrauterine insemination (IUI) is often used as a first-choice treatment for couples whose infertility is unexplained or is due to mild male factor infertility [1]. While NICE has suggested that IUI has a limited value in infertility care [2], several recent studies have supported IUI as a cost-effective treatment in comparison with in vitro fertilization [3]. Nevertheless, large-scale datasets have indicated that the delivery rates per IUI cycle using homologous sperm remain stable at rates as low as 8–9% [4, 5].
Several factors, such as age, infertility diagnosis, body mass index (BMI), and semen quality have been linked to the likelihood of pregnancy following IUI cycles. Among them, BMI has been cumulatively reported as a negative predictor for assisted reproductive outcome [6]. However, most of the studies were performed in IVF, and the information regarding IUI outcomes in extreme BMI is still controversial. While some authors have suggested that high BMI in IUI cycles may reduce the response to ovarian stimulation and increase the biochemical pregnancy [7] and pregnancy complications [8], other studies have suggested a neutral effect of BMI on IUI outcomes [9, 10]. Notably, several authors have shown that BMI is positively associated with pregnancy following IUI [11], suggesting a detrimental effect of low BMI rather than obesity. The inconsistency among studies may be due to different cut-off points for BMI, discrepancies among the inclusion criteria, and/or varying focuses of outcome measures. In several studies [9, 12], including a recent one [7], underweight women were combined with normal-weight women or simply excluded in analyses due to their low number. Such an approach may underestimate the effect of low BMI on IUI outcome; however, especially for Asian populations in which low BMI is more common.
In the present study, we evaluated the effect of BMI on the outcome of IUI cycles in a Chinese cohort including 13,745 cycles, focusing on the effect of low BMI on both per-cycle live births and cumulative live births following up to four cycles.
Materials and methods
Study population
The retrospective cohort study was performed on patients who underwent IUI treatment in the Xiamen University Affiliated Chenggong Hospital from July 2015 to December 2020. Before beginning therapy, all couples underwent a standard infertility evaluation. All women had at least one patent fallopian tube documented by either hysterosalpingography or laparoscopy, and all men had prewash total motile counts over 1,000,000 in an ejaculate during the infertility workup. Exclusion criteria included women with bilateral tubal pathology or other endocrine disorders, such as thyroid disease. Patients receiving more than four cycles (n = 34) were also excluded to reduce bias, because these patients may have poorer prognoses than others. This retrospective study was approved by the Ethics Committee of the Medical College of Xiamen University.
All IUI cycles were divided into three groups according to the World Health Organization (WHO) guidelines: underweight (< 18.5 kg/m2), normal weight (18.5–24.9 kg/m2), and overweight (25.0–29.9 kg/m2). Women with BMI ≥ 30.0 kg/m2 were asked to reduce their weight before considering treatment, and so we did not analyze the data from patients with BMI ≥ 30.0 kg/m2.
Intrauterine insemination protocol
The selection of IUI regimens is largely determined by the patient’s preference. Some of the women underwent ovarian stimulation, which was performed with letrozole (2.5 mg) (Jiangsu Hengrui Medicine Co. Jiangsu, China) for 5 days on menstrual cycle days 3–5. A number of patients were stimulated with 37.5–75.0 IU/day of human menopausal gonadotropin (Maanshan Pharmaceutical Trading Co., Anhui, China). The dose was adjusted according to the ovarian response and the patient’s characteristics. The follicular development and endometrial thickness were monitored by serial transvaginal ultrasounds. When the maximum follicle reached at least 18 mm in diameter, 250 µg of recombinant human chorionic gonadotropin hormone (hCG) (Merck Serono, Spain) was administered. The IUI procedure was performed 32 to 36 h after hCG administration. Cycles were cancelled when more than three dominant follicles ≥ 14 mm were detected to prevent high-order multiple pregnancies.
In natural IUI cycles, detection of ovulation was performed either with urine luteinizing hormone (LH) tests or by transvaginal ultrasound. Patients were inseminated 24 h after detection of a spontaneous LH surge or 32 to 36 h following the administration of hCG, where follicular growth was monitored by ultrasound.
A 2-week course of daily treatment with 20 mg of dydrogestrone (Abbott Biologicals, Netherlands) was prescribed for luteal support. The serum β-hCG level was estimated 14 days after IUI. Clinical pregnancy was identified 5 weeks after the IUI with the presence of an intrauterine gestational sac and a pulsating fetal heartbeat.
Statistical analysis
BMI was categorized according to WHO guidelines. The effect of BMI on cumulative outcomes of IUI treatment was estimated with the Kaplan–Meier method according to cycle numbers. Due to the relatively low success rate of IUI treatment, we used a “conservative” model [13] to calculate the cumulative outcomes. In this model, patients who did not return for subsequent treatment were assumed to have no chance of a live birth even if they remained in the cohort.
Cox regression was used to assess the effect of covariates, including female age, basal follicle-stimulating hormone (FSH), LH and antral follicle count (AFC), etiologies (unilateral tubal obstruction, polycystic ovary syndrome (PCOS), and mild endometriosis), parity, duration of infertility, and post-wash motile sperm count.
Per-cycle outcomes were evaluated using a generalized estimating equation (GEE), with adjustments for aforementioned covariates, and important cycle parameters including ovarian stimulation, endometrial thickness, diameter of dominant follicles, and order of IUI cycles.
All calculations were performed in SPSS 22 (IBM, Armonk, NY, USA).
Results
A total of 6407 patients were reviewed, resulting in 13,745 cycles, 4769 of which were natural cycles and 8976 stimulated cycles. Of the total cycles, 2220 (16.15%) involved underweight women and 1756 (12.78%) involved overweight women. Most (71.07%) of the women in the study were of normal weight. The overall multiple pregnancy rate was 4.77% (4.41% twins, 0.36% triplets). Demographic characteristics are summarized in Table 1. Compared with normal-weight patients, underweight patients were characterized by younger age, whereas the overweight patient demographics were biased towards advanced age. As BMI increased, the mean baseline FSH decreased from 7.56 ± 2.43 IU/L in underweight patients to 6.32 ± 1.73 IU/L in the highest BMI categories. There was an increased incidence of PCOS in the overweight group. A higher incidence of endometriosis was observed in the underweight group. Overweight women had a significantly higher infertility duration than underweight individuals and those with BMI < 18.5 kg/m2. Although there was no difference in the total motile sperm count categories among groups, parity was slightly higher in the overweight group.
Table 1.
Baseline characteristics
| Variable | Normal weight | Under weight | Overweight | Underweight vs. normal weight | Overweight vs. normal weight | Overweight vs. underweight |
|---|---|---|---|---|---|---|
| (18.5–24.9 kg/m2; n = 4,563) |
(< 18.5 kg/m2; n = 990) |
(25.0–29.9 kg/m2; n = 854) |
||||
| Age(years) | 30.22 ± 3.81 | 29.44 ± 3.41 | 30.51 ± 4.15 | < .001 | .040 | < .001 |
| Basal FSH (IU/L) | 7.00 ± 2.1 | 7.56 ± 2.43 | 6.32 ± 1.73 | < .001 | < .001 | < .001 |
| Basal LH (IU/L) | 5.70 ± 3.87 | 6.04 ± 3.9 | 5.15 ± 3.44 | .011 | < .001 | < .001 |
| Basal AFC (n) | 13.17 ± 12.49 | 12.02 ± 5.65 | 14.15 ± 6.42 | .003 | .018 | < .001 |
| BMI (kg/m2) | 21.05 ± 1.45 | 17.61 ± 0.71 | 25.32 ± 1.74 | < .001 | < .001 | < .001 |
| Additional etiologies | ||||||
| PCOS (%) | 860/4563 (18.85) | 102/990 (10.30) | 224/854 (26.23) | < .001 | < .001 | < .001 |
| Endometriosis (%) | 350/4563 (7.67) | 115/990 (11.62) | 51/854 (5.97) | < .001 | .082 | < .001 |
| Unilateral tubal obstruction (%) | 738/4563 (16.17) | 153/990 (15.45) | 127/854 (14.87) | .576 | .340 | .728 |
| Duration of infertility(years) | .758 | .030 | .008 | |||
| < 2 | 1044/4563 (22.88) | 231/990 (23.33) | 156/854 (18.27) | |||
| ≥ 2 | 3519/4563 (77.12) | 759/990 (76.67) | 698/854 (81.73) | |||
| Parity (n) | < .001 | < .001 | .001 | |||
| 0 | 4094/4563 (89.72) | 922/990 (93.13) | 734/854 (85.95) | |||
| ≥ 1 | 469/4563 (10.28) | 68/990 (6.86) | 120/854 (14.05) | |||
| Postwash TMC (106) | .844 | .086 | .094 | |||
| ≤ 5.0 | 43/4563 (0.94) | 10/990 (1.01) | 7/854 (0.82) | |||
| 5.1–10.0 | 1392/4563 (30.51) | 286/990 (28.89) | 269/854 (31.50) | |||
| 10.1–15.0 | 1404/4563 (30.77) | 304/990 (30.71) | 291/854 (34.07) | |||
| 15.1–20.0 | 1046/4563 (22.92) | 240/990 (24.24) | 187/854 (21.90) | |||
| > 20.0 | 678/4563 (14.86) | 150/990 (15.15) | 100/854 (11.71) | |||
Data are presented as mean ± SD and n (%). FSH: follicle-stimulating hormone; LH: luteinizing hormone; AFC: antral follicle count; BMI: body mass index; PCOS: polycystic ovarian syndrome; TMC: total motile sperm count
After four IUI cycles, the conservative cumulative pregnancy rate was 25.92% (95% CI: 24.9–27.0) and the conservative cumulative live birth rate was 21.59% (95% CI: 20.6–22.6). The cumulative outcomes calculated according to BMI categories are shown in Table 2. The conservative cumulative live birth rate in normal weight, underweight, and overweight patients was 21.61% (95% CI: 20.4–22.8), 17.17% (95% CI: 14.9–19.5), and 26.58% (95% CI: 23.7–29.6), respectively. The BMI-specific live birth rates were significantly different from one another, according to log-rank tests (p < 0.001).
Table 2.
Cumulative outcomes for IUI cycles
| Cycle | Overall | Normal weight (18.5–24.9 kg/m2; n = 4563) |
Under weight (< 18.5 kg/m2; n = 990) |
Overweight (25.0–29.9 kg/m2; n = 854) |
||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Patients in the cohort | Patients who did not return (%) | Pregnancy (%) | Live birth (%) | Patients in the cohort | Patients who did not return (%) | Pregnancy (%) | Live birth (%) |
Patients in the cohort | Patients who did not return (%) | Pregnancy (%) | Live birth (%) | Patients in the cohort | Patients who did not return (%) | Pregnancy (%) | Live birth (%) | |
| 1 | 6407 | N/A | 842 (13.14) | 716 (11.18) | 4563 | N/A | 610 (13.37) | 519 (11.37) | 990 | N/A | 89 (8.99) | 75 (7.58) | 854 | N/A | 143 (16.74) | 122 (14.29) |
| 2 | 4698 | 993/5691 (17.45) | 556 (11.83) | 455 (9.68) | 3351 | 693/4044 (17.14) | 388 (11.58) | 317 (9.46) | 764 | 151/915 (16.50) | 80 (10.47) | 69 (9.03) | 583 | 149/732 (20.36) | 88 (15.09) | 69 (11.84) |
| 3 | 2497 | 1746/4243 (41.15) | 243 (9.73) | 197 (7.89) | 1751 | 1283/3034 (42.29) | 168 (9.59) | 138 (7.88) | 442 | 253/695 (36.40) | 33 (7.47) | 23 (5.20) | 304 | 210/514 (40.86) | 42 (13.82) | 36 (11.84) |
| 4 | 143 | 2157/2300 (93.78) | 20 (13.99) | 15 (10.49) | 104 | 1509/1613 (93.55) | 17 (16.35) | 12 (11.54) | 24 | 395/419 (94.27) | 3 (12.5) | 3 (12.50) | 15 | 253/268 (94.40) | 0 (0) | 0(0) |
| All cycles | 6407 | N/A | 1661 (25.92) | 1383 (21.59) | 4563 | N/A | 1183 (25.93) | 986 (21.61) | 990 | N/A | 205 (20.71) | 170 (17.17)* | 854 | N/A | 273 (31.97) | 227 (26.58)* |
Data are presented as n (%). *The BMI-specific live birth rates were significantly different from one another, according to log-rank tests (P < 0.001)
According to Cox regression (Table 3), underweight is associated with lower cumulative pregnancy and live birth rates, while overweight is associated with higher cumulative pregnancy and live birth rates, with adjustment for age, ovarian reserve markers, parity, etiologies, and total motile sperm count categories.
Table 3.
Effect of patient characteristics on cumulative live birth based on Cox regression
| Variable | Category | HR (95% CI) | |
|---|---|---|---|
| Cumulative pregnancy | Cumulative live birth | ||
| BMI(kg/m2) | 18.5–24.9 | Ref | Ref |
| < 18.5 | 0.85 (0.73–0.98) | 0.80 (0.67–0.95) | |
| 25.0–29.9 | 1.19 (1.04–1.36) | 1.19 (1.02–1.38) | |
| Age(years) | Per year increased | 0.96 (0.95–0.98) | 0.95 (0.93–0.96) |
| Basal FSH (IU/L) | Per IU increased | 0.93 (0.90–0.96) | 0.94 (0.91–0.96) |
| Basal LH (IU/L) | Per IU increased | 1.02 (1.01–1.03) | 1.02 (1.00–1.03) |
| Basal AFC (n) | Per AFC increased | 1.00 (1.00–1.01) | 1.00 (1.00–1.01) |
| PCOS | With vs. without | 1.75 (1.55–1.98) | 1.73 (1.51–1.98) |
| Endometriosis | With vs. without | 0.65 (0.52–0.82) | 0.62 (0.48–0.80) |
| Unilateral tubal obstruction | With vs. without | 0.76 (0.65–0.88) | 0.79 (0.67–0.93) |
| Parity (n) | 0 | Ref | Ref |
| ≥ 1 | 0.99 (0.82–1.19) | 0.97 (0.79–1.19) | |
| Duration of infertility(years) | < 2 | Ref | Ref |
| ≥ 2 | 0.84 (0.75–0.94) | 0.87 (0.77–0.99) | |
| Postwash TMC(106) | ≤ 5.0 | Ref | Ref |
| 5.1–10.0 | 1.07 (0.65–1.77) | 1.00 (0.59–1.71) | |
| 10.1–15.0 | 1.07 (0.65–1.77) | 1.03 (0.61–1.76) | |
| 15.1–20.0 | 1.00 (0.61–1.66) | 0.94 (0.55–1.61) | |
| > 20.0 | 1.06 (0.64–1.76) | 0.97 (0.56–1.67) | |
BMI body mass index; FSH follicle-stimulating hormone; LH luteinizing hormone; AFC antral follicle count; PCOS polycystic ovarian syndrome; TMC total motile sperm count
BMI was also associated with per-cycle pregnancy and live birth according to GEE analyses (Table 4). Adjusted for potential confounding factors, low BMI was associated with a reduced live birth rate (OR 0.79, 95% CI: 0.66–0.95). However, the live birth rate in the overweight group significantly increased (OR 1.21, 95% CI: 1.03–1.42). The other variables with an independent effect on the rate of clinical pregnancy in the multivariate models were age, basal FSH, basal LH, ovarian stimulation, duration of infertility, diameter of dominant follicles, and endometrial thickness. Compared with natural cycles, oral medication cycles and gonadotropin cycles increased live birth rates 1.31-fold (95% CI: 1.12–1.54) and 2.02-fold (95% CI: 1.71–2.38), respectively. The probability of clinical pregnancy in cases with endometrial thickness < 7 mm was significantly lower than in cases with endometrial thickness > 9 mm, with adjustment for potential confounding factors (p < 0.01).
Table 4.
GEE analyses of per-cycle live birth
| Variable | Category | OR (95% CI) | |
|---|---|---|---|
| Pregnancy | Live birth | ||
| BMI (kg/m2) | 18.5–24.9 | Ref | Ref |
| < 18.5 | 0.81 (0.69–0.95) | 0.79 (0.66–0.95) | |
| 25.0–29.9 | 1.22 (1.05–1.42) | 1.21 (1.03–1.42) | |
| Age(years) | Per year increased | 0.97 (0.95–0.99) | 0.95 (0.94–0.97) |
| Basal FSH (IU/L) | Per IU increased | 0.92 (0.89–0.95) | 0.92 (0.89–0.96) |
| Basal LH (IU/L) | Per IU increased | 1.04 (1.02–1.05) | 1.03 (1.02–1.05) |
| Basal AFC (n) | Per AFC increased | 1.01 (0.98–1.04) | 1.01 (0.99–1.03) |
| Parity (n) | 0 | Ref | Ref |
| ≥ 1 | 1.07 (0.89–1.30) | 1.04 (0.85–1.29) | |
| Duration of infertility(years) | < 2 | Ref | Ref |
| ≥ 2 | 0.81(0.72–0.92) | 0.86(0.75–0.98) | |
| Postwash TMC(106) | ≤ 5.0 | Ref | Ref |
| 5.1–10.0 | 1.35 (0.71–2.59) | 1.55 (0.74–3.25) | |
| 10.1–15.0 | 1.53 (0.80–2.93) | 1.79 (0.85–3.76) | |
| 15.1–20.0 | 1.34 (0.70–2.58) | 1.58 (0.75–3.32) | |
| > 20.0 | 1.43 (0.74–2.76) | 1.63 (0.77–3.44) | |
| Type of cycles | Natural cycles | Ref | Ref |
| Oral medications | 1.30 (1.12–1.51) | 1.31 (1.12–1.54) | |
| Gonadotropin | 2.04 (1.71–2.42) | 2.02 (1.71–2.38) | |
| Endometrial thickness (mm) | < 7 | Ref | Ref |
| 7–8 | 1.12 (0.94–1.35) | 1.17 (0.96–1.43) | |
| 8–9 | 1.13 (0.94–1.35) | 1.21 (0.99–1.47) | |
| 9–10 | 1.28 (1.06–1.53) | 1.42 (1.16–1.73) | |
| 10–11 | 1.15 (0.94–1.41) | 1.26 (1.00–1.57) | |
| 11–12 | 1.38 (1.09–1.75) | 1.55 (1.20–2.00) | |
| ≥ 12 | 1.32 (1.05–1.67) | 1.45 (1.13–1.86) | |
| Follicle (mm) | post ovulation | Ref | Ref |
| < 17 | 1.23 (0.95–1.60) | 1.32 (0.99–1.76) | |
| 17–18 | 1.46 (1.14–1.86) | 1.57 (1.20–2.05) | |
| 18–19 | 1.45 (1.16–1.83) | 1.57 (1.22–2.03) | |
| 19–20 | 1.54 (1.22–1.94) | 1.64 (1.27–2.12) | |
| ≥ 20 | 1.49 (1.19–1.87) | 1.53 (1.19–1.96) | |
| Order of IUI cycles | 1 | Ref | Ref |
| 2 | 0.95 (0.85–1.07) | 0.92 (0.81–1.05) | |
| > 2 | 0.88 (0.76–1.01) | 0.85 (0.73–0.99) | |
BMI body mass index; FSH follicle-stimulating hormone; LH luteinizing hormone; AFC antral follicle count; TMC total motile sperm count
The distribution of ovarian stimulation cycles was uneven among BMI categories (Supplementary Table 1) and it may introduce potential bias. We further analyzed the association between BMI and IUI outcomes in natural cycles and simulation cycles respectively (Supplementary Table 2). The results suggested that the association between BMI and IUI outcomes was similar between different types of cycles.
Because the ovarian stimulation is also associated with multiple pregnancies, we further analyzed the association between BMI and multiple pregnancy rates. GEE analyses showed that there was no significant correlation between multiple pregnancy rate and BMI (Supplementary Table 3).
Discussion
In this retrospective study, we found that BMI is associated with cumulative live birth rate following a maximum of four IUI cycles and per-cycle live birth outcome in a cohort of 6407 women resulting in 13,745 cycles. The data indicated that underweight women might have a lower chance of success in IUI treatments in comparison with normal-weight women, while overweight women might have a higher chance, which suggests a positive association between BMI and IUI outcomes.
Our results are largely in accordance with the results described by Wang et al., which demonstrated a significant increase in fecundity from underweight to obese women [11]. In a cohort of 477 women undergoing 1189 ovulation induction IUI cycles, Souter et al. also demonstrated that a higher BMI (≥ 25 kg/m2) was associated with higher odds of achieving pregnancy and live birth than the lowest BMI (< 25 kg/m2) [14]. More recently, Immediata et al. also observed a positive association between BMI and live birth following IUI cycles in a cohort of 2901 patients by univariate analyses [15]. However, BMI was not included in their multivariate model, and they finally concluded that IUI outcomes “were found to be significantly correlated with female age and FSH levels”. Our study further supported the existing evidence by reporting cumulative live birth in a larger IUI cohort categorized according to the WHO’s BMI criteria.
Several other studies have reported a lack of association between BMI and IUI outcomes [9, 10]. However, as mentioned by the authors, the small number of patients with extreme BMI might have made it difficult to draw strong conclusions [10].
Our study conflicts with the work of Aydin et al. [8], in which BMI is negatively associated with pregnancies. The difference may be explained by the distribution of BMI in the two populations. In Aydin et al.’s work, the mean BMI of non-pregnant women was as high as 26 kg/m2, indicating a large proportion of obese patients in their cohort. Due to the lack of patients with BMI > 30 kg/m2 in our cohort, we were unable to estimate the effect of obesity. However, other authors who included obese women in their analyses still produced conflicting results [7, 14, 16], highlighted the need for further studies on the effect of obesity.
BMI may affect the IUI outcomes in several aspects. While BMI is negatively associated with hormone levels and follicular growth [17], Souter et al. suggested that BMI was positively associated with endometrial thickness, indicating that higher BMI may be a favorable factor for endometrial receptivity as soon as “the medication and response are adjusted to overcome the weight effect” [14]. Therefore, heterogeneity in medication and the patients’ response may contribute to the difference in the effect of BMI shown by previous studies. Our per-cycle multivariate analyses showed that the effect of BMI was not confounded or mediated by either ovarian stimulation or follicular growth, supporting a possible role in endometrial receptivity.
Our study is strengthened by a relatively large sample size, but it is limited by its retrospective nature. Selection bias exists, because women with high BMIs may be recommended to lose weight before treatment. This bias may skew the estimation of the higher end of BMI. The additional bias might also be introduced due to the patient’s preference for IUI regimens. The distribution of natural and stimulation cycles appeared to be uneven across the BMI categories. Nevertheless, the analyses stratified according to the type of cycle support our argument. The reasons for the low BMI in the population are not well documented. A low BMI may simply be due to reduced food intake, but it may also suggest chronic conditions. Unreported conditions may contribute to unknown confounding factors in this retrospective study.
Conclusion
Our study suggests that BMI is positively associated with cumulative IUI outcomes in women with a BMI < 30 kg/m2. Especially, underweight women may have a lower chance of getting pregnant in comparison with normal-weight and overweight women. With increasing concerns about the health effects of obesity, several authors have either ignored underweight women [7] or pooled them with women with normal BMIs [14]. Our results, however, suggest that low BMI as well as obesity should be considered when providing consultations to patients receiving IUI treatments.
Supplementary information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors thank all of the staff, nurses, and physicians at the Reproductive Medicine Center for their support in generating this manuscript.
Funding
This work was funded by the Clinical Research Special Fund of Chinese Medical Association (NO.18010360765), Xiamen Medical Advantage Subspecialty Construction Project (2018296) and Xiamen Medical and Health Guidance Project (3502Z20214ZD1189).
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Juan Zheng and Jiali Cai contributed equally to this work.
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