The Impact of serum uric acid Levels on the Cumulative Live Birth Rate in Women with Polycystic Ovary Syndrome Undergoing In Vitro Fertilization-Embryo Transfer (IVF-ET)

The Impact of serum uric acid Levels on the Cumulative Live Birth Rate in Women with Polycystic Ovary Syndrome Undergoing In Vitro Fertilization-Embryo Transfer (IVF-ET) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of serum uric acid Levels on the Cumulative Live Birth Rate in Women with Polycystic Ovary Syndrome Undergoing In Vitro Fertilization-Embryo Transfer (IVF-ET) Siyue Xu, Ting Zhang, Nan Jia, Meng Li, Lifeng Tian, Shaodi Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5873869/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose To estimate the impact of serum uric acid (SUA) levels on the cumulative live birth rate (CLBR) in women with polycystic ovary syndrome (PCOS) undergoing in vitro fertilization-embryo transfer (IVF-ET). Methods A retrospective cohort study analyzed data from 2,841 women who had their first IVF-ET treatment at the Reproductive Center of Henan Provincial People's Hospital and the Reproductive Center of Jiangxi Provincial Maternal and Child Health Hospital between January 2016 and December 2021. The women were divided into four groups based on SUA quartiles. Baseline characteristics and clinical and laboratory indicators were compared across these groups. Logistic regression was used to assess the impact of different SUA levels on CLBR. Correlation analysis identified factors influencing SUA levels and clarified the main factors affecting CLBR in women with PCOS. Results After adjusting for confounding factors, the SUA level did not significantly affect CLBR (P > 0.05). SUA levels were positively correlated with body mass index (BMI), weight, baseline testosterone (T), and fasting insulin (P < 0.05). Curve-fitting analyses showed that SUA levels exhibited an increasing trend with the rise of BMI, weight, fasting insulin, and baseline T. BMI and weight were linearly associated with the CLBR, with rates decreasing as BMI and weight increased. In contrast, SUA, fasting insulin, and baseline T did not correlate significantly with the CLBR. Conclusion SUA levels do not have a significant impact on the CLBR in women with PCOS. BMI and weight are negatively correlated with CLBR. Serum Uric Acid BMI In Vitro Fertilization-Embryo Transfer Polycystic Ovary Syndrome Cumulative Live Birth Rate Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Polycystic ovary syndrome (PCOS) is a common endocrine disorder primarily characterized by infrequent ovulation/anovulation, hyperandrogenism, and polycystic ovarian morphology, with a prevalence rate of 4%-21% among women of reproductive age[1] PCOS is one of the leading causes of ovulatory infertility, making assisted reproductive technology (ART) a significant option for women with PCOS. Additionally, PCOS often coexists with metabolic disturbances such as obesity, hypertension, dyslipidemia, and elevated serum uric acid (SUA) levels [2–4]. SUA is the end product of endogenous metabolic production and the breakdown of dietary purines. SUA levels are influenced by the endogenous metabolism of the liver, kidneys, and small intestine and the exogenous intake of high-fructose and high-purine foods [5]. Unhealthy lifestyles and dietary habits in modern society have led to an increased prevalence of hyperuricemia. Elevated SUA levels have been implicated in the development of various diseases. Current research indicates that elevated SUA levels are associated with insulin resistance, obesity [6], hypertension, type 2 diabetes [7], and cardiovascular diseases[8]. Recently, the relationship between hyperuricemia and infertility has gained increasing attention. Data from the National Health and Nutrition Examination Survey (NHANES) conducted by the Centers for Disease Control and Prevention (CDC) in the United States from 2013 to 2020 showed that the incidence of female infertility increased significantly with rising SUA levels [9]. Another study based on NHANES data, after adjusting for confounding factors such as age, race, marital status, smoking, alcohol, history of pregnancy, history of diabetes, history of hypertension, fasting glucose, total cholesterol, serum creatinine, low-density lipoprotein cholesterol, direct high-density lipoprotein cholesterol, glycohemoglobin, and body mass index(BMI) showed that the risk of infertility in the higher uric acid group was 83% greater compared to the lower uric acid group [10]. Research by Durmus U and colleagues has demonstrated that SUA levels are significantly elevated in the PCOS population and correlate with the severity of the disease [11]. Currently, there are few studies on the impact of SUA levels on assisted reproductive outcomes in infertile women with PCOS. SUA levels have been shown to influence clinical pregnancy rate, live birth rate, and instances of low birth weight in infertile women with PCOS [12]. A multicenter randomized trial involving 1,508 women with PCOS indicated that metabolic syndrome negatively correlates with the cumulative live birth rate (CLBR) among women with PCOS and metabolic syndrome [13], and SUA is related to metabolic syndrome factors such as high BMI, obesity, and insulin resistance [14]. Women with PCOS often have concurrent endocrine and metabolic abnormalities, such as hyperandrogenemia and hyperinsulinemia. Is SUA associated with these endocrine and metabolic disturbances, and do these factors influence assisted reproductive outcomes? Furthermore, is SUA an independent factor affecting assisted reproductive outcomes? These questions remain unresolved in current research. This study analyzes the clinical data of 2,841 PCOS women to explore the impact of SUA levels on CLBR in PCOS women, thereby clarifying the main factors affecting CLBR in PCOS women. Materials and Methods Study Population This study involved 4,441 women undergoing their first IVF/ICSI treatment at the Reproductive Centers of Henan Provincial People's Hospital and Jiangxi Provincial Maternal and Child Health Hospital from January 2016 to December 2021. Inclusion criteria included: (1) diagnosis of PCOS according to the Rotterdam criteria [15]; (2) age < 40 years; (3) women undergoing their first IVF/ICSI cycle. Exclusion criteria included: (1) chromosomal abnormalities in either partner (n = 426); (2) cycles involving Preimplantation genetic testing (PGT) (n = 31), donor sperm/oocytes cycles or frozen oocytes cycles(n = 20), severe male factor (n = 70); (3) uterine malformations (n = 8), uterine fibroids (n = 16), adenomyosis or endometriosis (n = 43); (4) factors affecting the uterine lining, such as endometrial polyps (n = 109), intrauterine adhesions and history of endometrial tuberculosis (n = 59), hydrosalpinx reflux (n = 13); (5) thyroid dysfunction (n = 14), diabetes (n = 7), hyperprolactinemia (n = 1); (6) recurrent miscarriage (n = 33); (7) cycles with no oocytes retrieval (n = 4), canceled cycles (n = 25); (8) cycles with remaining embryos not followed up to live birth (n = 540); (9) cycles with incomplete or anomalous data (n = 181). Based on SUA levels, women were divided into four quartiles: Quartile 1 (SUA ≤ 262 mg/dl, n = 714), Quartile 2 (262 mg/dl < SUA ≤ 310 mg/dl, n = 709), Quartile 3 (310 mg/dl 367 mg/dl, n = 708). 2. Biochemical Indicator Testing Participants in this study were required to fast for at least 8 hours before blood drawing. The patient's blood was collected and placed in a 37°C incubator for about 20 minutes, then centrifuged at 3500 rpm with a centrifugal force of 2190xg for 15 minutes. After centrifugation, the supernatant was collected for testing. Sex hormones and fasting insulin were measured using electrochemiluminescence (Swiss Roche E602). Fasting glucose and SUA were determined using an automatic analyzer (American Abbott Biochemical Analyzer c16000). The normal range for uric acid, as measured by the biochemical analyzer c16000, was 155–357 umol/L. In terms of precision, both intra-assay and inter-assay variability for sex hormone measurements were less than 12%. For other biochemical parameters, intra-assay and inter-assay variability were less than 10%. 3. Ovulation Induction Protocol The GnRH agonist protocol and the GnRH antagonist protocol all refer to previously published articles from our center[16]. 4. Embryo Culture, Embryo Transfer, and Luteal Phase Support Each cleavage-stage embryo was graded according to previously published articles from our center[17]. Blastocyst scoring was performed according to the Gardner scoring system [18]. The criteria for fresh embryo transfer included an endometrial thickness of ≥ 8 mm with a uniform echo, P < 1.5 µg/L, and no infections, OHSS risk, or significant medical histories. 1–2 cleavage embryos or blastocyst were transferred. The remaining embryos or blastocysts meeting cryopreservation criteria were vitrified for future frozen-thawed embryo transfer (FET). Women undergoing fresh transfer began treatment with oral dydrogesterone (Duphaston, 10 mg/tablet, Abbott Laboratories) at 10 mg twice daily, alongside vaginal progesterone slow-release gel (Crinone, 90 mg/applicator, Merck Serono) at 90 mg once daily, starting on the day of oocyte retrieval. FET was performed in patients who did not achieve a live birth after a fresh transfer and had remaining embryos or who did not undergo a fresh cycle transfer. The decision to use an HRT protocol and an ovulation induction protocol was based on the patient's menstrual and ovulation status. The HRT protocol refer to previously published articles from our center[17]. For the ovulation induction protocol, letrozole (Femara, 2.5 mg/tablet, Jiangsu Hengrui Medicine Co., Ltd.) 2.5 mg/day is administered orally for five consecutive days starting from days 3–5 of the menstrual cycle. A week later, the vaginal ultrasound was examined, and according to the situation of follicles, it was decided whether to inject HMG (Human menopausal gonadotropin, 75 units/branch, Zhuhai Lizon Pharmaceutical). Follicles measuring 16 mm or larger are monitored until ovulation occurs. If the follicles are ≥ 18–20 mm and have not ovulated, with P < 1 ng/ml, an HCG 10000 IU or Decapeptyl 0.2 mg injection is administered to induce follicular rupture. Cleavage-stage embryos were transferred on the third day after ovulation, while blastocysts were transferred on the fifth day. 5. Follow-up and Observation Indicators Serum HCG levels are measured 14 days after embryo transfer. For positive results, vaginal ultrasounds are conducted on days 28 and 35 post-transfer to confirm the presence of an intrauterine gestational sac and fetal heartbeat. Clinical pregnancy is defined as at least one gestational sac visible on ultrasound 4 to 6 weeks after transfer. Luteal phase support is gradually reduced from 30 to 35 days post-transfer and discontinued at 8 to 10 weeks of pregnancy. Deliveries at ≥ 28 weeks gestation with any signs of life are classified as live births. CLBR was defined as the delivery of at least one live birth during a complete IVF/ICSI cycle (including the fresh cycles and all subsequent FET cycles). The observation period was 2 years. The observation ends upon achieving at least one live birth or after all embryos from the oocyte retrieval cycle have been utilized [19]. Statistical Methods Data were analyzed using SPSS version 27.0. Continuous variables were reported as mean ± standard deviation or median (interquartile range). One-way ANOVA was used for normally distributed data with homogeneous variances, followed by the Tukey-Kramer test for post-hoc analysis. For normally distributed data with heterogeneity of variance, Welch's ANOVA and Games-Howell test were employed. Non-normally distributed data were analyzed using the Kruskal-Wallis test with appropriate post-hoc analysis. Categorical variables were expressed as frequencies (percentages), with intergroup comparisons made using chi-squared (χ2) tests. Adjustment variables included SUA, age, BMI, duration of infertility, AMH, baseline LH, baseline E2, baseline T, fasting glucose, fasting insulin, Gn dosage, Gn duration, and the number of transferable embryos. Correlation analyses (Pearson, Spearman, and partial) were conducted to explore factors related to SUA using SPSS and JASP Stats software. Smooth curve fitting was performed with Empower Stats software, based on R language, to analyze correlations between various factors and cumulative live birth rate (CLBR) as well as uric acid levels. A P-value of < 0.05 was deemed statistically significant. Results 1. Baseline Characteristics According to SUA Levels 2,841 PCOS women undergoing their first IVF/ICSI treatment were included in the study ( Fig. 1 ). The SUA, BMI, weight, baseline T, fasting glucose, and fasting insulin were significantly higher among groups 2, 3, and 4 compared with group 1 (P < 0.05). The estrogen levels were significantly higher among groups 2 and 4 than in group 1 (P < 0.05). (Table 1 ). The Gn dosage and Gn duration were significantly higher among groups 3 and 4 compared with group 1 (P < 0.05). (Table 2 ). Table 1 Comparison of Baseline Characteristics by Uric Acid Level Quartiles Baseline Characteristics Quartile 1 n = 714 Quartile 2 n = 709 Quartile 3 n = 710 Quartile 4 n = 708 P-value Serum Uric Acid(mg/dl) 232(211–248) 287(274–298)a 337(324–351)ab 419(388–467)abc <0.001 Age 28.01 ± 3.44 28.12 ± 3.55 28.01 ± 3.44 27.95 ± 3.54 0.837 BMI 22.90 ± 3.63 23.78 ± 3.62a 24.54 ± 3.68ab 25.53 ± 3.87abc <0.001 Weight (kg) 58.78 ± 10.03 61.10 ± 10.07a 63.06 ± 10.42ab 65.63 ± 11.24abc <0.001 Duration of Infertility 3(2–5) 3(2–5) 4(3–5) 4(2–5) 0.072 Type of Infertility 0.494 Primary Infertility 470(65.8) 451(63.6) 460(64.8) 477(67.4) Secondary Infertility 244(34.2) 258(36.4) 250(35.2) 231(32.6) AMH 10.09 ± 4.72 9.89 ± 4.77 10.00 ± 4.88 9.46 ± 4.49 0.094 Baseline LH 8.62(5.25–12.90) 8.14(5.42–12.31) 8.53(5.24–12.44) 8.04(5.12–11.38) 0.074 Baseline E2 41.37 ± 17.08 39.11 ± 14.65a 39.33 ± 15.27 38.22 ± 15.35a 0.003 Baseline T 0.51(0.30–1.23) 0.66(0.36–1.40)a 0.79(0.41–1.57)ab 1.02(0.49–1.73)abc <0.001 Fasting glucose 4.75 ± 0.61 4.81 ± 0.55a 4.90 ± 0.65ab 4.95 ± 0.64abc <0.001 Fasting insulin 12.77 ± 7.48 14.62 ± 7.85a 16.93 ± 8.55ab 19.94 ± 9.74abc <0.001 Note: Body Mass Index(BMI); Anti-Mullerian Hormone(AMH); luteinizing hormone (LH); oestrogen (E2); testosterone (T) Table 2 Comparison of Ovarian Stimulation and IVF Outcomes Across Quartiles of Serum Uric Acid Levels Item Quartile 1 Quartile 2 Quartile 3 Quartile 4 P-value Gn dosage(IU) 1425.0(1115.6-2071.9) 1587.5(1200.0-2231.3) 1693.8(1275.0-2475.0)a 1875.0(1350.0-2700.0)abc <0.001 Gn duration(days) 11.62 ± 3.08 11.92 ± 3.06 12.37 ± 3.08ab 12.91 ± 3.43abc <0.001 Protocol 0.161 GnRH-A protocol 68(9.5) 81(11.4) 56(7.9) 67(9.5) GnRH-a protocol 646(90.5) 628(88.6) 654(92.1) 641(90.5) EMT on hcg trigger day(mm) 10.70 ± 2.40 10.52 ± 2.35 10.62 ± 2.38 10.63 ± 2.44 0.569 Fertilization type 0.427 IVF 607(85.0) 620(87.4) 623(87.7) 614(86.7) ICSI 107(15.0) 89(12.6) 87(12.3) 94(13.3) No. of retrieved oocytes 14(10–19) 14(9–19) 14(10–19) 15(10–20) 0.095 No. of fertilized oocytes 8(5–12) 8(5–12) 8(5–13) 9(5–13) 0.348 No. of transferable embryo 4(2–6) 4(2–6) 4(2–6) 4(2–6) 0.097 Cumulative pregnancy rate (%) 86.4(617/714) 82.4(584/709) 81.4(578/710) 82.3(583/708) 0.055 Cumulative live birth rate (%) 77.2(551/714) 77.0(546/709) 72.7(516/710) 73.6(521/708) 0.106 clinical pregnancy rate (%) 69.1(739/1070) 69.7(707/1014) 69.8(643/921) 67.6(577/853) 0.740 miscarriage rate (%) 18.9(140/739) 18.7(132/707) 21.8(140/643) 18.9(109/577) 0.440 live birth rate (%) 56.0(599/1070) 56.7(575/1014) 54.6(503/921) 54.9(468/853) 0.837 Note: gonadotropins(Gn); endometrial thickness (EMT) ;gonadotropin-releasing hormone agonist (GnRH-a) ;gonadotropin-releasing hormone antagonist (GnRH-A); clinical pregnancy rate refers to clinical pregnancy rate per embryo transfer cycle; miscarriage rate refers to miscarriage rate per embryo transfer cycle; live birth rate refers to live birth rate per embryo transfer cycle 2. Logistic Regression Analysis of CLBR Multivariate logistic regression was used to analyze the factors influencing the cumulative live birth rate. BMI was negatively correlated with CLBR (OR 0.924, 95% CI: 0.880–0.969, P = 0.001), and the number of transferable embryos was positively correlated with CLBR (OR = 1.325, 95%CI = 1.249–1.405, P <0.001). (P < 0.01) However, SUA levels did not significantly impact CLBR (OR = 0.999, 95%CI: 0.998–1.001, P = 0.589). (Table 3 ). Table 3 Logistic Regression Analysis of Cumulative Live Birth Rate B S.E. Wald P-value OR(95%Confidence Interval) Serum Uric Acid(mg/dl) -0.0001 0.001 0.291 0.589 0.999(0.998–1.001) Age 0.002 0.022 0.010 0.921 1.002(0.961–1.045) BMI -0.079 0.024 10.549 0.001 0.924(0.880–0.969) Duration of Infertility -0.050 0.031 2.737 0.098 0.951(0.896–1.009) AMH -0.008 0.016 0.264 0.608 0.992(0.962–1.023) Baseline LH 0.010 0.015 0.417 0.518 1.010(0.980–1.040) Baseline E2 -0.006 0.005 1.268 0.260 0.994(0.985–1.004) Baseline T -0.161 0.154 1.087 0.297 0.851(0.629–1.152) Fasting glucose -0.077 0.127 0.364 0.546 0.926(0.722–1.188) Fasting insulin 0.008 0.010 0.597 0.440 1.008(0.988–1.028) Gn dosage(IU) 0.000 0.000 0.007 0.934 1.000(1.000–1.000) Gn duration(days) 0.047 0.048 0.982 0.322 1.048(0.955–1.151) No. of transferable embryo 0.281 0.030 88.435 <0.001 1.325(1.249–1.405) Constant 2.467 0.925 7.107 0.008 11.782 Note: Body Mass Index(BMI); Anti-Mullerian Hormone(AMH); luteinizing hormone (LH); oestrogen (E2); testosterone (T);gonadotropins(Gn) 3. Correlation Analysis and Curve Fitting Results Between SUA and Various Factors Pearson correlation analysis revealed that serum SUA was significantly positively correlated with BMI, weight, baseline T, fasting glucose, and fasting insulin (P < 0.01) and negatively correlated with AMH (P 0.05). However, SUA remained significantly positively correlated with BMI, weight, baseline T, and fasting insulin (P < 0.05) (Table 4 ). Table 4 Correlation Analysis of Serum Uric Acid Levels with Various Clinical Indicators Variable Pearson Correlation Analysis Partial correlation analysis R-value P-value R-value P-value BMI 0.233 <0.001 0.071a 0.012 AMH -0.045 0.026 -0.026b 0.359 Baseline T 0.206g <0.001 0.224c <0.001 Fasting glucose 0.112 <0.001 0.042d 0.142 Fasting insulin 0.327 <0.001 0.240e <0.001 Weight 0.219 <0.001 0.064f 0.023 Note: a Partial correlation analysis controlling for baseline AMH, baseline T, fasting glucose, and fasting insulin; b Partial correlation analysis controlling for BMI, baseline T, fasting glucose, and fasting insulin; c Partial correlation analysis controlling for BMI, AMH, fasting glucose, and fasting insulin based on Spearman Correlation Analysis; d Partial correlation analysis controlling for BMI, AMH, baseline T, and fasting insulin; e Partial correlation analysis controlling for BMI, AMH, baseline T, and fasting glucose; f Partial correlation analysis controlling for AMH, baseline T, fasting glucose, and fasting insulin;g Spearman Correlation Analysis Note:Body Mass Index(BMI); Anti-Mullerian Hormone(AMH); testosterone (T) Figure 2 depicted the linear relationships between BMI, weight, fasting insulin, and baseline testosterone with SUA as determined by curve fitting. The analysis indicated that as BMI, weight, fasting insulin, and baseline T increased, SUA levels also exhibited a tendency to rise. 4. Curve Fitting Between Various Factors and CLBR Figure 3 presented the curve fitting between various factors and the CLBR after adjusting for confounding variables. Figures 3 B and 3 C indicated that BMI and weight were linearly related to CLBR, with a decline in the CLBR as BMI and weight increased. Figures 3 A, 3 D, and 3 E show no significant correlation between SUA, baseline T, fasting insulin, and CLBR. Discussion In this large retrospective cohort study, we found that SUA levels do not have a significant impact on CLBR in women with PCOS undergoing IVF-ET. Our data also support previous studies showing that SUA positively correlated with BMI, weight, and baseline T, all associated with metabolic syndrome [20]. Additionally, our findings emphasize the significant effect of BMI and weight on CLBR, with increases in both BMI and weight associated with a decline in CLBR, consistent with prior research [13]. Furthermore, our study indicates that high BMI (BMI ≥ 25kg/m 2 ) and obesity contribute to increased SUA levels. Obesity and high BMI are associated with hyperuricemia and a decreased CLBR. After adjusting for confounding factors, SUA itself was found to have no significant effect on CLBR in women with PCOS undergoing IVF-ET. A cross-sectional survey conducted in the United States demonstrated a positive correlation between BMI dietary energy intake and serum SUA levels [21]. Additionally, a study from China involving 15,959 adults identified a correlation between SUA levels and obesity. Overweight and obese individuals had higher SUA levels than normal BMI (β = 0.451, 95% CI: 0.357 to 0.546, P < 0.00001; β = 0.853, 95% CI: 0.760 to 0.946, P < 0.00001; respectively) [22]. Previous research has established that obesity significantly affects SUA levels in women with PCOS [23]. Hosoyamada et al. found a positive correlation between serum total testosterone and SUA levels in women with PCOS [24]. Consistent with these findings, our study also shows that SUA levels in PCOS women tend to increase with rising BMI, weight, insulin levels, and baseline T. Hyperuricemia can result from excessive production or intake of SUA or reduced excretion. The potential mechanisms are as follows: First, the excessive intake of high-fructose foods can impair the small intestine's ability to clear fructose. Unmetabolized fructose, absorbed by the small intestine into the liver, stimulates the breakdown of purine nucleotides and the synthesis of SUA from amino acid precursors like glycine, leading to increased uric acid production [25,26]. Second, overproduction of SUA can occur due to increased energy intake, which contributes to obesity and hyperlipidemia, thereby enhancing purine synthesis and SUA production. Increased visceral fat raises free fatty acid levels in the portal vein system, which in turn activates hepatic fatty acid synthesis and the 5-phosphoribosyl 1-pyrophosphate (PRPP) pathway, resulting in increased synthesis of triglycerides and SUA [27]. Lastly, reduced uric acid excretion can be attributed to obesity-induced increases in leptin levels. Leptin directly inhibits the renal tubules' ability to excrete SUA [28]. It stimulates renin release at the renal level through the sympathetic nervous system, increasing sodium and SUA reabsorption in the proximal renal tubules and reducing uric acid excretion[29,30]. Additionally, obesity is strongly correlated with elevated insulin levels and insulin resistance [31]. Insulin promotes androgen synthesis [32], and elevated androgens can exacerbate insulin resistance in skeletal muscle and fat cells, leading to hyperinsulinemia by reducing the hepatic breakdown rate of insulin [33]. Insulin resistance or hyperinsulinemia may also activate the renin-angiotensin-aldosterone system, resulting in decreased renal blood flow and reduced uric acid excretion, increasing SUA levels [34–37](Fig. 4 ). Hyperandrogenism is a prominent feature of Polycystic Ovary Syndrome (PCOS). Multiple studies have demonstrated that androgens can promote uric acid production and decrease excretion, thereby contributing to hyperuricemia. For instance, Pizzichini et al. reported that testosterone increases the mRNA and protein levels of the sodium-coupled monocarboxylate transporter 1 (Smct1) while decreasing the mRNA and protein expression levels of glucose transporter 9 (Glut9). These changes induce functional alterations in the renal tubular reabsorption system, leading to increased SUA reabsorption [38]. Additionally, animal studies have shown that testosterone elevates SUA levels by enhancing the liver metabolism of purine nucleotides and stimulating renal purine metabolism [39,40]. Moreover, it has been observed that anti-androgen contraceptive pills significantly lower SUA levels in obese women with PCOS [24], further suggesting that androgens influence SUA levels in this population (Fig. 4 ). In women with PCOS, the inherent predisposition to obesity, insulin resistance, and hyperandrogenemia are significant risk factors for hyperuricemia. Therefore, it is essential to determine whether obesity, insulin levels, or androgen levels influence assisted reproductive outcomes or if SUA itself affects these outcomes in women with PCOS. This investigation represents one of the primary objectives of our study. Current research indicates that metabolic syndrome-related factors, such as obesity and BMI, are critical determinants of assisted reproductive outcomes in women with PCOS, with metabolic syndrome as an independent risk factor for CLBR [13,41,42]. A study by Rafael et al. demonstrated that overweight and obese women had significantly lower CLBRs compared to women of normal weight [43]. Additionally, a study involving 1,395 women with PCOS found that lean PCOS women exhibited higher CLBRs, while obese PCOS women had a significantly increased miscarriage rate compared to their lean counterparts[44]. Another investigation encompassing 5,016 PCOS women revealed a linear negative correlation between CLBR across multiple IVF cycles and BMI [45]. A study conducted in China categorized PCOS women into higher and lower BMI groups, finding that the clinical pregnancy and live birth rates were lower in the higher BMI group compared to the lower BMI group [46]. Our study aligns with these findings, showing that BMI and weight significantly influence CLBR in PCOS women undergoing ART, with CLBR decreasing as BMI and weight increase. The impact of hyperandrogenemia on assisted reproductive outcomes remains contentious. Some studies suggest that PCOS with elevated androgens is associated with a significantly lower CLBR compared to the normal androgen PCOS phenotype [47]. However, these studies were limited by small sample sizes and did not encompass all PCOS phenotypes. A recent meta-analysis found that the high androgen PCOS group had a higher miscarriage rate compared to the normal androgen PCOS group(RR: 1.56, 95% CI: 1.13, 2. 16), though no significant differences were observed in clinical pregnancy rates (RR: 0.88, 95% CI: 0.77, 1.01) or live birth rates (RR: 0.79, 95% CI: 0.55, 1. 11) between the two groups [48]. Our study aligns with these findings, showing no significant correlation between baseline T levels and CLBR. Current research regarding the impact of SUA levels on assisted reproductive outcomes is limited. A study by Yang, H et al. reported that elevated SUA levels are associated with decreased probabilities of live birth and clinical pregnancy, as well as an increased risk of low birth weight in women with polycystic ovary syndrome. However, this study had a small sample size. It spanned an extended period, which may have introduced variability in measurement indicators, diagnostic criteria for the inclusion and exclusion of diseases, and IVF treatment protocols. Additionally, the study did not further investigate the impact of BMI and insulin levels on the outcomes [12]. Another investigation indicated that pregnant women with preeclampsia exhibit elevated SUA levels and a higher risk of low birth weight. However, no statistical difference in live birth rates was observed compared to normal pregnant women [49]. Our study indicates that, after adjusting for confounding factors, varying SUA levels do not significantly impact the CLBR in women with PCOS undergoing IVF. Our analysis shows that SUA levels positively correlate with BMI, weight, baseline T, and fasting insulin. Further examination of the associations between CLBR, SUA, and BMI revealed that SUA does not affect CLBR in PCOS patients, whereas BMI and weight were negatively correlated with CLBR. Consequently, we propose that hyperuricemia may be a concomitant condition associated with obesity, insulin resistance, and hyperandrogenemia rather than a direct determinant of CLBR in PCOS women undergoing IVF-ET. This study investigated the impact of SUA levels, BMI, and insulin levels on the CLBR in women with PCOS. The primary strengths of our study include its conduction at two major reproductive centers, where we collected data over a relatively short period and with a large sample size. This approach enhances the representativeness and reliability of the data. Additionally, our data were harmonized before integration concerning treatment processes, departmental protocols, and key indicators such as SUA testing, PCOS diagnostic criteria, ultrasound measurement, hormone test sensitivity, controlled ovarian stimulation (COS) protocols, and laboratory scoring standards. This harmonization aimed to minimize systematic errors. Furthermore, our study not only examined the influence of varying SUA levels on CLBR in the PCOS population but also further elucidated other factors affecting SUA levels and CLBR through correlation analysis and curve fitting—this comprehensive exploration aimed to identify the underlying factors influencing CLBR in PCOS women undergoing IVF-ET. Despite establishing strict inclusion and exclusion criteria, the retrospective design of this study presents several unavoidable limitations that may affect the reliability of our conclusions. The PCOS women included in this study were diagnosed using the Rotterdam criteria, which may not apply to those diagnosed by other standards. Additionally, the study population included women under 40, with pituitary down-regulation protocols used in 90.4% (2569/2841) of the ovulation induction schemes. Consequently, the applicability of our findings to older women (≥ 40 years) or those undergoing different ovulation induction protocols requires further investigation. Conclusion SUA levels do not significantly impact the CLBR in PCOS women undergoing IVF-ET. Instead, BMI and weight negatively correlated with SUA levels and CLBR. Therefore, strategies focused on weight reduction may serve as effective therapeutic interventions to improve the CLBR in PCOS women. However, our conclusions require validation through further prospective, multicenter studies. Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author contributions All authors contributed to the study conception and design. SZ and LT supervised the study, including procedures, conception, design, and completion. SX and LT were responsible for collecting information. SX and TZ contributed to the analysis data and drafted the manuscript. NJ and ML participated in revising the article. All authors contributed to the article and approved the submitted version. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Reproductive Medicine Ethics Committee of Henan Provincial People's Hospital (SYSZ-LL-2021091501). Acknowledgments We thank all the laboratory staff of our reproductive centers for their contribution to this work. We also acknowledge the patients who took part in this study. Consent to participate Informed consent was obtained from all individual participants included in the study. Data Availability Some or all datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request. References Lizneva D, Suturina L, Walker W, Brakta S, Gavrilova-Jordan L, Azziz R. Criteria, prevalence, and phenotypes of polycystic ovary syndrome. Fertil Steril. 106(1),6-15 (2016). https://doi.org/10.1016/j.fertnstert.2016.05.003. Mu L, Pan J, Yang L, Chen Q, Chen Y, Teng Y, Wang P, Tang R, Huang X, Chen X, Yang H. Association between the prevalence of hyperuricemia and reproductive hormones in polycystic ovary syndrome. Reprod Biol Endocrinol. 16(1),104 (2018). https://doi.org/10.1186/s12958-018-0419-x. Cooney LG, Dokras A. Beyond fertility: polycystic ovary syndrome and long-term health. 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Association between hyperandrogenism and adverse pregnancy outcomes in patients with different polycystic ovary syndrome phenotypes undergoing in vitro fertilization/intracytoplasmic sperm injection: a systematic review and meta-analysis. Gynecol Endocrinol. 37(8),694-701 (2021). https://doi.org/10.1080/09513590.2021.1897096. Ayankunle OM, Adeniyi AA, Adewara OE, Awoyinka SB, Adebara IO, Adeyemo OT, Bakare A, Olumodeji AM, Jimoh AK. Maternal serum uric acid: a reliable prognostic indicator of foetal outcome among pre-eclamptic patients in a low resource setting. J Matern Fetal Neonatal Med. 35(25),7695-700 (2022). https://doi.org/10.1080/14767058.2021.1960969. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5873869","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":406240493,"identity":"2db87216-f6a7-4070-bf05-2953438114d4","order_by":0,"name":"Siyue Xu","email":"","orcid":"","institution":"Henan Provincial People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Siyue","middleName":"","lastName":"Xu","suffix":""},{"id":406240495,"identity":"53a1b362-ad49-4ba6-a7fb-ea8da557cfa4","order_by":1,"name":"Ting Zhang","email":"","orcid":"","institution":"The Third Hospital of Changsha","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Zhang","suffix":""},{"id":406240497,"identity":"7d6055a1-de16-495d-be8a-436c318d269f","order_by":2,"name":"Nan Jia","email":"","orcid":"","institution":"Henan Provincial People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nan","middleName":"","lastName":"Jia","suffix":""},{"id":406240499,"identity":"65aec054-7b9d-49cc-9279-95e94d9c2fe8","order_by":3,"name":"Meng Li","email":"","orcid":"","institution":"Henan Provincial People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Li","suffix":""},{"id":406240500,"identity":"c72d06f9-8a17-4ad6-9b8a-f8346c3a0de5","order_by":4,"name":"Lifeng Tian","email":"","orcid":"","institution":"Jiangxi Maternal and Child Health Hospital, Nanchang Medical College","correspondingAuthor":false,"prefix":"","firstName":"Lifeng","middleName":"","lastName":"Tian","suffix":""},{"id":406240501,"identity":"55062fd3-79bd-4d6f-bed1-6c103bb7d3c8","order_by":5,"name":"Shaodi Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBAC+xlg6gBjPzPzwQdEaWGEaZnZzpZsQJqWDed5zASI0sIs3fzs4Zc/d2Q3H2YwY2CosYkmqIVN5pi5sWzbM+NthxnSHjAcS8ttIKSFRyLBTFqy4XAiUMtxA8aGw4S1SEikf5OW+HM4cXMzY5sEUVoMJHLMJD+wHU7cwMzMRrSWMmnGtsPGMw6zMRskEOMX+xnp2yR//Dks299//uODDzU2hLWAADMPjJVAjHIQYPxBrMpRMApGwSgYmQAAfC9Cqdg76KQAAAAASUVORK5CYII=","orcid":"","institution":"Henan Provincial People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Shaodi","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-01-21 13:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5873869/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5873869/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74960159,"identity":"01bbdd42-d8f4-47e5-9b62-d83d36d2bac5","added_by":"auto","created_at":"2025-01-28 18:51:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":28928,"visible":true,"origin":"","legend":"\u003cp\u003eData Screening Process Flowchart\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5873869/v1/f1279647f10f1bb4676a8cb5.png"},{"id":74961482,"identity":"94f1c70c-72f8-4c15-acc0-085367afdb9b","added_by":"auto","created_at":"2025-01-28 18:59:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":655579,"visible":true,"origin":"","legend":"\u003cp\u003eA represents the curve fitting of BMI and serum uric acid; B represents the curve fitting of weight and serum uric acid; C represents the curve fitting of baseline T and serum uric acid; D represents the curve fitting of fasting insulin and serum uric acid\u003c/p\u003e","description":"","filename":"21.png","url":"https://assets-eu.researchsquare.com/files/rs-5873869/v1/2a106ef96c54f1c2cef509af.png"},{"id":74961893,"identity":"f183554d-8f29-48c3-9399-6fd5a12c2a61","added_by":"auto","created_at":"2025-01-28 19:07:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":570281,"visible":true,"origin":"","legend":"\u003cp\u003e- A shows the curve fitting between serum uric acid and cumulative live birth rate after adjusting for confounding factors such as age, BMI, AMH, baseline T, fasting glucose, fasting insulin, and number of transferable embryo.\u003c/p\u003e\n\u003cp\u003e- B shows the curve fitting between BMI and cumulative live birth rate after adjusting for serum uric acid, age, AMH, baseline T, fasting glucose, fasting insulin, and number of transferable embryo as confounding factors.\u003c/p\u003e\n\u003cp\u003e- C shows the curve fitting between weight and cumulative live birth rate after adjusting for serum uric acid, age, AMH, baseline T, fasting glucose, fasting insulin, and number of transferable embryo as confounding factors.\u003c/p\u003e\n\u003cp\u003e- D shows the curve fitting between baseline T and cumulative live birth rate after adjusting for serum uric acid, age, BMI, AMH, fasting glucose, fasting insulin, and number of transferable embryo as confounding factors.\u003c/p\u003e\n\u003cp\u003e- E shows the curve fitting between fasting insulin and cumulative live birth rate after adjusting for serum uric acid, age, AMH, fasting glucose, baseline T, and number of transferable embryo as confounding factors.\u003c/p\u003e","description":"","filename":"31.png","url":"https://assets-eu.researchsquare.com/files/rs-5873869/v1/09c7c8c7683ed2209752886e.png"},{"id":74960160,"identity":"28b4dc20-475f-438b-8b59-df5777ce5c48","added_by":"auto","created_at":"2025-01-28 18:51:34","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":118468,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolic relationship diagram of obesity, insulin resistance, high fructose intake, and hyperandrogenism with hyperuricemia\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5873869/v1/37861247dbc8a3b2896bc795.png"},{"id":76394365,"identity":"bcb242b9-c498-497e-8272-89e69a7cb0ad","added_by":"auto","created_at":"2025-02-16 13:01:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2098258,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5873869/v1/5d9b546b-f254-46b4-9d1a-eb64da8fb47f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of serum uric acid Levels on the Cumulative Live Birth Rate in Women with Polycystic Ovary Syndrome Undergoing In Vitro Fertilization-Embryo Transfer (IVF-ET)","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePolycystic ovary syndrome (PCOS) is a common endocrine disorder primarily characterized by infrequent ovulation/anovulation, hyperandrogenism, and polycystic ovarian morphology, with a prevalence rate of 4%-21% among women of reproductive age[1] PCOS is one of the leading causes of ovulatory infertility, making assisted reproductive technology (ART) a significant option for women with PCOS. Additionally, PCOS often coexists with metabolic disturbances such as obesity, hypertension, dyslipidemia, and elevated serum uric acid (SUA) levels [2\u0026ndash;4].\u003c/p\u003e \u003cp\u003eSUA is the end product of endogenous metabolic production and the breakdown of dietary purines. SUA levels are influenced by the endogenous metabolism of the liver, kidneys, and small intestine and the exogenous intake of high-fructose and high-purine foods [5]. Unhealthy lifestyles and dietary habits in modern society have led to an increased prevalence of hyperuricemia. Elevated SUA levels have been implicated in the development of various diseases. Current research indicates that elevated SUA levels are associated with insulin resistance, obesity [6], hypertension, type 2 diabetes [7], and cardiovascular diseases[8].\u003c/p\u003e \u003cp\u003eRecently, the relationship between hyperuricemia and infertility has gained increasing attention. Data from the National Health and Nutrition Examination Survey (NHANES) conducted by the Centers for Disease Control and Prevention (CDC) in the United States from 2013 to 2020 showed that the incidence of female infertility increased significantly with rising SUA levels [9]. Another study based on NHANES data, after adjusting for confounding factors such as age, race, marital status, smoking, alcohol, history of pregnancy, history of diabetes, history of hypertension, fasting glucose, total cholesterol, serum creatinine, low-density lipoprotein cholesterol, direct high-density lipoprotein cholesterol, glycohemoglobin, and body mass index(BMI) showed that the risk of infertility in the higher uric acid group was 83% greater compared to the lower uric acid group [10]. Research by Durmus U and colleagues has demonstrated that SUA levels are significantly elevated in the PCOS population and correlate with the severity of the disease [11]. Currently, there are few studies on the impact of SUA levels on assisted reproductive outcomes in infertile women with PCOS. SUA levels have been shown to influence clinical pregnancy rate, live birth rate, and instances of low birth weight in infertile women with PCOS [12]. A multicenter randomized trial involving 1,508 women with PCOS indicated that metabolic syndrome negatively correlates with the cumulative live birth rate (CLBR) among women with PCOS and metabolic syndrome [13], and SUA is related to metabolic syndrome factors such as high BMI, obesity, and insulin resistance [14]. Women with PCOS often have concurrent endocrine and metabolic abnormalities, such as hyperandrogenemia and hyperinsulinemia. Is SUA associated with these endocrine and metabolic disturbances, and do these factors influence assisted reproductive outcomes? Furthermore, is SUA an independent factor affecting assisted reproductive outcomes? These questions remain unresolved in current research.\u003c/p\u003e \u003cp\u003eThis study analyzes the clinical data of 2,841 PCOS women to explore the impact of SUA levels on CLBR in PCOS women, thereby clarifying the main factors affecting CLBR in PCOS women.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eStudy Population\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThis study involved 4,441 women undergoing their first IVF/ICSI treatment at the Reproductive Centers of Henan Provincial People's Hospital and Jiangxi Provincial Maternal and Child Health Hospital from January 2016 to December 2021. Inclusion criteria included: (1) diagnosis of PCOS according to the Rotterdam criteria [15]; (2) age\u0026thinsp;\u0026lt;\u0026thinsp;40 years; (3) women undergoing their first IVF/ICSI cycle. Exclusion criteria included: (1) chromosomal abnormalities in either partner (n\u0026thinsp;=\u0026thinsp;426); (2) cycles involving Preimplantation genetic testing (PGT) (n\u0026thinsp;=\u0026thinsp;31), donor sperm/oocytes cycles or frozen oocytes cycles(n\u0026thinsp;=\u0026thinsp;20), severe male factor (n\u0026thinsp;=\u0026thinsp;70); (3) uterine malformations (n\u0026thinsp;=\u0026thinsp;8), uterine fibroids (n\u0026thinsp;=\u0026thinsp;16), adenomyosis or endometriosis (n\u0026thinsp;=\u0026thinsp;43); (4) factors affecting the uterine lining, such as endometrial polyps (n\u0026thinsp;=\u0026thinsp;109), intrauterine adhesions and history of endometrial tuberculosis (n\u0026thinsp;=\u0026thinsp;59), hydrosalpinx reflux (n\u0026thinsp;=\u0026thinsp;13); (5) thyroid dysfunction (n\u0026thinsp;=\u0026thinsp;14), diabetes (n\u0026thinsp;=\u0026thinsp;7), hyperprolactinemia (n\u0026thinsp;=\u0026thinsp;1); (6) recurrent miscarriage (n\u0026thinsp;=\u0026thinsp;33); (7) cycles with no oocytes retrieval (n\u0026thinsp;=\u0026thinsp;4), canceled cycles (n\u0026thinsp;=\u0026thinsp;25); (8) cycles with remaining embryos not followed up to live birth (n\u0026thinsp;=\u0026thinsp;540); (9) cycles with incomplete or anomalous data (n\u0026thinsp;=\u0026thinsp;181). Based on SUA levels, women were divided into four quartiles: Quartile 1 (SUA\u0026thinsp;\u0026le;\u0026thinsp;262 mg/dl, n\u0026thinsp;=\u0026thinsp;714), Quartile 2 (262 mg/dl\u0026thinsp;\u0026lt;\u0026thinsp;SUA\u0026thinsp;\u0026le;\u0026thinsp;310 mg/dl, n\u0026thinsp;=\u0026thinsp;709), Quartile 3 (310 mg/dl\u0026thinsp;\u0026lt;\u0026thinsp;SUA\u0026thinsp;\u0026le;\u0026thinsp;367 mg/dl, n\u0026thinsp;=\u0026thinsp;710), and Quartile 4 (SUA\u0026thinsp;\u0026gt;\u0026thinsp;367 mg/dl, n\u0026thinsp;=\u0026thinsp;708).\u003c/p\u003e \u003cp\u003e2. Biochemical Indicator Testing\u003c/p\u003e \u003cp\u003eParticipants in this study were required to fast for at least 8 hours before blood drawing. The patient's blood was collected and placed in a 37\u0026deg;C incubator for about 20 minutes, then centrifuged at 3500 rpm with a centrifugal force of 2190xg for 15 minutes. After centrifugation, the supernatant was collected for testing. Sex hormones and fasting insulin were measured using electrochemiluminescence (Swiss Roche E602). Fasting glucose and SUA were determined using an automatic analyzer (American Abbott Biochemical Analyzer c16000). The normal range for uric acid, as measured by the biochemical analyzer c16000, was 155\u0026ndash;357 umol/L. In terms of precision, both intra-assay and inter-assay variability for sex hormone measurements were less than 12%. For other biochemical parameters, intra-assay and inter-assay variability were less than 10%.\u003c/p\u003e \u003cp\u003e3. Ovulation Induction Protocol\u003c/p\u003e \u003cp\u003eThe GnRH agonist protocol and the GnRH antagonist protocol all refer to previously published articles from our center[16].\u003c/p\u003e \u003cp\u003e4. Embryo Culture, Embryo Transfer, and Luteal Phase Support\u003c/p\u003e \u003cp\u003eEach cleavage-stage embryo was graded according to previously published articles from our center[17]. Blastocyst scoring was performed according to the Gardner scoring system [18].\u003c/p\u003e \u003cp\u003eThe criteria for fresh embryo transfer included an endometrial thickness of \u0026ge;\u0026thinsp;8 mm with a uniform echo, P\u0026thinsp;\u0026lt;\u0026thinsp;1.5 \u0026micro;g/L, and no infections, OHSS risk, or significant medical histories. 1\u0026ndash;2 cleavage embryos or blastocyst were transferred. The remaining embryos or blastocysts meeting cryopreservation criteria were vitrified for future frozen-thawed embryo transfer (FET). Women undergoing fresh transfer began treatment with oral dydrogesterone (Duphaston, 10 mg/tablet, Abbott Laboratories) at 10 mg twice daily, alongside vaginal progesterone slow-release gel (Crinone, 90 mg/applicator, Merck Serono) at 90 mg once daily, starting on the day of oocyte retrieval.\u003c/p\u003e \u003cp\u003eFET was performed in patients who did not achieve a live birth after a fresh transfer and had remaining embryos or who did not undergo a fresh cycle transfer. The decision to use an HRT protocol and an ovulation induction protocol was based on the patient's menstrual and ovulation status.\u003c/p\u003e \u003cp\u003eThe HRT protocol refer to previously published articles from our center[17]. For the ovulation induction protocol, letrozole (Femara, 2.5 mg/tablet, Jiangsu Hengrui Medicine Co., Ltd.) 2.5 mg/day is administered orally for five consecutive days starting from days 3\u0026ndash;5 of the menstrual cycle. A week later, the vaginal ultrasound was examined, and according to the situation of follicles, it was decided whether to inject HMG (Human menopausal gonadotropin, 75 units/branch, Zhuhai Lizon Pharmaceutical). Follicles measuring 16 mm or larger are monitored until ovulation occurs. If the follicles are \u0026ge;\u0026thinsp;18\u0026ndash;20 mm and have not ovulated, with P\u0026thinsp;\u0026lt;\u0026thinsp;1 ng/ml, an HCG 10000 IU or Decapeptyl 0.2 mg injection is administered to induce follicular rupture. Cleavage-stage embryos were transferred on the third day after ovulation, while blastocysts were transferred on the fifth day.\u003c/p\u003e \u003cp\u003e5. Follow-up and Observation Indicators\u003c/p\u003e \u003cp\u003eSerum HCG levels are measured 14 days after embryo transfer. For positive results, vaginal ultrasounds are conducted on days 28 and 35 post-transfer to confirm the presence of an intrauterine gestational sac and fetal heartbeat. Clinical pregnancy is defined as at least one gestational sac visible on ultrasound 4 to 6 weeks after transfer. Luteal phase support is gradually reduced from 30 to 35 days post-transfer and discontinued at 8 to 10 weeks of pregnancy. Deliveries at \u0026ge;\u0026thinsp;28 weeks gestation with any signs of life are classified as live births.\u003c/p\u003e \u003cp\u003eCLBR was defined as the delivery of at least one live birth during a complete IVF/ICSI cycle (including the fresh cycles and all subsequent FET cycles). The observation period was 2 years. The observation ends upon achieving at least one live birth or after all embryos from the oocyte retrieval cycle have been utilized [19].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Methods\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS version 27.0. Continuous variables were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range). One-way ANOVA was used for normally distributed data with homogeneous variances, followed by the Tukey-Kramer test for post-hoc analysis. For normally distributed data with heterogeneity of variance, Welch's ANOVA and Games-Howell test were employed. Non-normally distributed data were analyzed using the Kruskal-Wallis test with appropriate post-hoc analysis. Categorical variables were expressed as frequencies (percentages), with intergroup comparisons made using chi-squared (χ2) tests. Adjustment variables included SUA, age, BMI, duration of infertility, AMH, baseline LH, baseline E2, baseline T, fasting glucose, fasting insulin, Gn dosage, Gn duration, and the number of transferable embryos. Correlation analyses (Pearson, Spearman, and partial) were conducted to explore factors related to SUA using SPSS and JASP Stats software. Smooth curve fitting was performed with Empower Stats software, based on R language, to analyze correlations between various factors and cumulative live birth rate (CLBR) as well as uric acid levels. A P-value of \u0026lt;\u0026thinsp;0.05 was deemed statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e1. Baseline Characteristics According to SUA Levels\u003c/p\u003e \u003cp\u003e2,841 PCOS women undergoing their first IVF/ICSI treatment were included in the study ( Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The SUA, BMI, weight, baseline T, fasting glucose, and fasting insulin were significantly higher among groups 2, 3, and 4 compared with group 1 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The estrogen levels were significantly higher among groups 2 and 4 than in group 1 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Gn dosage and Gn duration were significantly higher among groups 3 and 4 compared with group 1 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Baseline Characteristics by Uric Acid Level Quartiles\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuartile 1\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;714\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuartile 2\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;709\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuartile 3\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;710\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuartile 4\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;708\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Uric Acid(mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232(211\u0026ndash;248)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e287(274\u0026ndash;298)a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e337(324\u0026ndash;351)ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e419(388\u0026ndash;467)abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.01\u0026thinsp;\u0026plusmn;\u0026thinsp;3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.12\u0026thinsp;\u0026plusmn;\u0026thinsp;3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.01\u0026thinsp;\u0026plusmn;\u0026thinsp;3.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.54\u0026thinsp;\u0026plusmn;\u0026thinsp;3.68ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.78\u0026thinsp;\u0026plusmn;\u0026thinsp;10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.10\u0026thinsp;\u0026plusmn;\u0026thinsp;10.07a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.06\u0026thinsp;\u0026plusmn;\u0026thinsp;10.42ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.63\u0026thinsp;\u0026plusmn;\u0026thinsp;11.24abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of Infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(3\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(2\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary Infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e470(65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e451(63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e460(64.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e477(67.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary Infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e244(34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258(36.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250(35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e231(32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.09\u0026thinsp;\u0026plusmn;\u0026thinsp;4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.89\u0026thinsp;\u0026plusmn;\u0026thinsp;4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.46\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline LH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.62(5.25\u0026ndash;12.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.14(5.42\u0026ndash;12.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.53(5.24\u0026ndash;12.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.04(5.12\u0026ndash;11.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline E2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.37\u0026thinsp;\u0026plusmn;\u0026thinsp;17.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.11\u0026thinsp;\u0026plusmn;\u0026thinsp;14.65a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.33\u0026thinsp;\u0026plusmn;\u0026thinsp;15.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.22\u0026thinsp;\u0026plusmn;\u0026thinsp;15.35a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51(0.30\u0026ndash;1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66(0.36\u0026ndash;1.40)a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79(0.41\u0026ndash;1.57)ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02(0.49\u0026ndash;1.73)abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.77\u0026thinsp;\u0026plusmn;\u0026thinsp;7.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.62\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.93\u0026thinsp;\u0026plusmn;\u0026thinsp;8.55ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.94\u0026thinsp;\u0026plusmn;\u0026thinsp;9.74abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Body Mass Index(BMI); Anti-Mullerian Hormone(AMH); luteinizing hormone (LH); oestrogen (E2); testosterone (T)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Ovarian Stimulation and IVF Outcomes Across Quartiles of Serum Uric Acid Levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuartile 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuartile 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuartile 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuartile 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGn dosage(IU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1425.0(1115.6-2071.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1587.5(1200.0-2231.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1693.8(1275.0-2475.0)a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1875.0(1350.0-2700.0)abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGn duration(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.62\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.92\u0026thinsp;\u0026plusmn;\u0026thinsp;3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08ab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.91\u0026thinsp;\u0026plusmn;\u0026thinsp;3.43abc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtocol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGnRH-A protocol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81(11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67(9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGnRH-a protocol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e646(90.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e628(88.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e654(92.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e641(90.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEMT on hcg trigger day(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFertilization type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIVF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e607(85.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e620(87.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e623(87.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e614(86.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107(15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89(12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87(12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94(13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of retrieved oocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(10\u0026ndash;19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(9\u0026ndash;19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(10\u0026ndash;19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15(10\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of fertilized oocytes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(5\u0026ndash;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(5\u0026ndash;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(5\u0026ndash;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9(5\u0026ndash;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of transferable embryo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(2\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(2\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(2\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(2\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCumulative pregnancy rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.4(617/714)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.4(584/709)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.4(578/710)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.3(583/708)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCumulative live birth rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.2(551/714)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.0(546/709)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.7(516/710)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.6(521/708)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eclinical pregnancy rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.1(739/1070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.7(707/1014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.8(643/921)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.6(577/853)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.740\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emiscarriage rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.9(140/739)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.7(132/707)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.8(140/643)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.9(109/577)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elive birth rate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.0(599/1070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.7(575/1014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.6(503/921)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.9(468/853)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: gonadotropins(Gn); endometrial thickness (EMT) ;gonadotropin-releasing hormone agonist (GnRH-a) ;gonadotropin-releasing hormone antagonist (GnRH-A); clinical pregnancy rate refers to clinical pregnancy rate per embryo transfer cycle; miscarriage rate refers to miscarriage rate per embryo transfer cycle; live birth rate refers to live birth rate per embryo transfer cycle\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e2. Logistic Regression Analysis of CLBR\u003c/p\u003e \u003cp\u003eMultivariate logistic regression was used to analyze the factors influencing the cumulative live birth rate. BMI was negatively correlated with CLBR (OR 0.924, 95% CI: 0.880\u0026ndash;0.969, P\u0026thinsp;=\u0026thinsp;0.001), and the number of transferable embryos was positively correlated with CLBR (OR\u0026thinsp;=\u0026thinsp;1.325, 95%CI\u0026thinsp;=\u0026thinsp;1.249\u0026ndash;1.405, P \u0026lt;0.001). (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) However, SUA levels did not significantly impact CLBR (OR\u0026thinsp;=\u0026thinsp;0.999, 95%CI: 0.998\u0026ndash;1.001, P\u0026thinsp;=\u0026thinsp;0.589). (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic Regression Analysis of Cumulative Live Birth Rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR(95%Confidence Interval)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum Uric Acid(mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.999(0.998\u0026ndash;1.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.002(0.961\u0026ndash;1.045)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.924(0.880\u0026ndash;0.969)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of Infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.951(0.896\u0026ndash;1.009)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.992(0.962\u0026ndash;1.023)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline LH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.010(0.980\u0026ndash;1.040)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline E2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.994(0.985\u0026ndash;1.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.851(0.629\u0026ndash;1.152)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.926(0.722\u0026ndash;1.188)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.008(0.988\u0026ndash;1.028)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGn dosage(IU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.000(1.000\u0026ndash;1.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGn duration(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.048(0.955\u0026ndash;1.151)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of transferable embryo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.325(1.249\u0026ndash;1.405)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.782\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Body Mass Index(BMI); Anti-Mullerian Hormone(AMH); luteinizing hormone (LH); oestrogen (E2); testosterone (T);gonadotropins(Gn)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e3. Correlation Analysis and Curve Fitting Results Between SUA and Various Factors\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003ePearson correlation analysis revealed that serum SUA was significantly positively correlated with BMI, weight, baseline T, fasting glucose, and fasting insulin (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and negatively correlated with AMH (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Partial correlation analysis, controlling for the effects of related factors, showed no significant correlation between SUA and AMH or fasting glucose (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, SUA remained significantly positively correlated with BMI, weight, baseline T, and fasting insulin (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Analysis of Serum Uric Acid Levels with Various Clinical Indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePearson Correlation Analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePartial correlation analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.071a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.026b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.206g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.224c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting glucose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.042d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting insulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.240e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.064f\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: a Partial correlation analysis controlling for baseline AMH, baseline T, fasting glucose, and fasting insulin; b Partial correlation analysis controlling for BMI, baseline T, fasting glucose, and fasting insulin; c Partial correlation analysis controlling for BMI, AMH, fasting glucose, and fasting insulin based on Spearman Correlation Analysis; d Partial correlation analysis controlling for BMI, AMH, baseline T, and fasting insulin; e Partial correlation analysis controlling for BMI, AMH, baseline T, and fasting glucose; f Partial correlation analysis controlling for AMH, baseline T, fasting glucose, and fasting insulin;g Spearman Correlation Analysis\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eNote:Body Mass Index(BMI); Anti-Mullerian Hormone(AMH); testosterone (T)\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e depicted the linear relationships between BMI, weight, fasting insulin, and baseline testosterone with SUA as determined by curve fitting. The analysis indicated that as BMI, weight, fasting insulin, and baseline T increased, SUA levels also exhibited a tendency to rise.\u003c/p\u003e \u003cp\u003e4. Curve Fitting Between Various Factors and CLBR\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presented the curve fitting between various factors and the CLBR after adjusting for confounding variables. Figures\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC indicated that BMI and weight were linearly related to CLBR, with a decline in the CLBR as BMI and weight increased. Figures\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE show no significant correlation between SUA, baseline T, fasting insulin, and CLBR.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large retrospective cohort study, we found that SUA levels do not have a significant impact on CLBR in women with PCOS undergoing IVF-ET. Our data also support previous studies showing that SUA positively correlated with BMI, weight, and baseline T, all associated with metabolic syndrome [20]. Additionally, our findings emphasize the significant effect of BMI and weight on CLBR, with increases in both BMI and weight associated with a decline in CLBR, consistent with prior research [13]. Furthermore, our study indicates that high BMI (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25kg/m\u003csup\u003e2\u003c/sup\u003e) and obesity contribute to increased SUA levels. Obesity and high BMI are associated with hyperuricemia and a decreased CLBR. After adjusting for confounding factors, SUA itself was found to have no significant effect on CLBR in women with PCOS undergoing IVF-ET.\u003c/p\u003e \u003cp\u003eA cross-sectional survey conducted in the United States demonstrated a positive correlation between BMI dietary energy intake and serum SUA levels [21]. Additionally, a study from China involving 15,959 adults identified a correlation between SUA levels and obesity. Overweight and obese individuals had higher SUA levels than normal BMI (β\u0026thinsp;=\u0026thinsp;0.451, 95% CI: 0.357 to 0.546, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001; β\u0026thinsp;=\u0026thinsp;0.853, 95% CI: 0.760 to 0.946, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001; respectively) [22]. Previous research has established that obesity significantly affects SUA levels in women with PCOS [23]. Hosoyamada et al. found a positive correlation between serum total testosterone and SUA levels in women with PCOS [24]. Consistent with these findings, our study also shows that SUA levels in PCOS women tend to increase with rising BMI, weight, insulin levels, and baseline T.\u003c/p\u003e \u003cp\u003eHyperuricemia can result from excessive production or intake of SUA or reduced excretion. The potential mechanisms are as follows: First, the excessive intake of high-fructose foods can impair the small intestine's ability to clear fructose. Unmetabolized fructose, absorbed by the small intestine into the liver, stimulates the breakdown of purine nucleotides and the synthesis of SUA from amino acid precursors like glycine, leading to increased uric acid production [25,26]. Second, overproduction of SUA can occur due to increased energy intake, which contributes to obesity and hyperlipidemia, thereby enhancing purine synthesis and SUA production. Increased visceral fat raises free fatty acid levels in the portal vein system, which in turn activates hepatic fatty acid synthesis and the 5-phosphoribosyl 1-pyrophosphate (PRPP) pathway, resulting in increased synthesis of triglycerides and SUA [27]. Lastly, reduced uric acid excretion can be attributed to obesity-induced increases in leptin levels. Leptin directly inhibits the renal tubules' ability to excrete SUA [28]. It stimulates renin release at the renal level through the sympathetic nervous system, increasing sodium and SUA reabsorption in the proximal renal tubules and reducing uric acid excretion[29,30]. Additionally, obesity is strongly correlated with elevated insulin levels and insulin resistance [31]. Insulin promotes androgen synthesis [32], and elevated androgens can exacerbate insulin resistance in skeletal muscle and fat cells, leading to hyperinsulinemia by reducing the hepatic breakdown rate of insulin [33]. Insulin resistance or hyperinsulinemia may also activate the renin-angiotensin-aldosterone system, resulting in decreased renal blood flow and reduced uric acid excretion, increasing SUA levels [34\u0026ndash;37](Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHyperandrogenism is a prominent feature of Polycystic Ovary Syndrome (PCOS). Multiple studies have demonstrated that androgens can promote uric acid production and decrease excretion, thereby contributing to hyperuricemia. For instance, Pizzichini et al. reported that testosterone increases the mRNA and protein levels of the sodium-coupled monocarboxylate transporter 1 (Smct1) while decreasing the mRNA and protein expression levels of glucose transporter 9 (Glut9). These changes induce functional alterations in the renal tubular reabsorption system, leading to increased SUA reabsorption [38]. Additionally, animal studies have shown that testosterone elevates SUA levels by enhancing the liver metabolism of purine nucleotides and stimulating renal purine metabolism [39,40]. Moreover, it has been observed that anti-androgen contraceptive pills significantly lower SUA levels in obese women with PCOS [24], further suggesting that androgens influence SUA levels in this population (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn women with PCOS, the inherent predisposition to obesity, insulin resistance, and hyperandrogenemia are significant risk factors for hyperuricemia. Therefore, it is essential to determine whether obesity, insulin levels, or androgen levels influence assisted reproductive outcomes or if SUA itself affects these outcomes in women with PCOS. This investigation represents one of the primary objectives of our study.\u003c/p\u003e \u003cp\u003eCurrent research indicates that metabolic syndrome-related factors, such as obesity and BMI, are critical determinants of assisted reproductive outcomes in women with PCOS, with metabolic syndrome as an independent risk factor for CLBR [13,41,42]. A study by Rafael et al. demonstrated that overweight and obese women had significantly lower CLBRs compared to women of normal weight [43]. Additionally, a study involving 1,395 women with PCOS found that lean PCOS women exhibited higher CLBRs, while obese PCOS women had a significantly increased miscarriage rate compared to their lean counterparts[44]. Another investigation encompassing 5,016 PCOS women revealed a linear negative correlation between CLBR across multiple IVF cycles and BMI [45]. A study conducted in China categorized PCOS women into higher and lower BMI groups, finding that the clinical pregnancy and live birth rates were lower in the higher BMI group compared to the lower BMI group [46]. Our study aligns with these findings, showing that BMI and weight significantly influence CLBR in PCOS women undergoing ART, with CLBR decreasing as BMI and weight increase.\u003c/p\u003e \u003cp\u003eThe impact of hyperandrogenemia on assisted reproductive outcomes remains contentious. Some studies suggest that PCOS with elevated androgens is associated with a significantly lower CLBR compared to the normal androgen PCOS phenotype [47]. However, these studies were limited by small sample sizes and did not encompass all PCOS phenotypes. A recent meta-analysis found that the high androgen PCOS group had a higher miscarriage rate compared to the normal androgen PCOS group(RR: 1.56, 95% CI: 1.13, 2. 16), though no significant differences were observed in clinical pregnancy rates (RR: 0.88, 95% CI: 0.77, 1.01) or live birth rates (RR: 0.79, 95% CI: 0.55, 1. 11) between the two groups [48]. Our study aligns with these findings, showing no significant correlation between baseline T levels and CLBR.\u003c/p\u003e \u003cp\u003eCurrent research regarding the impact of SUA levels on assisted reproductive outcomes is limited. A study by Yang, H et al. reported that elevated SUA levels are associated with decreased probabilities of live birth and clinical pregnancy, as well as an increased risk of low birth weight in women with polycystic ovary syndrome. However, this study had a small sample size. It spanned an extended period, which may have introduced variability in measurement indicators, diagnostic criteria for the inclusion and exclusion of diseases, and IVF treatment protocols. Additionally, the study did not further investigate the impact of BMI and insulin levels on the outcomes [12]. Another investigation indicated that pregnant women with preeclampsia exhibit elevated SUA levels and a higher risk of low birth weight. However, no statistical difference in live birth rates was observed compared to normal pregnant women [49].\u003c/p\u003e \u003cp\u003eOur study indicates that, after adjusting for confounding factors, varying SUA levels do not significantly impact the CLBR in women with PCOS undergoing IVF. Our analysis shows that SUA levels positively correlate with BMI, weight, baseline T, and fasting insulin. Further examination of the associations between CLBR, SUA, and BMI revealed that SUA does not affect CLBR in PCOS patients, whereas BMI and weight were negatively correlated with CLBR. Consequently, we propose that hyperuricemia may be a concomitant condition associated with obesity, insulin resistance, and hyperandrogenemia rather than a direct determinant of CLBR in PCOS women undergoing IVF-ET.\u003c/p\u003e \u003cp\u003eThis study investigated the impact of SUA levels, BMI, and insulin levels on the CLBR in women with PCOS. The primary strengths of our study include its conduction at two major reproductive centers, where we collected data over a relatively short period and with a large sample size. This approach enhances the representativeness and reliability of the data. Additionally, our data were harmonized before integration concerning treatment processes, departmental protocols, and key indicators such as SUA testing, PCOS diagnostic criteria, ultrasound measurement, hormone test sensitivity, controlled ovarian stimulation (COS) protocols, and laboratory scoring standards. This harmonization aimed to minimize systematic errors. Furthermore, our study not only examined the influence of varying SUA levels on CLBR in the PCOS population but also further elucidated other factors affecting SUA levels and CLBR through correlation analysis and curve fitting\u0026mdash;this comprehensive exploration aimed to identify the underlying factors influencing CLBR in PCOS women undergoing IVF-ET.\u003c/p\u003e \u003cp\u003eDespite establishing strict inclusion and exclusion criteria, the retrospective design of this study presents several unavoidable limitations that may affect the reliability of our conclusions. The PCOS women included in this study were diagnosed using the Rotterdam criteria, which may not apply to those diagnosed by other standards. Additionally, the study population included women under 40, with pituitary down-regulation protocols used in 90.4% (2569/2841) of the ovulation induction schemes. Consequently, the applicability of our findings to older women (\u0026ge;\u0026thinsp;40 years) or those undergoing different ovulation induction protocols requires further investigation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSUA levels do not significantly impact the CLBR in PCOS women undergoing IVF-ET. Instead, BMI and weight negatively correlated with SUA levels and CLBR. Therefore, strategies focused on weight reduction may serve as effective therapeutic interventions to improve the CLBR in PCOS women. However, our conclusions require validation through further prospective, multicenter studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting Interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. SZ and LT supervised the study, including procedures, conception, design, and completion. SX and LT were responsible for collecting information. SX and TZ contributed to the analysis data and drafted the manuscript. NJ and ML participated in revising the article. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Reproductive Medicine Ethics Committee of Henan Provincial People\u0026apos;s Hospital (SYSZ-LL-2021091501).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the laboratory staff of our reproductive centers for their contribution to this work. We also acknowledge the patients who took part in this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData Availability\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSome or all datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLizneva D, Suturina L, Walker W, Brakta S, Gavrilova-Jordan L, Azziz R. Criteria, prevalence, and phenotypes of polycystic ovary syndrome. Fertil Steril. 106(1),6-15 (2016). https://doi.org/10.1016/j.fertnstert.2016.05.003.\u003c/li\u003e\n\u003cli\u003eMu L, Pan J, Yang L, Chen Q, Chen Y, Teng Y, Wang P, Tang R, Huang X, Chen X, Yang H. 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Cumulative live birth rates after IVF in patients with polycystic ovaries: phenotype matters. Reprod Biomed Online. 37(2),163-71 (2018). https://doi.org/10.1016/j.rbmo.2018.05.003.\u003c/li\u003e\n\u003cli\u003eMa L, Cao Y, Ma Y, Zhai J. Association between hyperandrogenism and adverse pregnancy outcomes in patients with different polycystic ovary syndrome phenotypes undergoing in vitro fertilization/intracytoplasmic sperm injection: a systematic review and meta-analysis. Gynecol Endocrinol. 37(8),694-701 (2021). https://doi.org/10.1080/09513590.2021.1897096.\u003c/li\u003e\n\u003cli\u003eAyankunle OM, Adeniyi AA, Adewara OE, Awoyinka SB, Adebara IO, Adeyemo OT, Bakare A, Olumodeji AM, Jimoh AK. Maternal serum uric acid: a reliable prognostic indicator of foetal outcome among pre-eclamptic patients in a low resource setting. J Matern Fetal Neonatal Med. 35(25),7695-700 (2022). https://doi.org/10.1080/14767058.2021.1960969.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Serum Uric Acid, BMI, In Vitro Fertilization-Embryo Transfer, Polycystic Ovary Syndrome, Cumulative Live Birth Rate","lastPublishedDoi":"10.21203/rs.3.rs-5873869/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5873869/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo estimate the impact of serum uric acid (SUA) levels on the cumulative live birth rate (CLBR) in women with polycystic ovary syndrome (PCOS) undergoing in vitro fertilization-embryo transfer (IVF-ET).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective cohort study analyzed data from 2,841 women who had their first IVF-ET treatment at the Reproductive Center of Henan Provincial People's Hospital and the Reproductive Center of Jiangxi Provincial Maternal and Child Health Hospital between January 2016 and December 2021. The women were divided into four groups based on SUA quartiles. Baseline characteristics and clinical and laboratory indicators were compared across these groups. Logistic regression was used to assess the impact of different SUA levels on CLBR. Correlation analysis identified factors influencing SUA levels and clarified the main factors affecting CLBR in women with PCOS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter adjusting for confounding factors, the SUA level did not significantly affect CLBR (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). SUA levels were positively correlated with body mass index (BMI), weight, baseline testosterone (T), and fasting insulin (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Curve-fitting analyses showed that SUA levels exhibited an increasing trend with the rise of BMI, weight, fasting insulin, and baseline T. BMI and weight were linearly associated with the CLBR, with rates decreasing as BMI and weight increased. In contrast, SUA, fasting insulin, and baseline T did not correlate significantly with the CLBR.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSUA levels do not have a significant impact on the CLBR in women with PCOS. BMI and weight are negatively correlated with CLBR.\u003c/p\u003e","manuscriptTitle":"The Impact of serum uric acid Levels on the Cumulative Live Birth Rate in Women with Polycystic Ovary Syndrome Undergoing In Vitro Fertilization-Embryo Transfer (IVF-ET)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-28 18:51:29","doi":"10.21203/rs.3.rs-5873869/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f1ed5b2-8b9f-43ab-961f-485483396ffa","owner":[],"postedDate":"January 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-16T12:53:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-28 18:51:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5873869","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5873869","identity":"rs-5873869","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}