The correlation between ANA and pregnancy loss and their impact on IVF/ICSI-ET pregnancy outcomes in patients with recurrent pregnancy loss

The correlation between ANA and pregnancy loss and their impact on IVF/ICSI-ET pregnancy outcomes in patients with recurrent pregnancy loss | 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 Article The correlation between ANA and pregnancy loss and their impact on IVF/ICSI-ET pregnancy outcomes in patients with recurrent pregnancy loss Manman Liu, Hebo Zhang, Shilian Xu, Rui Zhang, Mengfan Yuan, Bingnan Ren, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4580876/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 The relationship between antinuclear antibodies (ANA) and recurrent pregnancy loss (RPL) or single pregnancy loss (PL) is unclear. In this retrospective study, patients first seen at the hospital between January 2016 and December 2022 and who underwent two ANA tests within 4-6 weeks were included. After exclusion of confounding factors, patients were divided into the non-PL, single-PL or RPL group according to previous number of PLs, and the correlation between PL and ANA was analysed. The first embryo transfer (ET) after in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) without immunological treatment was selected in the RPL group, and patients were classified into the ANA-negative subgroup or ANA1:80 subgroup according to ANA titre. The effect of ANA on pregnancy outcomes in the RPL patients after IVF/ICSI-ET was further analysed. The results of multivariate unordered logistic regression showed that when the non-PL group was used as the reference, ANA positivity was an independent risk factor for RPL (P=0.023) but not for single PL (P=0.654). When the single-PL group was used as the reference, ANA positivity was an independent risk factor for RPL (P=0.022). There was no significant difference in ANA titre among the three groups of ANA-positive patients (P=0.106). Multivariate logistic regression analysis revealed that the early PL rate of the ANA1:80 subgroup was significantly higher than that of the ANA-negative subgroup (P=0.039), and the total PL rate of the ANA1:80 subgroup was significantly higher than that of the ANA-negative subgroup (P=0.033). The results showed that ANA positivity may be related to RPL occurrence, but there was no significant correlation between ANA positivity and single PL. ANA positivity (titre 1:80) is associated with PL occurrence in RPL patients after transplantation, and the correlation is reflected mainly in the first trimester. RPL patients should be screened for ANA and receive treatment. Biological sciences/Immunology/Autoimmunity Health sciences/Diseases/Reproductive disorders/Infertility Health sciences/Diseases/Reproductive disorders/Urogenital reproductive disorders Antinuclear antibody Pregnancy loss Recurrent pregnancy loss Assisted reproductive technology Figures Figure 1 Introduction Pregnancy loss (PL) is a common complication of pregnancy in women of childbearing age, and its incidence rate is approximately 10% 1 . According to the classical view, embryonic chromosome abnormalities are the main cause of PL, and the aetiology of PL can account for 50% of cases 2 . According to the guidelines of the European Society for Human Reproduction and Embryology (ESHRE) and Royal College of Obstetricians and Gynaecologists (RCOG) 3,4 , the spontaneous demise of a pregnancy before 24 weeks of pregnancy is referred to as a PL, while in China, PL before 28 weeks of pregnancy is still defined as spontaneous abortion (SA) 5 . According to the ESHRE guidelines, recurrent PL (RPL) is defined as the loss of two or more pregnancies, including non-visualized PL. In 2019, Green DM et al. reported that the incidence of RPL was approximately 1%~5% 6 . In recent years, an increasing number of scholars have begun to pay attention to the role of immune factors in adverse pregnancy and childbirth outcomes, especially RPL 7,8 . For example, classical antiphospholipid syndrome (APS) is closely related to RPL 9,10 , and it is the only immunological disease recommended for examination and treatment 3,11 . Because the components and functions of the immune system vary and the interactions among various immune components are complex, people have gradually begun to study specific pathogenic autoantibodies 12 , such as antiphospholipid antibodies, antinuclear antibodies (ANA), and antithyroid autoantibodies. ANA are autoantibodies that are produced by the body, and they combine with nuclear and intranuclear antigens. Approximately 13.0% of healthy people are positive for ANA, but the clinical significance of this phenomenon is not clear at present 13 . ANA are also present in several immunological diseases, such as systemic lupus erythematosus (SLE) and Sjogren's syndrome (SS), and these diseases can also lead to adverse pregnancy outcomes 14,15 . However, the role of simple ANA positivity in single PL and RPL is unclear. A study by Zhu in 2013 showed that ANA positivity may affect the outcomes of in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI-ET), but this study did not limit the number of PLs in patients 16 . A retrospective study by Sakthiswary R showed that the percentage of ANA-positive patients with unexplained RPL (URPL) was significantly higher than that of healthy controls 17 . Recent meta-analyses have shown that the rate of ANA positivity in RPL patients is higher than that in non-RPL patients 18,19 ; however, these meta-analyses did not define the number of PLs in non-RPL patients, and the control population included in each study differed. Therefore, we conducted this retrospective cohort study to explore the association between ANA and PL and to evaluate its effect on IVF/ICSI-ET pregnancy outcomes in RPL patients. Results Characteristics of all the subjects A total of 2946 patients, including 930 patients in the non-PL group (31.57%), 1416 patients in the single-PL group (48.06%) and 600 patients in the RPL group (20.37%), were enrolled in this study (Fig. 1). Among the three groups, there were significant differences in female age, male age, female body mass index (BMI), infertility duration, anti-Müllerian hormone (AMH) levels, antral follicle count (AFC) and infertility factors (all P<0.001). There were no significant differences in the basal follicle-stimulating hormone (bFSH) level among the three groups (P=0.070). There were 130 ANA-positive patients in non-PL group, 214 patients in the single PL group, and 122 patients in the RPL group. The difference in the percentage of ANA-positive individuals among the three groups was significant (14.0% vs. 15.1% vs. 20.3%, P=0.002), with the RPL group having a significantly higher ANA positive rate than the non-PL group and the single-PL group (both P<0.0167) (Table 1). Multivariate unordered logistic regression analysis of pregnancy loss Multivariate unordered logistic regression was performed in the study with the non-PL group and single-PL group as controls. When the non-PL group was used as the reference, ANA positivity was an independent risk factor for patients in the RPL group (aOR: 1.427, 95% CI: 1.050-1.940, P=0.023) but not for patients in the single PL group (aOR: 1.063, 95% CI: 0.814-1.387, P=0.654) (Table 2). Similarly, when the single PL group was used as the reference, ANA positivity was an independent risk factor for patients in the RPL group (aOR: 1.343, 95% CI: 1.043-1.729; P=0.022) (Table 3). Proportions of patients according to ANA titre in the three groups of ANA-positive patients There was no significant difference in the proportion of patients according to ANA titre among the three groups (P=0.106) (Table 4). Characteristics of RPL patients receiving IVF/ICSI-ET without immunotherapy After the patients were screened according to the exclusion criteria in the RPL group, 406 were included in the ANA-negative subgroup, and 61 were included in the ANA1:80 subgroup. The female age in the ANA1:80 subgroup was significantly higher than that in the ANA-negative subgroup (35.98 ± 5.71 vs. 34.38 ± 4.73, P=0.040). Female BMI was significantly lower in the ANA1:80 than in the ANA-negative subgroup (23.87 ± 2.96 vs. 25.03 ± 3.40, P=0.012). There were no significant differences in the other variables (all P>0.05) (Table 5). Pregnancy outcomes of RPL patients receiving IVF/ICSI-ET without immunotherapy Because of the significant differences in the characteristics of the two subgroups, a collinearity diagnosis of the characteristics was performed, and the results showed that the VIF was >5, suggesting that there was no obvious multicollinearity. Univariate and multivariate logistic regression were used to correct for confounding factors. Multivariate logistic regression analysis revealed that the early PL rate of patients in the ANA 1:80 subgroup was significantly higher than that in the ANA-negative subgroup (32.26% vs. 14.23%, aOR: 2.552, 95% CI: 1.050-6.206; P=0.039). There was no significant difference in the late PL rate between the two subgroups (3.23% vs. 5.02%, aOR: 0.673, 95% CI: 0.079-5.763, P=0.718), but the total PL rate of the ANA1:80 subgroup was still significantly higher than that of the ANA-negative subgroup (35.48% vs. 19.2%, aOR: 2.658, 95% CI: 1.803-6.521, P=0.033). Univariate regression analysis revealed that the live birth rate of the ANA 1:80 subgroup was significantly lower than that of the ANA-negative subgroup (32.79% vs. 46.31%, OR: 0.673, 95% CI: 0.320-0.999, P=0.050). However, after multivariate logistic regression correction for confounding factors, there was no significant difference in the live birth rate between the two subgroups (aOR: 0.592, 95% CI: 0.308-1.137, P=0.116) (Table 6). Discussion During mitosis, some substances in the nucleus may be exposed to the cell surface. When the body's immune system is out of balance, these substances may activate the autoimmune system and lead to the production of ANA 20 . In 1972, Abrahams et al. first described the relationship between ANA and RPL 21 . Recent studies have shown that ANA may be related to adverse pregnancy outcomes, such as infertility and RPL 22,23 ; however this conclusion remains controversial, and the relationship between ANA and single PL is still unclear. The results of multivariate unordered logistic regression in this study showed that ANA was significantly correlated with RPL but was not significantly correlated with single PL (Table 2, Table 3). However, the specific mechanism by which ANA lead to RPL is still unclear. Previous studies have shown that ANA in follicular fluid can negatively affect IVF/ICSI transplantation outcomes by decreasing oocyte quality or the number of invading granulosa cells 24,25 . However, the distribution of ANA in serum and follicular fluid is inconsistent. In the study by Ying et al., ANA were detected in the serum in 50 patients, but in the follicular fluid of only 36 patients 26 . Veglia M et al. injected ANA IgG into mice, which activated the complement system and resulted in PL 27 . In addition, the precipitation of immune complexes at the maternal-foetal interface may be one of the mechanisms leading to PL in ANA-positive women 28,29 . ANA test results are usually displayed according to titre. The ANA titres of most of the ANA-positive patients in the three groups of this study were 1:80, and there was no significant difference in the titre ratio (Table 4). Previous studies by Zhu et al. showed that there was no significant difference in IVF/ICSI outcomes between patients with an ANA titre >1:320 and patients with an ANA titre <1:320 16 , indicating that the effect of ANA on PL may be related only to whether or not the patient is positive for ANA, and an increase in the ANA titre may not increase the PL rate. After receiving IVF/ICSI-ET, the early PL rate and total PL rate in the ANA1:80 subgroup of RPL patients who did not receive immunotherapy were significantly higher than those in the ANA-negative subgroup (Table 6). This indicates a correlation between ANA positivity and the occurrence of PL in RPL patients after transplantation, which can be mutually confirmed with previous research results and further suggests that ANA positivity may be related to the occurrence of RPL. Notably, there was no significant difference in the late PL rate between the two subgroups, indicating that the correlation between ANA and PL is reflected mainly in the first trimester of pregnancy (before 12 weeks). This result indirectly proves that after successful progression through the early stage of pregnancy, if the body does not undergo drastic immunological changes, PL will not occur due to immunological factors. Univariate logistic regression analysis of the live birth rate revealed that the live birth rate of the ANA1:80 subgroup was significantly lower than that of the ANA-negative subgroup. After adjustments were made for the confounding factors of the live birth rate by multivariate logistic regression, the difference between the two groups become nonsignificant (Table 6). This phenomenon may be due to the insufficient sample size in the study. A total of 61 patients were included in the ANA1:80 subgroup, and only 20 patients had live births. It is necessary to expand the sample size to further evaluate the live birth rate. It is controversial whether patients with a previous history of PL need to be screened and treated for ANA. According to the results of this study, we recommend screening and treatment for RPL patients. For patients with a history of only one PL, screening and treatment of ANA should not be performed. However, at present, there are many related treatment schemes, and a consensus on the best treatment scheme has yet to be reached. A placebo-controlled trial in 2021 showed that the live birth rate of ANA-positive RPL patients treated with prednisone combined with aspirin did not increase significantly, but the risk of premature birth increased significantly 30 . However, research by Gao et al. showed that prednisone combined with hydroxychloroquine can improve the IVF/ICSI outcome of ANA-positive patients 31 . The advantage of this study lies in the addition of a single PL group, in which both the correlation between RPL and ANA and the relationship between single PL and ANA were investigated. In addition, due to the diverse treatment options available for ANA-positive RPL patients, to reduce their impact on the research results, this study excluded patients who had previously or were currently receiving immunological treatment. The limitation of this study is that it was a retrospective study, and the occurrence of selection bias could not be avoided. Second, the aetiology of embryo implantation failure is very similar to that of PL. In this study, only patients with recurrent implantation failure (RIF) were excluded, and a history of occasional implantation failure, which can be used as a confounding factor to influence the research results, was not considered. In addition, since this study did not analyse RPL patients with titres of 1:160 or above, the pregnancy outcomes of such patients cannot be determined. High-quality research is needed to confirm the impact of ANA titre on the pregnancy outcomes of RPL patients. Conclusion The results showed that there was a correlation between ANA and RPL, but there was no significant correlation between ANA and single PL. ANA positivity (titre 1:80) was related to the occurrence of PL after RPL transplantation, and the correlation was reflected mainly in the first trimester of pregnancy. It is suggested that RPL patients should be screened and treated for ANA. Materials And Methods Study design and subjects This retrospective observational case‒control study included patients who visited the Department of Reproductive Medicine at the Third Affiliated Hospital of Zhengzhou University for the first time from January 2016 to December 2022 and were tested for ANA twice within 4-6 weeks. The number of PLs was documented as the total number before the first ANA test. To reduce the influence of confounding factors, patients were excluded if they had any of the following: ① chromosome karyotype abnormality in either spouse; ② abnormal anatomical structure of the uterus, such as bicornuate uterus, saddle uterus, mediastinal uterus, uterine fibroids, or adenomyosis; ③ abnormal endocrinology or metabolism; ④ immunological diseases, such as APS, SLE, or SS; ⑤ prethrombotic state; ⑥ RIF; or ⑦ different ANA test results. These patients were divided into the non-PL group (no previous PL), single-PL group (history of one previous PL) and RPL group according to the number of previous PLs to evaluate whether ANA is a risk factor for PL. Patients with an ANA titre of 1:80 did not receive drug intervention unless they are complicated by definite rheumatic immune diseases or unless the patient needed treatment after consultation with a rheumatologist. However, most patients with an ANA titre ≥1:160 receive immunological treatment at our hospital, and there are various treatment options available to them. Therefore, in this study, we selected patients in the RPL group who did not undergo immunological treatment and who underwent their first ETs after IVF/ICSI. According to the ANA test results, the patients were divided into the ANA1:80 subgroup and the ANA-negative subgroup to analyse the impact of ANA on pregnancy outcomes after transplantation. In addition, to reduce confounding factors, the study excluded patients who used donor sperm or eggs or who underwent IVF/ICSI with preimplantation genetic testing. In this paper, PL is defined as natural foetal death before 24 weeks of pregnancy, and RPL is defined as PL occurring two or more times, including non-visualized PL, according to the ESHRE guidelines 3 . RIF is defined as failure to achieve pregnancy after three consecutive high-quality embryos 32 . ANA detection method Considering the experimental error, ANA detection should be carried out at least twice, with an interval of 4~6 weeks. It is clinically significant that the results of the two tests are the same. Detection of ANA based on indirect immunofluorescence: Fresh blood samples should be used. Blood samples containing particulate matter were centrifuged at low speed (<1000×g) to remove particles and then used within the first 8 hours after serum separation. In the first incubation, the serum was diluted to 1:32, 1:100 or higher, and the combination of HEp-2 cells and frozen sections of animal tissues was used as the matrix. Then, 35 µL of diluted serum was added and incubated at 20-26°C for 30 minutes. For the second incubation, the cells were gently washed with distilled water diluted with 1:10 cleaning buffer and then soaked in a dyeing dish 3 times for 5 minutes each. Then, 35 µL of FITC-conjugated secondary antibody was added to the sample, and the sample was incubated at 20-26 ℃ for 30 minutes, washed (as described above), and sealed on the tablet. The results were immediately obtained by fluorescence microscopy. Each test and result interpretation were performed with reference to positive and negative controls. When weak fluorescence appeared in the nucleus (titres between 1:80 and negative) or if the experimental results were uncertain, the samples were evaluated again. Observation indicators and their definitions The clinical pregnancy rate was defined as the number of clinically pregnant patients/the number of total transplantation patients × 100%. The presence of one or more gestational sacs on ultrasound indicated a clinical pregnancy, including an intrauterine pregnancy, an ectopic pregnancy, a simultaneous intrauterine and extrauterine pregnancy, or pregnancy with only a gestational sac but no foetal heartbeat. The early PL rate was defined as the number of PL patients within 12 weeks of pregnancy/the number of clinically pregnant patients × 100%. The late PL rate was defined as the number of PL patients after 12 weeks and before 24 weeks of pregnancy/the number of clinically pregnant patients × 100%. The total PL rate was defined as the number of PL patients before 24 weeks of pregnancy/the number of clinically pregnant patients × 100%. The ectopic pregnancy rate was defined as the number of ectopic pregnancy patients/the number of clinical pregnancy patients × 100%. An ectopic pregnancy was defined as a pregnancy in which a fertilized egg was implanted outside the uterine cavity, including tubal pregnancy, ovarian pregnancy, cervical pregnancy, broad ligament pregnancy and abdominal pregnancy. The premature birth rate was defined as the number of patients with live births between 24 and 37 weeks of pregnancy/the number of patients with live births after 24 weeks of pregnancy. The live birth rate was defined as the number of patients with live births after 24 weeks of pregnancy/total number of transplantation patients × 100%. Statistical analysis SPSS 26.0 software was used for statistical analysis. Normally distributed data with homogeneous variance are expressed as the mean ± standard deviation (. Student's t test was used for comparisons between two groups, and one-way analysis of variance was used for comparisons among multiple groups. Nonnormal distribution and/or homogeneity of variance are expressed as medians (quartiles) [M (Q1, Q3)]. The Kruskal-Wallis rank-sum test was used for comparisons between groups, with a significance level of α=0.05. Count data are expressed as the rate or composition ratio (%). The chi-square test was used for comparisons between groups. When the theoretical frequency was less than 5, Fisher’s exact probability method was used for comparisons between groups, and the significance level was set at α=0.05. The Bonferroni method was used for pairwise comparisons between multiple groups of measurement and counting data, and the corrected test level was α'=0.0167. Factors related to the PL were analysed by multivariate unordered logistic regression, and variables with P<0.05 among multiple groups were included. Univariate and multivariate logistic regression were used to correct for confounding factors related to the clinical pregnancy outcomes of RPL patients. When the clinical characteristics from the univariate logistic regression analysis showed P<0.10, they were included in the multivariate logistic regression analysis. Ethical approval All the procedures of this study conformed to the 1964 Helsinki Declaration and its later amendments or similar ethical standards and passed the examination and approval of the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2023-067-01). The need to obtain informed consent was waived by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University Declarations Acknowledgements We would like to express our sincere gratitude to all individuals who contributed to the completion of this study. Author contributions Manman Liu and Hebo Zhang designed the study, analysed the data, and drafted the manuscript, both of which have equal contribution. Shilian Xu, Rui Zhang and Mengfan Yuan participated in the critical discussion and revision of the article. Bingnan Ren, Zhaozhao Liu and Yichun Guan assisted in the article writing and revising. The authors contributed to the article and approved the submitted version. Data availability The datasets generated during and analysed during the current study are not publicly available due to hospital's privacy policy but are available from the corresponding author on reasonable request. Funding This project has received funding from National Key Research and Development Program of China (2021YFC2700602) and the Henan Province Medical Science and Technology Research Program (Joint Construction) project (LHGJ20190369) in China Competing interests The authors declare no conflicts of interests. Additional information Correspondence and requests for materials should be addressed to M. L. References Rai, R. & Regan, L. Recurrent miscarriage. Lancet 368, 601–611. https://doi.org:10.1016/s0140-6736(06)69204-0 (2006). Jacobs, P. A. The role of chromosome abnormalities in reproductive failure. Reprod Nutr Dev Suppl 1, 63s-74s. https://doi.org:10.1051/rnd:19900706 (1990). Bender Atik, R. et al. ESHRE guideline: recurrent pregnancy loss. Human Reproduction Open 2018. https://doi.org:10.1093/hropen/hoy004 (2018). Regan, L., Rai, R., Saravelos, S., Li, T. C. & Royal Coll, O. Recurrent Miscarriage Green-top Guideline No. 17. 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Tables Characteristics Non-PL group Single-PL group RPL group P value N 930 1,416 600 Female age 33.30 ± 4.69 34.15 ±4.88 a 35.34 ±5.06 a, b < 0.001 Male age 33.00 (30.75, 37.00) 34.00 (31.00, 38.00) a 35.00 (32.00, 40.00) b < 0.001 Female BMI 23.69 ±3.17 23.90 ±3.22 24.79 ±3.26 a, b < 0.001 Infertility duration 4.00 (2.00, 6.00) 1.00 (0.60, 2.50) a 1.00 (0.80, 2.50) a < 0.001 bFSH 6.62 (5.49, 8.04) 6.70 (5.49, 8.19) 6.82 (5.79, 8.37) 0.070 AMH 18.41 (9.08, 32.40) 18.92 (8.27, 31.83) 12.91 (7.20, 27.99) a, b < 0.001 AFC 16.00 (9.75, 23.25) 16.00 (10.00, 23.00) 13.00 (7.00, 21.00) a, b < 0.001 Infertility factor < 0.001 Female factor 317 (34.09%) 651 (45.97%) a 313 (52.17%) a, b Male factor 92 (9.89%) 183 (12.92%) 58 (9.67%) Factor of both sides 103 (11.08%) 270 (19.07%) a 67 (11.17%) b Unknown cause 418 (44.95%) 312 (22.03%) a 162 (27.00%) a, b ANA status 0.002 ANA positive 130 (13.98%) 214 (15.11%) 122 (20.33%) a, b ANA negative 800 (86.02%) 1202 (84.89%) 478 (79.67%) a, b Table 1. Comparisons of the characteristics of the included patients. a reports P <0.0167 compared to the non-PL group, b reports P <0.0167 compared to the single-PL group. Single-PL group RPL group Characteristics β value Adjusted OR (95% CI) P value β value Adjusted OR (95% CI) P value Female age 0.040 1.041 (1.007, 1.077) 0.018 0.059 1.061 (1.020, 1.105) 0.004 Male age 0.038 1.038 (1.008, 1.070) 0.013 0.045 1.046 (1.011, 1.083) 0.010 Female BMI 0.025 1.025 (0.995, 1.056) 0.103 0.117 1.124 (1.085, 1.165) <0.001 Infertility duration -0.352 0.703 (0.676, 0.732) <0.001 -0.435 0.647 (0.611, 0.686) <0.001 AMH 0.002 1.002 (0.998, 1.007) 0.328 0.005 1.005 (0.999, 1.010) 0.107 AFC -0.010 0.990 (0.975, 1.006) 0.213 -0.029 0.972 (0.956, 0.988) 0.001 Infertility factors Female factor Ref. Ref. Male factor 0.101 1.106 (0.812, 1.506) 0.523 -0.189 0.828 (0.558, 1.229) 0.349 Factor of both sides 0.513 1.670 (1.235, 2.258) 0.001 -0.193 0.824 (0.560, 1.213) 0.327 Unknown cause -0.872 0.418 (0.337, 0.519) <0.001 -0.726 0.484 (0.372, 0.629) <0.001 ANA status ANA negative Ref. Ref. ANA positive 0.061 1.063 (0.814, 1.387) 0.654 0.356 1.427 (1.050, 1.940) 0.023 Table 2. The results of the multivariate unordered logistic regression analysis with the non-PL group as the control RPL group Characteristics β value Adjusted OR (95% CI) P value Female age 0.019 1.019 (0.986, 1.054) 0.263 Male age 0.008 1.008 (0.980, 1.036) 0.582 Female BMI 0.092 1.097 (1.064, 1.131) <0.001 Infertility duration -0.083 0.920 (0.869, 0.975) 0.005 AMH 0.002 1.002 (0.998, 1.007) 0.330 AFC -0.027 0.973 (0.985, 0.989) 0.001 Infertility factors Female factor Ref. Male factor -0.289 0.749 (0.537, 1.043) 0.087 Factor on both sides -0.706 0.493 (0.363, 0.670) <0.001 Unknown cause 0.146 1.157 (0.912, 1.469) 0.229 ANA status ANA negative Ref. ANA positive 0.295 1.343 (1.043, 1.729) 0.022 Table 3. The results of multivariate unordered logistic regression with the single-PL group as the control group Non-PL group Single-PL group RPL group P value n 130 214 122 ANA titre 0.106 1: 80 88 (67.69%) 158 (73.83%) 87 (71.31%) 1: 160 20 (15.38%) 39 (18.22%) 24 (19.67%) ≥1: 320 22 (16.92%) 17 (7.94%) 11 (9.02%) Table 4. The proportions of patients according to ANA titre in each group of ANA-positive patients. Characteristics ANA-negative subgroup ANA1:80 subgroup P value n 406 61 Female age 34.38±4.73 35.98±5.71 0.040 Male age 35.00 (32.00, 39.00) 38.00 (31.25, 40.75) 0.167 Female BMI 25.03±3.40 23.87±2.96 0.012 Infertility duration 1.00 (0.60, 2.00) 1.00 (0.60, 2.00) 0.590 bFSH 6.70 (5.54, 8.06) 7.12 (5.81, 8.40) 0.375 AMH 16.09 (8.14, 33.53) 11.11 (7.23, 24.45) 0.085 AFC 15.00 (9.00, 23.00) 13.00 (9.00, 19.00) 0.065 Endometrial thickness on the day of transplantation 8.99±1.84 9.03±1.75 0.872 Proportion of single-embryo transfers 50.49 (205/406) 44.26 (27/61) 0.364 Infertility factors 0.083 Female factor 205 (50.49%) 41 (67.21%) Male factor 41 (10.10%) 6 (9.84%) Factor on both sides 54 (13.30%) 5 (8.20%) Unknown cause 106 (26.11%) 9 (14.75%) Type of embryo transfer 0.747 Cleavage-stage embryo transfer 182 (44.83%) 26 (42.62%) Blastocyst embryo transfer 224 (55.17%) 35 (57.38%) Embryo transfer cycle 0.914 Fresh cycle 89 (21.92%) 13 (21.31%) Thawing cycle 317 (78.08%) 48 (78.69%) Table 5. Comparison of the characteristics of RPL patients receiving IVF/ICSI-ET. ANA-negative subgroup ANA1:80 subgroup Unadjusted OR (95% CI) P value Adjusted OR (95% CI) P value Clinical pregnancy rate 239/406 (58.87%) 31/61 (50.82%) 0.722 (0.421, 1.238) 0.237 0.833 (0.454, 1.530) 0.566 Early pregnancy loss rate * 34/239 (14.23%) 10/31 (32.26%) 2.871 (1.245, 6.624) 0.013 2.552 (1.050, 6.206) 0.039 Late pregnancy loss rate * 12/239 (5.02%) 1/31 (3.23%) 0.631 (0.079, 5.023) 0.663 0.673 (0.079, 5.763) 0.718 Total pregnancy loss rate * 46/239 (19.2%) 11 (35.48%) 2.308 (1.034, 5.151) 0.041 2.658 (1.083, 6.521) 0.033 Ectopic pregnancy rate * 5/239 (2.09%) 0 (0.00%) 0.000 (0.000) 0.998 / / Premature birth rate ** 23/188 (12.23%) 3/20 (15.00%) 1.006 (0.284, 3.568) 0.992 / / Live birth rate 188 (46.31%) 20 (32.79%) 0.566 (0.320, 0.999) 0.050 0.592 (0.308, 1.137) 0.116 Table 6. Univariate and multivariate logistic regression analysis of pregnancy outcomes in RPL patients receiving IVF/ICSI-ET. * represents the denominator of clinical pregnancy patients. ** represents the denominator of the number of live birth patients. Clinical pregnancy rate: Female age, male age, infertility factors, bFSH, AMH, AFC, endometrial thickness on the day of transplantation, and type of embryo transfer were covariates. Early pregnancy loss rate: Female age, male age, AMH and AFC were covariates. Late pregnancy loss rate: Infertility factors, BMI, AMH and proportion of single embryo transfer were covariates. Total pregnancy loss rate: Female age, male age, BMI, AMH, AFC, proportion of single embryo transfer, and type of embryos transfer were covariates. Ectopic pregnancy rate and premature delivery rate: Univariate regression analysis of characteristics showed that all P values were >0.10. Live birth rate: Female age, male age, infertility factors, BMI, bFSH, AMH, AFC, endometrial thickness on the day of transplantation, and type of embryo transfer were covariates. 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4580876","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":318481474,"identity":"abdc1506-27a1-4293-820d-090995fee52a","order_by":0,"name":"Manman Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYBACAwYGZiBpwcDADuR9MLCRI1aLBJhinFGQZkykFgaIFmaeD4cTCWoxl0h+bPCjQCKxn5n52WMbA+YEBvbDRzfg02I5I804scdAInFmM5u5cY4BWx4DT1raDbwOu5FgfIAHqGXDYQYz6RwDnmIGCR4zAlrSPx/8A9bC/k3aAshoIKwlxzgZYguPmTSDgQERWs68KTaWMZAwntnMUybZY5BgzEbQL8fTN0u++WMj28/evk3ix5//cvzsh4/h1YIJ2EhTPgpGwSgYBaMAGwAATj9C2j8/4IkAAAAASUVORK5CYII=","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"Manman","middleName":"","lastName":"Liu","suffix":""},{"id":318481475,"identity":"ce68acd4-0ba0-46dd-b9e8-829d4d41faf0","order_by":1,"name":"Hebo Zhang","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Hebo","middleName":"","lastName":"Zhang","suffix":""},{"id":318481476,"identity":"61ae1263-6c8e-4bf3-9023-3df2a31ebe63","order_by":2,"name":"Shilian Xu","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Shilian","middleName":"","lastName":"Xu","suffix":""},{"id":318481477,"identity":"03e70485-9bb1-400f-9533-b089282d2ecc","order_by":3,"name":"Rui Zhang","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Rui","middleName":"","lastName":"Zhang","suffix":""},{"id":318481478,"identity":"2d5bd1bf-df9c-4763-9b6b-a38f1516aaac","order_by":4,"name":"Mengfan Yuan","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Mengfan","middleName":"","lastName":"Yuan","suffix":""},{"id":318481479,"identity":"b0b99c65-64a9-44e7-bfe8-b60a78068068","order_by":5,"name":"Bingnan Ren","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Bingnan","middleName":"","lastName":"Ren","suffix":""},{"id":318481480,"identity":"a5c7ef01-c49f-4a8e-85fc-b6119b44f9b8","order_by":6,"name":"Wenjuan Zhang","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Wenjuan","middleName":"","lastName":"Zhang","suffix":""},{"id":318481481,"identity":"2ba3d306-9d36-4f1a-b42a-bb9150df899c","order_by":7,"name":"Zhaozhao Liu","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Zhaozhao","middleName":"","lastName":"Liu","suffix":""},{"id":318481482,"identity":"8d047506-ee11-4f4d-ae5e-88b1513559ff","order_by":8,"name":"Yichun Guan","email":"","orcid":"","institution":"Third Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yichun","middleName":"","lastName":"Guan","suffix":""}],"badges":[],"createdAt":"2024-06-14 09:09:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4580876/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4580876/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60435566,"identity":"a436aba3-9820-4415-a560-9936ffcbd2db","added_by":"auto","created_at":"2024-07-16 17:23:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":479584,"visible":true,"origin":"","legend":"\u003cp\u003eResearch flowchart. PL represents pregnancy loss. RIF represents recurrent implantation failure.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4580876/v1/e4682378872a8b9b47c4ebce.jpg"},{"id":64833124,"identity":"43d31dba-2cdc-4091-ac39-9fe64e2c5a6a","added_by":"auto","created_at":"2024-09-19 10:03:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1193040,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4580876/v1/9c3bbc30-c2c4-4dc3-9326-e352d52cdf64.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The correlation between ANA and pregnancy loss and their impact on IVF/ICSI-ET pregnancy outcomes in patients with recurrent pregnancy loss","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePregnancy loss (PL) is a common complication of pregnancy in women of childbearing age, and its incidence rate is approximately 10%\u0026nbsp;\u003csup\u003e1\u003c/sup\u003e. According to the classical view, embryonic chromosome abnormalities are the main cause of PL, and the aetiology of PL can account for 50% of cases\u0026nbsp;\u003csup\u003e2\u003c/sup\u003e. According to the guidelines of the European Society for Human Reproduction and Embryology (ESHRE) and Royal College of Obstetricians and Gynaecologists (RCOG)\u0026nbsp;\u003csup\u003e3,4\u003c/sup\u003e, the spontaneous demise of a pregnancy before 24 weeks of pregnancy is referred to as a PL, while in China, PL before 28 weeks of pregnancy is still defined as spontaneous abortion (SA)\u0026nbsp;\u003csup\u003e5\u003c/sup\u003e. According to the ESHRE guidelines, recurrent PL (RPL) is defined as the loss of two or more pregnancies, including non-visualized PL. In 2019, Green DM et al. reported that the incidence of RPL was approximately 1%~5%\u0026nbsp;\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn recent years, an increasing number of scholars have begun to pay attention to the role of immune factors in adverse pregnancy and childbirth outcomes, especially RPL\u0026nbsp;\u003csup\u003e7,8\u003c/sup\u003e. For example, classical antiphospholipid syndrome (APS) is closely related to RPL\u0026nbsp;\u003csup\u003e9,10\u003c/sup\u003e, and it is the only immunological disease recommended for examination and treatment\u0026nbsp;\u003csup\u003e3,11\u003c/sup\u003e. Because the components and functions of the immune system vary and the interactions among various immune components are complex, people have gradually begun to study specific pathogenic autoantibodies\u0026nbsp;\u003csup\u003e12\u003c/sup\u003e, such as antiphospholipid antibodies, antinuclear antibodies (ANA), and antithyroid autoantibodies.\u003c/p\u003e\n\u003cp\u003eANA are autoantibodies that are produced by the body, and they combine with nuclear and intranuclear antigens. Approximately 13.0% of healthy people are positive for ANA, but the clinical significance of this phenomenon is not clear at present\u0026nbsp;\u003csup\u003e13\u003c/sup\u003e. ANA are also present in several immunological diseases, such as systemic lupus erythematosus (SLE) and Sjogren\u0026apos;s syndrome (SS), and these diseases can also lead to adverse pregnancy outcomes\u0026nbsp;\u003csup\u003e14,15\u003c/sup\u003e. However, the role of simple ANA positivity in single PL and RPL is unclear.\u003c/p\u003e\n\u003cp\u003eA study by Zhu in 2013 showed that ANA positivity may affect the outcomes of in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI-ET), but this study did not limit the number of PLs in patients\u0026nbsp;\u003csup\u003e16\u003c/sup\u003e. A retrospective study by Sakthiswary R showed that the percentage of ANA-positive patients with unexplained RPL (URPL) was significantly higher than that of healthy controls\u0026nbsp;\u003csup\u003e17\u003c/sup\u003e. Recent meta-analyses have shown that the rate of ANA positivity in RPL patients is higher than that in non-RPL patients\u0026nbsp;\u003csup\u003e18,19\u003c/sup\u003e; however, these meta-analyses did not define the number of PLs in non-RPL patients, and the control population included in each study differed. Therefore, we conducted this retrospective cohort study to explore the association between ANA and PL and to evaluate its effect on IVF/ICSI-ET pregnancy outcomes in RPL patients.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCharacteristics of all the subjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 2946 patients, including 930 patients in the non-PL group (31.57%), 1416 patients in the single-PL group (48.06%) and 600 patients in the RPL group (20.37%), were enrolled in this study (Fig. 1). Among the three groups, there were significant differences in female age, male age, female body mass index (BMI), infertility duration, anti-M\u0026uuml;llerian hormone (AMH) levels, antral follicle count (AFC) and infertility factors (all P\u0026lt;0.001). There were no significant differences in the basal follicle-stimulating hormone (bFSH) level among the three groups (P=0.070). There were 130 ANA-positive patients in non-PL group, 214 patients in the single PL group, and 122 patients in the RPL group. The difference in the percentage of ANA-positive individuals among the three groups was significant (14.0% vs. 15.1% vs. 20.3%, P=0.002), with the RPL group having a significantly higher ANA positive rate than the non-PL group and the single-PL group (both P\u0026lt;0.0167) (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate unordered logistic regression analysis of pregnancy loss\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariate unordered logistic regression was performed in the study with the non-PL group and single-PL group as controls. When the non-PL group was used as the reference, ANA positivity was an independent risk factor for patients in the RPL group (aOR: 1.427, 95% CI: 1.050-1.940, P=0.023) but not for patients in the single PL group (aOR: 1.063, 95% CI: 0.814-1.387, P=0.654) (Table 2). Similarly, when the single PL group was used as the reference, ANA positivity was an independent risk factor for patients in the RPL group (aOR: 1.343, 95% CI: 1.043-1.729; P=0.022) (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProportions of patients according to ANA titre in the three groups of ANA-positive patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no significant difference in the proportion of patients according to ANA titre among the three groups (P=0.106) (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristics of RPL patients receiving IVF/ICSI-ET without immunotherapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the patients were screened according to the exclusion criteria in the RPL group, 406 were included in the ANA-negative subgroup, and 61 were included in the ANA1:80 subgroup. The female age in the ANA1:80 subgroup was significantly higher than that in the ANA-negative subgroup (35.98 \u0026plusmn; 5.71 vs. 34.38 \u0026plusmn; 4.73, P=0.040). Female BMI was significantly lower in the ANA1:80 than in the ANA-negative subgroup (23.87\u0026nbsp;\u0026plusmn;\u0026nbsp;2.96 vs. 25.03\u0026nbsp;\u0026plusmn;\u0026nbsp;3.40, P=0.012). There were no significant differences in the other variables (all P\u0026gt;0.05) (Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePregnancy outcomes of RPL patients receiving IVF/ICSI-ET without immunotherapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause of the significant differences in the characteristics of the two subgroups, a collinearity diagnosis of the characteristics was performed, and the results showed that the VIF was \u0026gt;5, suggesting that there was no obvious multicollinearity. Univariate and multivariate logistic regression were used to correct for confounding factors. Multivariate logistic regression analysis revealed that the early PL rate of patients in the ANA 1:80 subgroup was significantly higher than that in the ANA-negative subgroup (32.26% vs. 14.23%, aOR: 2.552, 95% CI: 1.050-6.206; P=0.039). There was no significant difference in the late PL rate between the two subgroups (3.23% vs. 5.02%, aOR: 0.673, 95% CI: 0.079-5.763, P=0.718), but the total PL rate of the ANA1:80 subgroup was still significantly higher than that of the ANA-negative subgroup (35.48% vs. 19.2%, aOR: 2.658, 95% CI: 1.803-6.521, P=0.033). Univariate regression analysis revealed that the live birth rate of the ANA 1:80 subgroup was significantly lower than that of the ANA-negative subgroup (32.79% vs. 46.31%, OR: 0.673, 95% CI: 0.320-0.999, P=0.050). However, after multivariate logistic regression correction for confounding factors, there was no significant difference in the live birth rate between the two subgroups (aOR: 0.592, 95% CI: 0.308-1.137, P=0.116) (Table 6).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDuring mitosis, some substances in the nucleus may be exposed to the cell surface. When the body\u0026apos;s immune system is out of balance, these substances may activate the autoimmune system and lead to the production of ANA\u0026nbsp;\u003csup\u003e20\u003c/sup\u003e. In 1972, Abrahams et al. first described the relationship between ANA and RPL\u0026nbsp;\u003csup\u003e21\u003c/sup\u003e. Recent studies have shown that ANA may be related to adverse pregnancy outcomes, such as infertility and RPL\u0026nbsp;\u003csup\u003e22,23\u003c/sup\u003e; however this conclusion remains controversial, and the relationship between ANA and single PL is still unclear.\u003c/p\u003e\n\u003cp\u003eThe results of multivariate unordered logistic regression in this study showed that ANA was significantly correlated with RPL but was not significantly correlated with single PL (Table 2, Table 3). However, the specific mechanism by which ANA lead to RPL is still unclear. Previous studies have shown that ANA in follicular fluid can negatively affect IVF/ICSI transplantation outcomes by decreasing oocyte quality or the number of invading granulosa cells\u0026nbsp;\u003csup\u003e24,25\u003c/sup\u003e. However, the distribution of ANA in serum and follicular fluid is inconsistent. In the study by Ying et al., ANA were detected in the serum in 50 patients, but in the follicular fluid of only 36 patients\u0026nbsp;\u003csup\u003e26\u003c/sup\u003e. Veglia M et al. injected ANA IgG into mice, which activated the complement system and resulted in PL\u0026nbsp;\u003csup\u003e27\u003c/sup\u003e. In addition, the precipitation of immune complexes at the maternal-foetal interface may be one of the mechanisms leading to PL in ANA-positive women\u0026nbsp;\u003csup\u003e28,29\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eANA test results are usually displayed according to titre. The ANA titres of most of the ANA-positive patients in the three groups of this study were 1:80, and there was no significant difference in the titre ratio (Table 4). Previous studies by Zhu et al. showed that there was no significant difference in IVF/ICSI outcomes between patients with an ANA titre \u0026gt;1:320 and patients with an ANA titre \u0026lt;1:320\u0026nbsp;\u003csup\u003e16\u003c/sup\u003e, indicating that the effect of ANA on PL may be related only to whether or not the patient is positive for ANA, and an increase in the ANA titre may not increase the PL rate.\u003c/p\u003e\n\u003cp\u003eAfter receiving IVF/ICSI-ET, the early PL rate and total PL rate in the ANA1:80 subgroup of RPL patients who did not receive immunotherapy were significantly higher than those in the ANA-negative subgroup (Table 6). This indicates a correlation between ANA positivity and the occurrence of PL in RPL patients after transplantation, which can be mutually confirmed with previous research results and further suggests that ANA positivity may be related to the occurrence of RPL. Notably, there was no significant difference in the late PL rate between the two subgroups, indicating that the correlation between ANA and PL is reflected mainly in the first trimester of pregnancy (before 12 weeks). This result indirectly proves that after successful progression through the early stage of pregnancy, if the body does not undergo drastic immunological changes, PL will not occur due to immunological factors. Univariate logistic regression analysis of the live birth rate revealed that the live birth rate of the ANA1:80 subgroup was significantly lower than that of the ANA-negative subgroup. After adjustments were made for the confounding factors of the live birth rate by multivariate logistic regression, the difference between the two groups become nonsignificant (Table 6). This phenomenon may be due to the insufficient sample size in the study. A total of 61 patients were included in the ANA1:80 subgroup, and only 20 patients had live births. It is necessary to expand the sample size to further evaluate the live birth rate.\u003c/p\u003e\n\u003cp\u003eIt is controversial whether patients with a previous history of PL need to be screened and treated for ANA. According to the results of this study, we recommend screening and treatment for RPL patients. For patients with a history of only one PL, screening and treatment of ANA should not be performed. However, at present, there are many related treatment schemes, and a consensus on the best treatment scheme has yet to be reached. A placebo-controlled trial in 2021 showed that the live birth rate of ANA-positive RPL patients treated with prednisone combined with aspirin did not increase significantly, but the risk of premature birth increased significantly\u0026nbsp;\u003csup\u003e30\u003c/sup\u003e. However, research by Gao et al. showed that prednisone combined with hydroxychloroquine can improve the IVF/ICSI outcome of ANA-positive patients\u0026nbsp;\u003csup\u003e31\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe advantage of this study lies in the addition of a single PL group, in which both the correlation between RPL and ANA and the relationship between single PL and ANA were investigated. In addition, due to the diverse treatment options available for ANA-positive RPL patients, to reduce their impact on the research results, this study excluded patients who had previously or were currently receiving immunological treatment.\u003c/p\u003e\n\u003cp\u003eThe limitation of this study is that it was a retrospective study, and the occurrence of selection bias could not be avoided. Second, the aetiology of embryo implantation failure is very similar to that of PL. In this study, only patients with recurrent implantation failure (RIF) were excluded, and a history of occasional implantation failure, which can be used as a confounding factor to influence the research results, was not considered. In addition, since this study did not analyse RPL patients with titres of 1:160 or above, the pregnancy outcomes of such patients cannot be determined. High-quality research is needed to confirm the impact of ANA titre on the pregnancy outcomes of RPL patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results showed that there was a correlation between ANA and RPL, but there was no significant correlation between ANA and single PL. ANA positivity (titre 1:80) was related to the occurrence of PL after RPL transplantation, and the correlation was reflected mainly in the first trimester of pregnancy. It is suggested that RPL patients should be screened and treated for ANA.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and subjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective observational case‒control study included patients who visited the Department of Reproductive Medicine at the Third Affiliated Hospital of Zhengzhou University for the first time from January 2016 to December 2022 and were tested for ANA twice within 4-6 weeks. The number of PLs was documented as the total number before the first ANA test. To reduce the influence of confounding factors, patients were excluded if they had any of the following:\u0026nbsp;①\u0026nbsp;chromosome karyotype abnormality in either spouse;\u0026nbsp;②\u0026nbsp;abnormal anatomical structure of the uterus, such as bicornuate uterus, saddle uterus, mediastinal uterus, uterine fibroids, or adenomyosis;\u0026nbsp;③\u0026nbsp;abnormal endocrinology or metabolism;\u0026nbsp;④\u0026nbsp;immunological diseases, such as APS, SLE, or SS;\u0026nbsp;⑤\u0026nbsp;prethrombotic state;\u0026nbsp;⑥\u0026nbsp;RIF; or\u0026nbsp;⑦ different\u0026nbsp;ANA test results. These patients were divided into the non-PL group (no previous PL), single-PL group (history of one previous PL) and RPL group according to the number of previous PLs to evaluate whether ANA is a risk factor for PL.\u003c/p\u003e\n\u003cp\u003ePatients with an ANA titre of 1:80 did not receive drug intervention unless they are complicated by definite rheumatic immune diseases or unless the patient needed treatment after consultation with a rheumatologist. However, most patients with an ANA titre\u0026nbsp;\u0026ge;1:160 receive immunological treatment at our hospital, and there are various treatment options available to them. Therefore, in this study, we selected patients in the RPL group who did not undergo immunological treatment and who underwent their first ETs after IVF/ICSI. According to the ANA test results, the patients were divided into the ANA1:80 subgroup and the ANA-negative subgroup to analyse the impact of ANA on pregnancy outcomes after transplantation. In addition, to reduce confounding factors, the study excluded patients who used donor sperm or eggs or who underwent IVF/ICSI with preimplantation genetic testing.\u003c/p\u003e\n\u003cp\u003eIn this paper, PL is defined as natural foetal death before 24 weeks of pregnancy, and RPL is defined as PL occurring two or more times, including non-visualized PL, according to the ESHRE guidelines\u0026nbsp;\u003csup\u003e3\u003c/sup\u003e. RIF is defined as failure to achieve pregnancy after three consecutive high-quality embryos\u0026nbsp;\u003csup\u003e32\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eANA detection method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsidering the experimental error, ANA detection should be carried out at least twice, with an interval of 4~6 weeks. It is clinically significant that the results of the two tests are the same.\u003c/p\u003e\n\u003cp\u003eDetection of ANA based on indirect immunofluorescence: Fresh blood samples should be used. Blood samples containing particulate matter were centrifuged at low speed (\u0026lt;1000\u0026times;g) to remove particles and then used within the first 8 hours after serum separation. In the first incubation, the serum was diluted to 1:32, 1:100 or higher, and the combination of HEp-2 cells and frozen sections of animal tissues was used as the matrix. Then, 35 \u0026micro;L of diluted serum was added and incubated at 20-26\u0026deg;C\u0026nbsp;for 30 minutes. For the second incubation, the cells were gently washed with distilled water diluted with 1:10 cleaning buffer and then soaked in a dyeing dish 3 times for 5 minutes each. Then, 35 \u0026micro;L of FITC-conjugated secondary antibody was added to the sample, and the sample was incubated at 20-26\u0026nbsp;℃ for 30 minutes, washed (as described above), and sealed on the tablet. The results were immediately obtained by fluorescence microscopy. Each test and result interpretation were performed with reference to positive and negative controls. When weak fluorescence appeared in the nucleus (titres between 1:80 and negative) or if the experimental results were uncertain, the samples were evaluated again.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObservation indicators and their definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical pregnancy rate was defined as the number of clinically pregnant patients/the number of total transplantation patients\u0026nbsp;\u0026times;\u0026nbsp;100%. The presence of one or more gestational sacs on ultrasound indicated a clinical pregnancy, including an intrauterine pregnancy, an ectopic pregnancy, a simultaneous intrauterine and extrauterine pregnancy, or pregnancy with only a gestational sac but no foetal heartbeat.\u003c/p\u003e\n\u003cp\u003eThe early PL rate was defined as the number of PL patients within 12 weeks of pregnancy/the number of clinically pregnant patients\u0026nbsp;\u0026times;\u0026nbsp;100%.\u003c/p\u003e\n\u003cp\u003eThe late PL rate was defined as the number of PL patients after 12 weeks and before 24 weeks of pregnancy/the number of clinically pregnant patients \u0026times;\u0026nbsp;100%.\u003c/p\u003e\n\u003cp\u003eThe total PL rate was defined as the number of PL patients before 24 weeks of pregnancy/the number of clinically pregnant patients\u0026nbsp;\u0026times;\u0026nbsp;100%.\u003c/p\u003e\n\u003cp\u003eThe ectopic pregnancy rate was defined as the number of ectopic pregnancy patients/the number of clinical pregnancy patients\u0026nbsp;\u0026times;\u0026nbsp;100%. An ectopic pregnancy was defined as a pregnancy in which a fertilized egg was implanted outside the uterine cavity, including tubal pregnancy, ovarian pregnancy, cervical pregnancy, broad ligament pregnancy and abdominal pregnancy.\u003c/p\u003e\n\u003cp\u003eThe premature birth rate was defined as the number of patients with live births between 24 and 37 weeks of pregnancy/the number of patients with live births after 24 weeks of pregnancy.\u003c/p\u003e\n\u003cp\u003eThe live birth rate was defined as the number of patients with live births after 24 weeks of pregnancy/total number of transplantation patients\u0026nbsp;\u0026times;\u0026nbsp;100%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS 26.0 software was used for statistical analysis. Normally distributed data with homogeneous variance are expressed as the mean \u0026plusmn; standard deviation (. Student\u0026apos;s t test was used for comparisons between two groups, and one-way analysis of variance was used for comparisons among multiple groups. Nonnormal distribution and/or homogeneity of variance are expressed as medians (quartiles) [M (Q1, Q3)]. The Kruskal-Wallis rank-sum test was used for comparisons between groups, with a significance level of \u0026alpha;=0.05.\u0026nbsp;Count data are expressed as the rate or composition ratio (%). The chi-square test was used for comparisons between groups. When the theoretical frequency was less than 5, Fisher\u0026rsquo;s exact probability method was used for comparisons between groups, and the significance level was set at\u0026nbsp;\u0026alpha;=0.05. The Bonferroni method was used for pairwise comparisons between multiple groups of measurement and counting data, and the corrected test level was\u0026nbsp;\u0026alpha;\u0026apos;=0.0167. Factors related to the PL were analysed by multivariate unordered logistic regression, and variables with P\u0026lt;0.05 among multiple groups were included. Univariate and multivariate logistic regression were used to correct for confounding factors related to the clinical pregnancy outcomes of RPL patients. When the clinical characteristics from the univariate logistic regression analysis showed P\u0026lt;0.10, they were included in the multivariate logistic regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the procedures of this study conformed to the 1964 Helsinki Declaration and its later amendments or similar ethical standards and passed the examination and approval of the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2023-067-01). The need to obtain informed consent was waived by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to all individuals who contributed to the completion of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eManman Liu and Hebo Zhang designed the study, analysed the data, and drafted the manuscript, both of which have equal contribution. Shilian Xu, Rui Zhang and Mengfan Yuan participated in the critical discussion and revision of the article. Bingnan Ren, Zhaozhao Liu and Yichun Guan assisted in the article writing and revising. The authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and analysed during the current study are not publicly available due to hospital\u0026apos;s privacy policy but are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project has received funding from National Key Research and Development Program of China (2021YFC2700602) and the Henan Province Medical Science and Technology Research Program (Joint Construction) project (LHGJ20190369) in China\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to M. 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Human Fertility 25, 813\u0026ndash;837. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1080/14647273.2021.1905886\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1080/14647273.2021.1905886\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"620\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\"\u003e\n \u003cp\u003eNon-PL group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\"\u003e\n \u003cp\u003eSingle-PL group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\"\u003e\n \u003cp\u003eRPL group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e1,416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e33.30 \u0026plusmn; 4.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e34.15 \u0026plusmn;4.88 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e35.34 \u0026plusmn;5.06 \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e33.00 (30.75, 37.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e34.00 (31.00, 38.00) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e35.00 (32.00, 40.00) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eFemale BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e23.69 \u0026plusmn;3.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e23.90 \u0026plusmn;3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e24.79 \u0026plusmn;3.26 \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e4.00 (2.00, 6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.60, 2.50) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.80, 2.50) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003ebFSH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e6.62 (5.49, 8.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e6.70 (5.49, 8.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e6.82 (5.79, 8.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eAMH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e18.41 (9.08, 32.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e18.92 (8.27, 31.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e12.91 (7.20, 27.99) \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eAFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e16.00 (9.75, 23.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e16.00 (10.00, 23.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e13.00 (7.00, 21.00) \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eFemale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e317 (34.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e651 (45.97%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e313 (52.17%) \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e92 (9.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e183 (12.92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e58 (9.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eFactor of both sides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e103 (11.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e270 (19.07%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e67 (11.17%) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown cause\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\" valign=\"top\"\u003e\n \u003cp\u003e418 (44.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e312 (22.03%) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e162 (27.00%) \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\"\u003e\n \u003cp\u003eANA status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\"\u003e\n \u003cp\u003eANA positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\"\u003e\n \u003cp\u003e130 (13.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e214 (15.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\"\u003e\n \u003cp\u003e122 (20.33%)\u003csup\u003e\u0026nbsp;a, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.747980613893375%\"\u003e\n \u003cp\u003eANA negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.324717285945074%\"\u003e\n \u003cp\u003e800 (86.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\" valign=\"top\"\u003e\n \u003cp\u003e1202 (84.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.617124394184167%\"\u003e\n \u003cp\u003e478 (79.67%) \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.693053311793214%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eComparisons of the characteristics of the included patients. \u003csup\u003ea\u003c/sup\u003e reports \u003cem\u003eP\u003c/em\u003e\u0026lt;0.0167 compared to the non-PL group, \u003csup\u003eb\u003c/sup\u003e reports \u003cem\u003eP\u003c/em\u003e\u0026lt;0.0167 compared to the single-PL group.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"684\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.46783625730994%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.76608187134503%\" colspan=\"3\"\u003e\n \u003cp\u003eSingle-PL group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.76608187134503%\" colspan=\"3\"\u003e\n \u003cp\u003eRPL group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\"\u003e\n \u003cp\u003e\u0026beta; value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\"\u003e\n \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\"\u003e\n \u003cp\u003e\u0026beta; value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\"\u003e\n \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.041 (1.007, 1.077)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.061 (1.020, 1.105)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.038 (1.008, 1.070)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.046 (1.011, 1.083)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eFemale BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.025 (0.995, 1.056)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.124 (1.085, 1.165)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.703 (0.676, 0.732)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.647 (0.611, 0.686)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eAMH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.002 (0.998, 1.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.005 (0.999, 1.010)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eAFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.990 (0.975, 1.006)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.972 (0.956, 0.988)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eFemale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.106 (0.812, 1.506)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\"\u003e\n \u003cp\u003e0.523\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.828 (0.558, 1.229)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eFactor of both sides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.670 (1.235, 2.258)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.824 (0.560, 1.213)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown cause\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.418 (0.337, 0.519)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e-0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e0.484 (0.372, 0.629)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\"\u003e\n \u003cp\u003eANA status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\"\u003e\n \u003cp\u003eANA negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.497803806734993%\"\u003e\n \u003cp\u003eANA positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.063 (0.814, 1.387)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\"\u003e\n \u003cp\u003e0.654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.784773060029282%\" valign=\"top\"\u003e\n \u003cp\u003e0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.10834553440703%\" valign=\"top\"\u003e\n \u003cp\u003e1.427 (1.050, 1.940)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.931185944363104%\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eThe results of the multivariate unordered logistic regression analysis with the non-PL group as the control\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"431\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.41067285382831%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"66.5893271461717%\" colspan=\"3\"\u003e\n \u003cp\u003eRPL group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e\u0026beta; value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\"\u003e\n \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e1.019 (0.986, 1.054)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e1.008 (0.980, 1.036)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eFemale BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e1.097 (1.064, 1.131)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e-0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e0.920 (0.869, 0.975)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eAMH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e1.002 (0.998, 1.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eAFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e-0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e0.973 (0.985, 0.989)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eFemale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e-0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e0.749 (0.537, 1.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eFactor on both sides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e-0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e0.493 (0.363, 0.670)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown cause\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e1.157 (0.912, 1.469)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\"\u003e\n \u003cp\u003eANA status\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\"\u003e\n \u003cp\u003eANA negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.48837209302326%\"\u003e\n \u003cp\u003eANA positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\" valign=\"top\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.604651162790695%\" valign=\"top\"\u003e\n \u003cp\u003e1.343 (1.043, 1.729)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.953488372093023%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eThe results of multivariate unordered logistic regression with the single-PL group as the control group\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"98%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.046040515653775%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17863720073665%\" valign=\"top\"\u003e\n \u003cp\u003eNon-PL group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.36279926335175%\" valign=\"top\"\u003e\n \u003cp\u003eSingle-PL group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.915285451197054%\" valign=\"top\"\u003e\n \u003cp\u003eRPL group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.046040515653775%\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17863720073665%\" valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.36279926335175%\" valign=\"top\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.915285451197054%\" valign=\"top\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.046040515653775%\"\u003e\n \u003cp\u003eANA titre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17863720073665%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.36279926335175%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.915285451197054%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.046040515653775%\"\u003e\n \u003cp\u003e1: 80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17863720073665%\"\u003e\n \u003cp\u003e88 (67.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.36279926335175%\" valign=\"top\"\u003e\n \u003cp\u003e158 (73.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.915285451197054%\"\u003e\n \u003cp\u003e87 (71.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.046040515653775%\"\u003e\n \u003cp\u003e1: 160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17863720073665%\"\u003e\n \u003cp\u003e20 (15.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.36279926335175%\" valign=\"top\"\u003e\n \u003cp\u003e39 (18.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.915285451197054%\"\u003e\n \u003cp\u003e24 (19.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.046040515653775%\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026ge;1: 320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17863720073665%\"\u003e\n \u003cp\u003e22 (16.92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.36279926335175%\" valign=\"top\"\u003e\n \u003cp\u003e17 (7.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.915285451197054%\"\u003e\n \u003cp\u003e11 (9.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eThe proportions of patients according to ANA titre in each group of ANA-positive patients.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"593\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003eANA-negative subgroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003eANA1:80 subgroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e34.38\u0026plusmn;4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e35.98\u0026plusmn;5.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u0026nbsp;age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e35.00 (32.00, 39.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e38.00 (31.25, 40.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eFemale BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e25.03\u0026plusmn;3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e23.87\u0026plusmn;2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.60, 2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e1.00 (0.60, 2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003ebFSH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e6.70 (5.54, 8.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e7.12 (5.81, 8.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eAMH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e16.09 (8.14, 33.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e11.11 (7.23, 24.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eAFC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e15.00 (9.00, 23.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e13.00 (9.00, 19.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eEndometrial thickness on the day of transplantation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e8.99\u0026plusmn;1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e9.03\u0026plusmn;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eProportion of single-embryo transfers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e50.49 (205/406)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e44.26 (27/61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eInfertility factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eFemale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e205 (50.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e41 (67.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eMale factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e41 (10.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e6 (9.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eFactor on both sides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e54 (13.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e5 (8.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eUnknown cause\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e106 (26.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e9 (14.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eType of embryo transfer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eCleavage-stage embryo transfer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e182 (44.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e26 (42.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eBlastocyst embryo transfer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e224 (55.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e35 (57.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eEmbryo\u0026nbsp;transfer\u0026nbsp;cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e0.914\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eFresh cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e89 (21.92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e13 (21.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60539629005059%\" valign=\"top\"\u003e\n \u003cp\u003eThawing cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e317 (78.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.138279932546375%\" valign=\"top\"\u003e\n \u003cp\u003e48 (78.69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.118043844856661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eComparison of the characteristics of RPL patients receiving IVF/ICSI-ET.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"778\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003eANA-negative subgroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003eANA1:80 subgroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003eUnadjusted OR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003eClinical pregnancy rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e239/406 (58.87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e31/61 (50.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e0.722 (0.421, 1.238)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e0.833 (0.454, 1.530)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.566\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003eEarly pregnancy loss rate\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e34/239 (14.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e10/31 (32.26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e2.871 (1.245, 6.624)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e2.552 (1.050, 6.206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003eLate pregnancy loss rate\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e12/239 (5.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e1/31 (3.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e0.631 (0.079, 5.023)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e0.673 (0.079, 5.763)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.718\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003eTotal pregnancy loss rate\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e46/239 (19.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e11 (35.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e2.308 (1.034, 5.151)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e2.658 (1.083, 6.521)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003eEctopic pregnancy rate\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e5/239 (2.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e0.000 (0.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003ePremature birth rate\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e23/188 (12.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e3/20 (15.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e1.006 (0.284, 3.568)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.463320463320464%\" valign=\"top\"\u003e\n \u003cp\u003eLive birth rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e188 (46.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.057915057915057%\"\u003e\n \u003cp\u003e20 (32.79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e0.566 (0.320, 0.999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.98841698841699%\"\u003e\n \u003cp\u003e0.592 (0.308, 1.137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.722007722007722%\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u0026nbsp;\u003c/strong\u003eUnivariate and multivariate logistic regression analysis of pregnancy outcomes in RPL patients receiving IVF/ICSI-ET. *\u003csup\u003e\u0026nbsp;\u003c/sup\u003erepresents the denominator of clinical pregnancy patients. **\u003csup\u003e\u0026nbsp;\u003c/sup\u003erepresents the denominator of the number of live birth patients. Clinical pregnancy rate: Female age, male age, infertility factors, bFSH, AMH, AFC, endometrial thickness on the day of transplantation, and type of embryo transfer were covariates. Early pregnancy loss rate: Female age, male age, AMH and AFC were covariates. Late pregnancy loss rate: Infertility factors, BMI, AMH and proportion of single embryo transfer were covariates. Total pregnancy loss rate: Female age, male age, BMI, AMH, AFC, proportion of single embryo transfer, and type of embryos transfer were covariates. Ectopic pregnancy rate and premature delivery rate: Univariate regression analysis of characteristics showed that all P values were \u0026gt;0.10. Live birth rate: Female age, male age, infertility factors, BMI, bFSH, AMH, AFC, endometrial thickness on the day of transplantation, and type of embryo transfer were covariates.\u003c/p\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":"Antinuclear antibody, Pregnancy loss, Recurrent pregnancy loss, Assisted reproductive technology","lastPublishedDoi":"10.21203/rs.3.rs-4580876/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4580876/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe relationship between antinuclear antibodies (ANA) and recurrent pregnancy loss (RPL) or single pregnancy loss (PL) is unclear. In this retrospective study, patients first seen at the hospital between January 2016 and December 2022 and who underwent two ANA tests within 4-6 weeks were included. After exclusion of confounding factors, patients were divided into the non-PL, single-PL or RPL group according to previous number of PLs, and the correlation between PL and ANA was analysed. The first embryo transfer (ET) after in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) without immunological treatment was selected in the RPL group, and patients were classified into the ANA-negative subgroup or ANA1:80 subgroup according to ANA titre. The effect of ANA on pregnancy outcomes in the RPL patients after IVF/ICSI-ET was further analysed. The results of multivariate unordered logistic regression showed that when the non-PL group was used as the reference, ANA positivity was an independent risk factor for RPL (P=0.023) but not for single PL (P=0.654). When the single-PL group was used as the reference, ANA positivity was an independent risk factor for RPL (P=0.022). There was no significant difference in ANA titre among the three groups of ANA-positive patients (P=0.106). Multivariate logistic regression analysis revealed that the early PL rate of the ANA1:80 subgroup was significantly higher than that of the ANA-negative subgroup (P=0.039), and the total PL rate of the ANA1:80 subgroup was significantly higher than that of the ANA-negative subgroup (P=0.033). The results showed that ANA positivity may be related to RPL occurrence, but there was no significant correlation between ANA positivity and single PL. ANA positivity (titre 1:80) is associated with PL occurrence in RPL patients after transplantation, and the correlation is reflected mainly in the first trimester. RPL patients should be screened for ANA and receive treatment.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"The correlation between ANA and pregnancy loss and their impact on IVF/ICSI-ET pregnancy outcomes in patients with recurrent pregnancy loss","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-16 17:23:47","doi":"10.21203/rs.3.rs-4580876/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":"a55446dc-ddc2-47ce-bbb9-a02ce635563b","owner":[],"postedDate":"July 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33676448,"name":"Biological sciences/Immunology/Autoimmunity"},{"id":33676449,"name":"Health sciences/Diseases/Reproductive disorders/Infertility"},{"id":33676450,"name":"Health sciences/Diseases/Reproductive disorders/Urogenital reproductive disorders"}],"tags":[],"updatedAt":"2024-09-19T09:55:31+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-16 17:23:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4580876","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4580876","identity":"rs-4580876","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}