A Validated Model for Individualized Prediction of Live Birth in Patients With Adenomyosis Undergoing Frozen-Thawed Embryo Transfer

A Validated Model for Individualized Prediction of Live Birth in Patients With Adenomyosis Undergoing Frozen-Thawed Embryo Transfer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Validated Model for Individualized Prediction of Live Birth in Patients With Adenomyosis Undergoing Frozen-Thawed Embryo Transfer Yaoqiu Wu, Rong Yang, Jie Lan, Haiyan Lin, Chunwei Cao, Xuedan Jiao, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-842214/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 Background There is few predictive tools for live birth in women with adenomyosis, which provide further personalized and clinically specific information related to individualized decisions making during IVF/ICSI treatment. Methods A total of 424 patients with adenomyosis underwent frozen-thawed embryo transfer (FET) from Jan 2013 to Dec 2019 at a public university hospital were included. The patients were randomly divided into training (n = 265) and validation (n = 159) samples for the building and testing of the nomogram, respectively. Multivariate logistic regression (MLR) was developed on the basis of clinical covariates assessed for their association with live birth. Results In all, 183 (43.16%) patients became pregnant, and 114 (26.88%) had a live birth. In the multivariable analysis of the training cohort, probability of live birth was significantly correlated with the age < 37 years old (odds ratio [OR], 3.465; 95% CI, 1.215–9.885, P = 0.020), uterine volume prior ET < 102.02 cm 3 (OR, 8.141; 95% CI, 2.170–10.542; P = 0.002), blastocyst transfer (OR, 3.231; 95% CI, 1.065–8.819, P = 0.023), twin pregnancy (OR, 0.328; 95% CI, 0.104–0.344, P = 0.005) and protocol in FET (P < 0.001). The statistical nomogram was built based on the five variates, age, uterine volume prior embryo transfer, twin pregnancy, stage of transferred embryo and protocol of FET, with an area under the curve (AUC) of 0.837 (95% confidence interval: 0.741–0.910) for the training cohort. The AUC for the validation cohort was 0.737 (95% confidence interval: 0.661–0.813), showing a satisfactory goodness-of-fit and discrimination ability in this nomogram. Conclusions Single blastocyst transfer, GnRH-a pretreated and smaller uterine size before embryo transfer contributed to increasing live birth rate in patients with adenomyosis. The user-friendly nomogram built on the risk factors of live birth in patients with adenomyosis, provides a useful guide for medical staff on individualized decisions making during the IVF/ICSI procedure. Maternal & Fetal Medicine Adenomyosis Uterine size Live birth GnRH-a prediction model. Figures Figure 1 Figure 2 Figure 3 Background Adenomyosis is a common gynecological disorder where endometrial glands and stroma surrounded by hyperplastic smooth muscle were found within the myometrium [ 1 , 2 ]. It affects up to 24.4% in infertile women, which represents a clinical issue associated with pelvic pain, excessive vaginal bleeding, enlarged uterus and infertility [ 3 , 4 ]. Adenomyosis has been reported to adversely impact fertility via abnormal uterine contractility, including altered endometrial function and receptivity, and impaired implantation [ 5 ]. Besides, patient with adenomyosis was also linked with poor obstetrical outcomes including preeclampsia, placental malposition, preterm delivery and preterm premature rupture of membrane [ 6 – 8 ]. Assisted reproduction technology (ART), including in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), is extensively being used for managing adenomyosis related infertility. ART results, however, vary according to reports, with some showing identical outcome as in patients without adenomyosis and others presenting increased miscarriage and lower clinical pregnancy rate[ 1 ]. Several studies provided evidences that enlarged uterus in adenomyosis had an adverse impact on pregnancy outcomes by the morphological and functional pathological changes [ 9 , 10 ]. In addition, results from some trials on adenomyosis showed that applying gonadotrophin-releasing hormone agonists (GnRH-a) before IVF/ICSI cycle exert positive effects on increasing clinical pregnancy rate in patients with adenomyosis [ 11 – 13 ]. The success for a patient with adenomyosis - associated infertility in IVF/ICSI procedure to achieve pregnancy depend on a number of factors. Although several scoring systems have been published to evaluate the pregnancy rate after IVF/ICSI in infertile patients, current guidelines are based on general rather than individual clinic data. Despite the availability of these models, few of them are applicable for patients with adenomyosis and cannot evaluate the chances of live birth for individual adenomyosis patient. In this aspect, setting up of a predictive calculation model in live birth with a combination of all the risk factors in patients with adenomyosis will be beneficial for medical staff in the decision-making process and promoting adherence to medication through risk informed counselling. The aim of the current study was, therefore, to develop a nomogram model on retrospective data analysis to predict the probability of live birth for patients with adenomyosis. Patients And Methods Data sources Women diagnosed as adenomyosis undergoing frozen-thawed embryo transfer during 2013 and 2019 at Sun Yat-Sen Memorial Hospital, Guangzhou, China, were screened for this retrospective cohort study. Patients were included if they had received their first frozen-thawed embryo transfer (FET) cycle with autologous embryos. Exclusion criteria included congenital uterine malformation (unicornuate, bicornuate, septate uterus), intrauterine adhesion, uterine malformation, leiomyoma. Couples who received a preimplantation genetic screening or underwent preimplantation genetic diagnosis were excluded. Indications for IVF/ICSI included the tubal factor, male factor and immunity factor. Demographic data on age, body mass index (BMI), infertility duration, basal sexual hormone levels (tested on day 2-3 of menstrual cycle), uterine volume prior to embryo transfer (ET) (long diameter × width diameter ×anteroposterior diameter × π / 6) [ 14 ], type of adenomyosis (diffusion or focal), endometrial thickness, protocol of FET were obtained from the clinical database. The diagnosis of adenomyosis was ascertained by detailed chart review, including visit notes, ultrasound and operative reports, as well as pathology reports. The diagnosis was defined with two or more transvaginal sonographic criteria included heterogeneous myometrial area, globular asymmetric uterus, irregular cystic spaces, myometrial linear striations, poor definition of the endometrial myometrial junction, myometrial anterior posterior asymmetry, thickening of the anterior and posterior myometrial wall, and increased or decreased echogenicity [ 15 , 16 ]. All identified adenomyosis cases were confirmed by two experienced sonographers. Diffuse adenomyosis was defined as outer myometrium extensive disease with endometrial glands and stroma scattered throughout the uterine musculature and focal adenomyosis included adenomyoma, was defined as grossly circumscribed adenomyotic masses within the myometrium [ 9 , 17 ]. Frozen thawed embryo transfer procedure FET was performed through a natural cycle (NC) or through hormone replacement therapy (HRT) cycles with endometrial preparation by exogenous estrogen and progesterone, or through the cycle adding gonadotrophin-releasing hormone agonists (GnRH-a) before estradiol. Among the patients with GnRH agonist pre-treatment, long-acting GnRH-a were administrated of up to three injections of 3.75mg of triptorelin acetate (Ipsen Pharma Biotech, France)[ 18 ]. No more than two embryos were transferred. The luteal supported phase was administered by vaginal administration of micronized progesterone (400 mg/day). Pregnancies were diagnosed by an increasing concentration of serum β-hCG, which was tested 14 days after embryo transfer[ 18 ]. Clinical pregnancies were confirmed by the presence of the gestational sac on vaginal ultrasound examination during the fifth week. Twin pregnancy was confirmed by ultrasound examination during the twelfth week. A live birth is defined as any live born baby after 24th week of pregnancy. Data analysis Statistics with Gaussian distribution were presented as mean ± SD and categorical variables were described as absolute frequencies (Table 1). Youden Index was used to determine the optimal cut-off point of the uterine volume related to live birth. External validation was chosen in the study so that patients enrolled were divided into a training set (n = 265) and validating set (n = 159) by the sampling techniques of random numbers. Statistical analyses were performed using the STATA 14.0 MP software and Regression Modeling Strategies (RMS, R version 3.6.3). For the nomogram establishment and the AUC measurements, we used the “regplot”, “pROC” and “rms” in R software[ 19 ]. Differences between groups were compared using Student’s t -test or Chi‐squared test as appropriate. Development and validation of the model The training cohort of 265 patients was used to develop the nomogram for predicting patient-specific the probability of live birth in women with adenomyosis. The end-point of the study was live birth rate after FET cycles. Backward variable selection was performed to determine independent covariates. Multivariate analysis was performed using the logistic regression model and including the variables that were significant at univariate analysis (P < 0.05). (Table S1). Coefficient for each independent covariates and the constant were generated in the equation by MLR analysis [ 20 ]. Variables entered into the nomogram model were age, uterine volume, stage of transferred embryo, twin pregnancy, and protocol of FET in the study. Values for each of the model covariates were mapped to points on a scale ranging from 0 to 100 and the total points obtained for each model corresponded to the probability of a live birth[ 19 ]. The model was applied to data from a sample of 159 patients (validating set) for external validation with a bootstrapping technique to obtain relatively unbiased estimates (1000 repetitions). The bootstrapping method is based on resampling obtained by randomly drawing data and replacing them with samples from the original dataset[ 21 ]. The predictive accuracy of the models was measured using the average optimism of the area under the curve (AUC). A precise prediction model would result in a plot where the observed and predicted probabilities fall along the diagonal [ 19 ]. Results Description of the study population A total of 424 patients with adenomyosis underwent frozen-thawed embryo transfer from January 2011 to December 2019 were identified as eligible and were analyzed in this study. In all, 183 (43.16%) patients became pregnant, and 114 (26.88%) had a live birth. Patients were divided into a training set and validation set by the sampling techniques of random numbers. The model was built from a training cohort of 265 patients and was validating on an independent validation cohort of 159 patients. Epidemiological, clinical, biological demographics and therapeutic strategies of the training and validation cohorts are summarized in Table 1. No significant difference was observed in the patients’ characteristics between the two cohorts. 79 patients (29.81%) had live birth in the training cohort while 35 patients (22.01%) had live birth in the validation cohort. Logistic regression analysis revealed blastocyst transfer, small uterine size and GnRH-a pretreated prior to FET improved live birth, but twin pregnancy negatively impacted live birth. The optimal cut-off point of the uterine volume prior ET related to live birth was 102.02 cm 3 (AUC = 0.603, P = 0.003) according to the Youden Index. Table S1 summarizes univariable and Multivariable analysis. According to univariable logistic regression analysis, live birth was significantly correlated with age (P = 0.018), uterine volume prior ET < 102.02 cm 3 (P < 0.001), twin pregnancy (P < 0.001), stage of transferred embryo (P = 0.012) and protocol in FET (P < 0.001). In the MLR analysis of the training cohort, probability of live birth was significantly correlated with the age < 37 years old (odds ratio [OR], 3.465; 95% CI, 1.215-9.885, P = 0.020), uterine volume prior ET < 102.02 cm 3 (OR, 8.141; 95% CI, 2.170 - 10.542; P = 0.002), blastocyst transfer (OR, 3.231; 95% CI, 1.065 - 8.819, P = 0.023), twin pregnancy (OR, 0.328; 95% CI, 0.104-0.344, P = 0.005) and protocol in FET (P < 0.001) (Fig. 1). Blastocyst transfer, small uterine size and GnRH-a pretreated were associated with an increased the probability of live birth but twin pregnancy decreased the probability. Development of the models from the training cohort On the basis of the univariable and multivariable logistic regression analysis we performed, a nomogram incorporating the significant risk factors was established to predict the probability of live birth (Fig. 2). A total score was calculated using age, stage of transferred embryo, uterine volume, twin pregnancy and protocol of FET. The equation describing the probability of live birth was: P = 1/(1 + exp (-X)), where X = 0.4755302 + 0.1091108 × V1 + 0.0882141 × V2 - 0.3309371 × V3 + 0.1281561 × V4 + 0.2339871, where V1 was age (1 if < 37 y and 0 if ≥37 y) , V2 blastocyst transfer (0 if no and 1 if yes), V3 twin pregnancy (1 if no and 0 if yes) and V4 protocol of FET(2 if GnRH-a HRT, 1 if NC, 0 if HRT), V5 uterine volume (1 if < 102.02 cm 3 , 0 if ≥102.02 cm 3 ). The nomogram derived from this equation is reported in Fig. 2. Validation of predictive accuracy No significant difference was observed between the predicted probability obtained from the bootstrap correction and the actual probabilities of live birth (P = 0.186), which implied that the nomogram was well calibrated. The model demonstrated an AUC of 0.837 (95% confidence interval: 0.741 - 0.910) in the training cohort (Fig. 3A&B), which denoted good performance. The AUC of the receiver operating characteristic (ROC) curve in the validation set was 0.737 (95% confidence interval: 0.661 - 0.813), which indicated fair performance. Discussion On the basis of 424 infertile patients with adenomyosis underwent FET, we have first created a predictive nomogram tailored to the individual patient and capable of reliably generating numerical probabilities of live birth. The nomogram was developed in a training cohort including 265 patients and tested on an external independent validation cohort including 159 patients. Both calibration and discrimination were used to evaluate the performance. This graphical tool is simple and straightforward calculator, integrating five predictive variables that was easily accessible during ART treatment constituting of age, uterine volume, protocol of FET, type of pregnancy and stage of transferred embryo. Moreover, this model firstly integrated the potential risks in fetal loss of patient with adenomyosis into one graphical calculator, which is of particular interest for clinicians to the make an informed decision on the timing and protocol of FET, stage and number of embryos to transfer. Enlarged uterus in patients negatively impacted the live birth rate as revealed by MRL in our study. Endometrial tissues within the myometrium induce hyperplasia and hypertrophy of the adjacent smooth muscle resulted in uterus enlargement which is considered as an important feature of adenomyosis[ 10 ]. Morphological and functional pathological changes caused by hyperplasia and hypertrophy of the adjacent smooth muscle weaken the scalability and coordination of uterus, which adversely influence the patient’s pregnancy and delivery procedure[ 1 , 10 , 22 ]. It’s suggested that adenomyosis patient with an enlarged uterus suffered from high rate of miscarriage, preterm delivery and small-for-gestational age [ 10 , 23 ]. In addition, Kim et al. indicated that preterm delivery in pregnant patients with adenomyosis can be predicted through uterine wall thickness measurement in second trimester [ 22 ]. Recently, a retrospective study from Li et al . demonstrated that adenomyosis patients with larger uterine volume suffered lower live birth rate due to higher incidence of miscarriage [ 9 ]. A prospective study by Hawkins et al. also revealed that women with uterine lengths longer than 9 cm were more likely to experience spontaneous abortions [ 24 ]. Consistently, uterine volume larger than 102.02 cm 3 was associated with a lower live birth rate in our study. Therefore, the use of uterine volume as a significant determinant factor in pre-pregnancy examinations should never be ignored. Routine checks for uterine size during ART treatment are beneficial for detecting patients at an increased risk, so that proper protocol for subsequent FET can be chosen and preventive measures can be taken in early pregnancy. GnRH-a pre-treatment in FET cycles significantly improved the live birth rate in our retrospective study. Consistently, several studies suggested that administration of GnRH agonist increased the implantation rate, clinical pregnancy rate, and ongoing pregnancy rate of patients with adenomyosis in FET cycles[ 11 , 25 ]. Adenomyosis tissue contained estrogen, progesterone and androgen receptors, develops in an estrogen-dependent manner[ 26 ]. Administration of GnRH agonist can suppress the hypothalamic-pituitary axis resulting in a hypoestrogenic status and then suppress the proliferation of cells derived from the endometrium reducing the size of pathologic lesions in patients with adenomyosis[ 27 , 28 ]. Moreover, the expression of aromatase cytochrome P450, a protein overexpressed in women with adenomyosis and catalyzed the conversion of androgen to estrogen, can be decreased by GnRH agonist[ 29 ]. Our results show that after adjustment for confounding factors, GnRH agonist pre-treatment is associated with increased live births in patients with adenomyosis in FET cycles. With the increasing use of embryo freezing-thawing, pretreatment with GnRH agonist is recommended for adenomyosis patients in FET cycles. Patient age has been considered to be a significant prognostic factor in reproductive medicine and frequently involved in assessing the probability of a live birth or pregnancy [ 30 ]. Uterine adenomyosis mostly occurs in women over the age of 35 years old and the average age of patients included in our study was up to 34, which was associated with adverse pregnancy outcomes in this study. Consistent with previously published studies[ 31 , 32 ], our study showed that the increased live birth rate was significantly associated with blastocyst transfer than cleavage embryo transfer. Besides, twin pregnancy a well understood risk factor of adverse obstetric outcomes[ 33 ] was a strong collective factor in our model. Therefore, single blastocyst embryo transfer, which is highly recommended in ET cycles for its high live birth rate, is encouraged in patients with adenomyosis, especially those with enlarged uterus. Still, some limitations of the present study have to be underlined. First, we could not avoid the measurement bias of uterine diameter induced by different operated clinicians. Second, diagnosis for adenomyosis relied on ultrasound results so that mild adenomyosis might have been misclassified. Third, the retrospective nature of the study cannot exclude all biases. Despite these limitations, our nomogram model to predict the live birth rate could be a useful tool in helping physicians and patients with adenomyosis undergoing the IVF/ICSI procedure to decide on embryo-transfer option and to pay special attentions during prenatal visits. Conclusion In conclusion, an objective and accurate prediction nomogram model for live birth rate was drawn up and validated in infertility patients with adenomyosis. Relative risk assessment could be performed during infertility consultation and appropriate measures could be carried out in advance to minimize the probability of fetal loss. Furthermore, our results support the concept that pretreatment of GnRH-a for reducing lesion size before FET effectively increased the probability of live birth. Abbreviations BMI, body mass index; FSH, follicular stimulating hormone; E2, estrogen; T, testosterone; HRT, Hormone replacement therapy; FET, frozen-thawed embryo transfer; IVF/ICSI, in vitro fertilization/ intracytoplasmic sperm injection; ART, assisted reproductive technology; GnRH-a, gonadotrophin-releasing hormone agonists; hCG, human chorionic gonadotropin; LBR, live birth rate; ROC, receiver operating characteristic curves; SD, standard deviation; ORs, odds ratios; CI, confidence interval. Declarations Ethics approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and with the 1964 Helsinki declaration and its later amendments. This study was approved by the ethical standards of the Ethics Committee of The Sun Yat-Sen Memorial Hospital of China (SYSEC-KY-KS-2020-127). Requirement for inform consent has been waived by the institutional ethics committee due to the retrospective nature of the study, and pseudonymization of data. Consent to Participate Not applicable Consent for Publication Not applicable Availability of Data and Materials The datasets analyzed during the current study are available from the corresponding author on reasonable request. Disclosure of interests The authors declare that they have no conflict of interest. Funding: This study was supported by the National Natural Science Foundation of China (81971332); Natural Science Foundation of Guangdong Province (2020A1515011126); and Sun Yat-Sen University Clinical Research 5010 Program (2016004). Acknowledgements The authors thank Liheng Che, Sun Yat-sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, for her technical support. Authors' contributions QZ supervised the entire study, including the procedures, conception, design and completion of the study data, HL and CC revised the article. RY JL and XJ was responsible for the collection of data. YW contributed the data collection and analysis and drafted the article. All authors contributed to the article and approved the submitted version. References Younes G, Tulandi T: Effects of adenomyosis on in vitro fertilization treatment outcomes: a meta-analysis. Fertility and sterility 2017, 108(3):483–490 e483. Ferenczy A: Pathophysiology of adenomyosis. Human reproduction update 1998, 4(4):312–322. Chapron C, Vannuccini S, Santulli P, Abrao MS, Carmona F, Fraser IS, Gordts S, Guo SW, Just PA, Noel JC et al: Diagnosing adenomyosis: an integrated clinical and imaging approach. Human reproduction update 2020, 26(3):392–411. 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Fertility and sterility 2012, 97(4):825–834. Tables Table 1. Patient characteristics in the training and the validation cohorts Characteristics a Training set n = 265 Validating set n = 159 P Live birth, n (%) 79 (29.81) 35 (22.01) 0.080 Age, years 34.05 ± 4.79 34.26 ± 4.52 0.652 Infertility duration, years 4.27 ± 3.41 4.57 ± 3.91 0.196 BMI, kg/m 2 21.41 ± 2.82 21.14 ± 2.74 0.331 AMH, IU/L 3.07 ± 2.83 3.76 ± 3.37 0.195 FSH, IU/L 8.65 ± 3.77 7.98 ± 2.13 0.087 LH, IU/L 5.27 ± 2.68 5.34 ± 2.87 0.822 E2, pg/mL 53.33 ± 15.78 46.60 ± 12.07 0.285 T, ng/mL 0.43 ± 0.24 0.46 ± 0.26 0.723 Type of Adenomyosis, n (%) 0.721 Diffuse 173 (65.29) 103 (64.78) Focal 92 (34.71) 59 (35.22) Uterine diameters prior ET Width diameter 5.41 ± 1.14 5.38 ± 1.13 0.415 Anteroposterior diameter 5.21 ± 1.11 5.30 ± 1.11 0.808 Long diameter 5.56 ± 1.05 5.67 ± 1.09 0.300 Uterine volume 84.81 ± 40.66 87.66 ± 40.35 0.485 Stage of embryo transfer 0.107 Cleavage, n (%) 53(20.00) 22 (13.84) blastocyst, n (%) 212 (80.00) 137 (86.16) Protocol of FET 0.219 HRT 115 (43.40) 58 (36.48) GnRHa-HRT 104 (39.25) 76 (47.80) NC 46 (17.35) 25 (15.72) Endometrial thickness (mm) 9.87 ± 2.72 9.91± 2.62 0.889 Pregnancy type 0.193 No pregnancy 142 (53.58) 99 (62.26) Singleton pregnancy, n (%) 71 (26.79) 37 (23.27) Twin pregnancy, n (%) 52 (19.62) 23 (14.47) Abbreviations: BMI, body mass index; AMH, anti-mullerian hormone; FSH, follicular stimulating hormone; E2, estrogen; T, testosterone; ET, embryo transfer; HRT, hormone replacement therapye; NC, nature cycle; a Continuous variable are expressed as mean ± standard deviation, SD, categorical variables as absolute frequencies, n (%). *P < 0.05 was considered statistically significant. Additional Declarations No competing interests reported. Supplementary Files TableS1.docx 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-842214","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":52770832,"identity":"5a31bebb-ca7d-4987-a2cc-3a7a9a8416d5","order_by":0,"name":"Yaoqiu Wu","email":"","orcid":"","institution":"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":false,"prefix":"","firstName":"Yaoqiu","middleName":"","lastName":"Wu","suffix":""},{"id":52770833,"identity":"5395556c-c9c2-4a21-b16c-fa8e0e055229","order_by":1,"name":"Rong Yang","email":"","orcid":"","institution":"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":false,"prefix":"","firstName":"Rong","middleName":"","lastName":"Yang","suffix":""},{"id":52770834,"identity":"b076c44f-2c01-4407-bdc4-9a9c705d0e0b","order_by":2,"name":"Jie Lan","email":"","orcid":"","institution":"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Lan","suffix":""},{"id":52770835,"identity":"8b207fc5-9095-4c80-93fb-8e485fb9bc81","order_by":3,"name":"Haiyan Lin","email":"","orcid":"","institution":"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":false,"prefix":"","firstName":"Haiyan","middleName":"","lastName":"Lin","suffix":""},{"id":52770836,"identity":"03bb252d-4398-4b3f-98a2-502dd1c137dd","order_by":4,"name":"Chunwei Cao","email":"","orcid":"","institution":"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":false,"prefix":"","firstName":"Chunwei","middleName":"","lastName":"Cao","suffix":""},{"id":52770837,"identity":"0dd35cea-7b58-4576-a458-d20e51e71771","order_by":5,"name":"Xuedan Jiao","email":"","orcid":"","institution":"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":false,"prefix":"","firstName":"Xuedan","middleName":"","lastName":"Jiao","suffix":""},{"id":52770838,"identity":"ff996aa3-f1a3-43cd-adf9-9031d558293c","order_by":6,"name":"Qingxue Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYDACCQaGA0BKjoGBsfEAkiBhLcZALQ3EawGBxAYGiF7CWuRnN288XPDrcPra9sNAW/4ctjc4wHzwNg+DXR4uLYxzjhUcntmXlrvtTGLDAca2w4kbDrAlW/MwJBfj0sIskWNwmLfHJnfbAZCWhsMJBgd4zKR5GA6AnYoNsEG0SKSbnX8Icxj/N7xaeEBaeH7YJJjdANrCwHaYccMBHja8WiQk0goO8zakGW67AbQlsS09ceZhNmPLOQbJOLXIz0je/Jnnz2F5s/PpDx98+GNtz3e8+eGNNxV2OLUAgQEDYxuUmcDQDAwRiCA+AJT9A+fU4VU6CkbBKBgFIxMAAAFZX9k7BPuVAAAAAElFTkSuQmCC","orcid":"","institution":"Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University","correspondingAuthor":true,"prefix":"","firstName":"Qingxue","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2021-08-24 11:14:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-842214/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-842214/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13780968,"identity":"16fa494d-ad3f-4923-9395-b74bd6dec9d9","added_by":"auto","created_at":"2021-09-20 15:25:28","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":83999,"visible":true,"origin":"","legend":"The Forest plot of predictive factors of live birth in Multivariable analysis of the training cohort. OR and 95% CI are presented to show the risk of predictive factors \nAbbreviations: FET, frozen-thawed embryo transfer; OR, odds ratio; CI, confidence interval; *P \u003c 0.05 was considered statistically significant","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-842214/v1/99852f666aeb5db1d2bc1e66.jpg"},{"id":13781314,"identity":"0dab427e-8bf6-4f76-9953-a0a1d3dea90a","added_by":"auto","created_at":"2021-09-20 15:28:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90372,"visible":true,"origin":"","legend":"Nomogram to predict the probability of live birth in adenomyosis related infertility patients undergoing FET. The probability of a live birth is calculated by drawing a line to the point on the axis for each of the following variables: stage of transferred embryo, age, twin pregnancy, protocol of FET and uterine volume prior ET. The points for each variable are summed and located on the total points line. Next, a vertical line is projected from the total points line to the predicted probability bottom scale to obtain the individual probability of a live birth.\nAbbreviations: FET, frozen-thawed embryo transfer;","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-842214/v1/96098a5e8ee1972facbbe334.jpg"},{"id":13780970,"identity":"4690d775-d7ce-4ed9-bf26-e68e7b8f036e","added_by":"auto","created_at":"2021-09-20 15:25:28","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73335,"visible":true,"origin":"","legend":"a: Discrimination for the training cohort. ROC curve of the model with an AUC of 0.837 (95% confidence interval: 0.741 - 0.910). b: Calibration of the nomogram to predict live birth in patients with adenomyosis undergoing FET\nAbbreviations: FET, frozen-thawed embryo transfer; CI, cervical insufficiency; ROC, Receiver Operating Characteristic Curve.","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-842214/v1/fe725c91bb4f0bf3779727fd.jpg"},{"id":19427638,"identity":"726854d0-71bd-4b38-a455-56e12a01ba8d","added_by":"auto","created_at":"2022-03-21 12:29:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":535172,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-842214/v1/81daebc8-9800-4b2a-a5ae-cc7cd7b2da57.pdf"},{"id":13780969,"identity":"1c5d745c-84de-4afe-9437-1e527d016bca","added_by":"auto","created_at":"2021-09-20 15:25:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14605,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-842214/v1/4bbd5ce7c1fad9648f9a4c8b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Validated Model for Individualized Prediction of Live Birth in Patients With Adenomyosis Undergoing Frozen-Thawed Embryo Transfer\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eAdenomyosis is a common gynecological disorder where endometrial glands and stroma surrounded by hyperplastic smooth muscle were found within the myometrium [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It affects up to 24.4% in infertile women, which represents a clinical issue associated with pelvic pain, excessive vaginal bleeding, enlarged uterus and infertility [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Adenomyosis has been reported to adversely impact fertility via abnormal uterine contractility, including altered endometrial function and receptivity, and impaired implantation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Besides, patient with adenomyosis was also linked with poor obstetrical outcomes including preeclampsia, placental malposition, preterm delivery and preterm premature rupture of membrane [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAssisted reproduction technology (ART), including \u003cem\u003ein vitro\u003c/em\u003e fertilization (IVF) and intracytoplasmic sperm injection (ICSI), is extensively being used for managing adenomyosis related infertility. ART results, however, vary according to reports, with some showing identical outcome as in patients without adenomyosis and others presenting increased miscarriage and lower clinical pregnancy rate[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Several studies provided evidences that enlarged uterus in adenomyosis had an adverse impact on pregnancy outcomes by the morphological and functional pathological changes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition, results from some trials on adenomyosis showed that applying gonadotrophin-releasing hormone agonists (GnRH-a) before IVF/ICSI cycle exert positive effects on increasing clinical pregnancy rate in patients with adenomyosis [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The success for a patient with adenomyosis - associated infertility in IVF/ICSI procedure to achieve pregnancy depend on a number of factors. Although several scoring systems have been published to evaluate the pregnancy rate after IVF/ICSI in infertile patients, current guidelines are based on general rather than individual clinic data. Despite the availability of these models, few of them are applicable for patients with adenomyosis and cannot evaluate the chances of live birth for individual adenomyosis patient. In this aspect, setting up of a predictive calculation model in live birth with a combination of all the risk factors in patients with adenomyosis will be beneficial for medical staff in the decision-making process and promoting adherence to medication through risk informed counselling.\u003c/p\u003e \u003cp\u003eThe aim of the current study was, therefore, to develop a nomogram model on retrospective data analysis to predict the probability of live birth for patients with adenomyosis.\u003c/p\u003e"},{"header":"Patients And Methods","content":"\u003cp\u003e\u003cstrong\u003eData sources\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWomen diagnosed as adenomyosis undergoing frozen-thawed embryo transfer during 2013 and 2019 at\u0026nbsp;Sun Yat-Sen Memorial Hospital, Guangzhou, China, were screened for this retrospective cohort study. Patients were included if they had received their first frozen-thawed embryo transfer (FET) cycle with autologous embryos. Exclusion criteria included congenital uterine malformation (unicornuate, bicornuate, septate uterus), intrauterine adhesion, uterine malformation, leiomyoma.\u0026nbsp;Couples who received a preimplantation genetic screening or underwent preimplantation genetic diagnosis were excluded. Indications for IVF/ICSI included the tubal factor, male factor and immunity factor. Demographic data on age, body mass index (BMI), infertility duration,\u0026nbsp;basal sexual hormone levels (tested on day 2-3 of menstrual cycle), uterine volume prior to embryo transfer (ET)\u0026nbsp;(long diameter \u0026times; width diameter \u0026times;anteroposterior diameter \u0026times; \u0026pi; / 6)\u0026nbsp;[\u003ca href=\"#_ENREF_14\" title=\"O'Donnell, 2012 #1780\"\u003e14\u003c/a\u003e], type of adenomyosis (diffusion or focal), endometrial thickness, protocol of FET were obtained from the clinical database.\u003c/p\u003e\n\u003cp\u003eThe diagnosis of adenomyosis was ascertained by detailed chart review, including visit notes, ultrasound and operative reports, as well as pathology reports. The diagnosis was defined with two or more transvaginal sonographic criteria included heterogeneous myometrial area, globular asymmetric uterus, irregular cystic spaces, myometrial linear striations, poor definition of the endometrial myometrial junction, myometrial anterior posterior asymmetry, thickening of the anterior and posterior myometrial wall, and increased or decreased echogenicity\u0026nbsp;[\u003ca href=\"#_ENREF_15\" title=\"Meredith, 2009 #523\"\u003e15\u003c/a\u003e,\u0026nbsp;\u003ca href=\"#_ENREF_16\" title=\"Tellum, 2020 #524\"\u003e16\u003c/a\u003e]. All identified adenomyosis cases were confirmed by two experienced\u0026nbsp;sonographers.\u0026nbsp;Diffuse adenomyosis was defined as outer myometrium extensive disease with endometrial glands and stroma scattered throughout the uterine musculature and focal adenomyosis included adenomyoma, was defined as grossly circumscribed adenomyotic masses\u0026nbsp;within the myometrium\u0026nbsp;[\u003ca href=\"#_ENREF_9\" title=\"Li, 2021 #513\"\u003e9\u003c/a\u003e,\u0026nbsp;\u003ca href=\"#_ENREF_17\" title=\"Grimbizis, 2014 #1846\"\u003e17\u003c/a\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFrozen thawed embryo transfer procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFET was performed through a natural cycle (NC) or through hormone replacement therapy (HRT) cycles with endometrial preparation by exogenous estrogen and progesterone, or through the cycle adding\u0026nbsp;gonadotrophin-releasing hormone agonists\u0026nbsp;(GnRH-a) before estradiol. Among the patients with GnRH agonist pre-treatment, long-acting GnRH-a were administrated of up to three injections of 3.75mg of triptorelin acetate (Ipsen Pharma Biotech, France)[\u003ca href=\"#_ENREF_18\" title=\"Li, 2019 #379\"\u003e18\u003c/a\u003e]. No more than two embryos were transferred. The luteal supported phase was administered by vaginal administration of micronized progesterone (400 mg/day). Pregnancies were diagnosed by an increasing concentration of serum \u0026beta;-hCG, which was tested 14 days after embryo transfer[\u003ca href=\"#_ENREF_18\" title=\"Li, 2019 #379\"\u003e18\u003c/a\u003e]. Clinical pregnancies were confirmed by the presence of the gestational sac on vaginal ultrasound examination during the fifth week. Twin pregnancy was confirmed by ultrasound examination during the twelfth week. A live birth is defined as any live born baby after 24th week of pregnancy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistics with Gaussian distribution were presented as mean \u0026plusmn; SD and categorical variables were described as absolute frequencies (Table 1). Youden Index was used to determine the optimal cut-off point of the uterine volume related to live birth. External validation was chosen in the study so that patients enrolled were divided into a training set (n = 265) and validating set (n = 159) by the sampling techniques of random numbers. Statistical analyses were performed using the STATA 14.0 MP software and Regression Modeling Strategies (RMS, R version 3.6.3). For the nomogram establishment and the AUC measurements, we used the \u0026ldquo;regplot\u0026rdquo;, \u0026ldquo;pROC\u0026rdquo; and \u0026ldquo;rms\u0026rdquo; in R software[\u003ca href=\"#_ENREF_19\" title=\"Wu, 2021 #1507\"\u003e19\u003c/a\u003e]. Differences between groups were compared using Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test or Chi‐squared test as appropriate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDevelopment and validation of the model\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe training cohort of 265 patients was used to develop the nomogram for predicting patient-specific the probability of live birth in women with adenomyosis. The end-point of the study was live birth rate after FET cycles. Backward variable selection was performed to determine independent covariates. Multivariate analysis was performed using the logistic regression model and including the variables that were significant at univariate analysis (P \u0026lt; 0.05). (Table S1). Coefficient for each independent covariates and the constant were generated in the equation by MLR analysis\u0026nbsp;[\u003ca href=\"#_ENREF_20\" title=\"Gao, 2020 #1508\"\u003e20\u003c/a\u003e]. Variables entered into the nomogram model were age, uterine volume, stage of transferred embryo, twin pregnancy, and protocol of FET in the study. Values for each of the model covariates were mapped to points on a scale ranging from 0 to 100 and the total points obtained for each model corresponded to the probability of a live birth[\u003ca href=\"#_ENREF_19\" title=\"Wu, 2021 #1507\"\u003e19\u003c/a\u003e].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe model was applied to data from a sample of\u0026nbsp;159 patients (validating set)\u0026nbsp;for external validation with a bootstrapping technique to obtain relatively unbiased estimates (1000 repetitions).\u0026nbsp;The bootstrapping method is based on resampling obtained by randomly drawing data and replacing them with samples from the original dataset[\u003ca href=\"#_ENREF_21\" title=\"Ouldamer, 2016 #1845\"\u003e21\u003c/a\u003e]. The predictive accuracy of the models was measured using the average optimism of the area under the curve (AUC). A precise prediction model would result in a plot where the observed and predicted probabilities fall along the diagonal\u0026nbsp;[\u003ca href=\"#_ENREF_19\" title=\"Wu, 2021 #1507\"\u003e19\u003c/a\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDescription of the study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 424 patients with\u0026nbsp;adenomyosis\u0026nbsp;underwent frozen-thawed embryo transfer from January 2011 to December 2019 were identified as eligible and were analyzed in this study.\u0026nbsp;In all, 183 (43.16%) patients became pregnant, and 114 (26.88%) had a live birth.\u0026nbsp;Patients were divided into a training set and validation set by the sampling techniques of random numbers. The model was built from a training cohort of 265 patients and was validating on an independent validation cohort of 159 patients. Epidemiological, clinical, biological demographics and therapeutic strategies of the training and validation cohorts are summarized in Table 1. No significant difference was observed in the patients\u0026rsquo; characteristics between the two cohorts. 79 patients (29.81%) had live birth in the training cohort while 35 patients (22.01%) had live birth in the validation cohort.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLogistic regression analysis revealed blastocyst transfer, small uterine size and GnRH-a pretreated prior to FET improved\u0026nbsp;live birth, but\u0026nbsp;twin pregnancy negatively impacted live birth.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe optimal cut-off point of the uterine volume\u0026nbsp;prior\u0026nbsp;ET related to live birth was 102.02 cm\u003csup\u003e3\u003c/sup\u003e (AUC = 0.603, P = 0.003) according to the Youden Index. Table S1 summarizes univariable and Multivariable analysis. According to univariable logistic regression analysis, live birth was significantly correlated with age (P = 0.018), uterine volume\u0026nbsp;prior\u0026nbsp;ET \u0026lt; 102.02 cm\u003csup\u003e3\u003c/sup\u003e (P \u0026lt; 0.001), twin pregnancy (P \u0026lt; 0.001), stage of transferred embryo (P =\u0026nbsp;0.012) and protocol in FET (P \u0026lt; 0.001). In the MLR analysis of the training cohort, probability of live birth was significantly correlated with the age \u0026lt; 37 years old (odds ratio [OR],\u0026nbsp;3.465;\u0026nbsp;95% CI,\u0026nbsp;1.215-9.885, P = 0.020), uterine volume\u0026nbsp;prior\u0026nbsp;ET \u0026lt; 102.02 cm\u003csup\u003e3\u003c/sup\u003e (OR, 8.141; 95% CI, 2.170 - 10.542; P = 0.002),\u0026nbsp;blastocyst\u0026nbsp;transfer\u0026nbsp;(OR,\u0026nbsp;3.231;\u0026nbsp;95% CI,\u0026nbsp;1.065 - 8.819, P = 0.023), twin pregnancy (OR,\u0026nbsp;0.328; 95% CI,\u0026nbsp;0.104-0.344,\u0026nbsp;P = 0.005) and protocol in FET (P \u0026lt; 0.001) (Fig. 1).\u0026nbsp;Blastocyst\u0026nbsp;transfer, small uterine size and GnRH-a pretreated were associated with an increased the probability of live birth but twin pregnancy decreased the probability.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDevelopment of the models from the training cohort\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the basis of the univariable and multivariable logistic regression analysis we performed, a nomogram incorporating the significant risk factors was established to predict the probability of live birth (Fig. 2). A total score was calculated using age, stage of transferred embryo, uterine volume, twin pregnancy and protocol of FET. The equation describing the probability of live birth was: P = 1/(1 + exp (-X)), where X = 0.4755302 + 0.1091108\u0026nbsp;\u0026times;\u0026nbsp;\u003cem\u003eV1\u0026nbsp;\u003c/em\u003e+ 0.0882141\u0026nbsp;\u0026times;\u0026nbsp;\u003cem\u003eV2\u003c/em\u003e - 0.3309371\u0026nbsp;\u0026times;\u0026nbsp;\u003cem\u003eV3\u003c/em\u003e + 0.1281561\u0026nbsp;\u0026times;\u0026nbsp;\u003cem\u003eV4\u0026nbsp;\u003c/em\u003e+ 0.2339871, where \u003cem\u003eV1\u003c/em\u003e was age (1 if \u0026lt; 37 y and 0 if\u0026nbsp;\u0026ge;37 y) , \u003cem\u003eV2\u003c/em\u003e blastocyst\u0026nbsp;transfer (0 if no and 1 if yes), \u003cem\u003eV3\u003c/em\u003e twin pregnancy (1 if no and 0 if yes) and \u003cem\u003eV4\u003c/em\u003e protocol of FET(2 if GnRH-a HRT, 1 if NC, 0 if HRT), \u003cem\u003eV5\u0026nbsp;\u003c/em\u003euterine volume (1 if \u0026lt; 102.02 cm\u003csup\u003e3\u003c/sup\u003e, 0 if\u0026nbsp;\u0026ge;102.02 cm\u003csup\u003e3\u003c/sup\u003e). The nomogram derived from this equation is reported in Fig. 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation of predictive accuracy\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo significant difference was observed between the predicted probability obtained from the bootstrap correction and the actual probabilities of live birth (P = 0.186), which implied that the nomogram was well calibrated. The model demonstrated an AUC of 0.837 (95% confidence interval: 0.741 - 0.910) in the training cohort (Fig. 3A\u0026amp;B), which denoted good performance. The AUC of the receiver operating characteristic (ROC) curve in the validation set was\u0026nbsp;0.737 (95% confidence interval:\u0026nbsp;0.661 - 0.813),\u0026nbsp;which indicated fair performance.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOn the basis of 424 infertile patients with adenomyosis underwent FET, we have first created a predictive nomogram tailored to the individual patient and capable of reliably generating numerical probabilities of live birth. The nomogram was developed in a training cohort including 265 patients and tested on an external independent validation cohort including 159 patients. Both calibration and discrimination were used to evaluate the performance. This graphical tool is simple and straightforward calculator, integrating five predictive variables that was easily accessible during ART treatment constituting of age, uterine volume, protocol of FET, type of pregnancy and stage of transferred embryo. Moreover, this model firstly integrated the potential risks in fetal loss of patient with adenomyosis into one graphical calculator, which is of particular interest for clinicians to the make an informed decision on the timing and protocol of FET, stage and number of embryos to transfer.\u003c/p\u003e \u003cp\u003eEnlarged uterus in patients negatively impacted the live birth rate as revealed by MRL in our study. Endometrial tissues within the myometrium induce hyperplasia and hypertrophy of the adjacent smooth muscle resulted in uterus enlargement which is considered as an important feature of adenomyosis[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Morphological and functional pathological changes caused by hyperplasia and hypertrophy of the adjacent smooth muscle weaken the scalability and coordination of uterus, which adversely influence the patient\u0026rsquo;s pregnancy and delivery procedure[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It\u0026rsquo;s suggested that adenomyosis patient with an enlarged uterus suffered from high rate of miscarriage, preterm delivery and small-for-gestational age [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In addition, Kim \u003cem\u003eet al.\u003c/em\u003e indicated that preterm delivery in pregnant patients with adenomyosis can be predicted through uterine wall thickness measurement in second trimester [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Recently, a retrospective study from Li \u003cem\u003eet al\u003c/em\u003e. demonstrated that adenomyosis patients with larger uterine volume suffered lower live birth rate due to higher incidence of miscarriage [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A prospective study by Hawkins \u003cem\u003eet al.\u003c/em\u003e also revealed that women with uterine lengths longer than 9 cm were more likely to experience spontaneous abortions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Consistently, uterine volume larger than 102.02 cm\u003csup\u003e3\u003c/sup\u003e was associated with a lower live birth rate in our study. Therefore, the use of uterine volume as a significant determinant factor in pre-pregnancy examinations should never be ignored. Routine checks for uterine size during ART treatment are beneficial for detecting patients at an increased risk, so that proper protocol for subsequent FET can be chosen and preventive measures can be taken in early pregnancy.\u003c/p\u003e \u003cp\u003eGnRH-a pre-treatment in FET cycles significantly improved the live birth rate in our retrospective study. Consistently, several studies suggested that administration of GnRH agonist increased the implantation rate, clinical pregnancy rate, and ongoing pregnancy rate of patients with adenomyosis in FET cycles[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Adenomyosis tissue contained estrogen, progesterone and androgen receptors, develops in an estrogen-dependent manner[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Administration of GnRH agonist can suppress the hypothalamic-pituitary axis resulting in a hypoestrogenic status and then suppress the proliferation of cells derived from the endometrium reducing the size of pathologic lesions in patients with adenomyosis[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Moreover, the expression of aromatase cytochrome P450, a protein overexpressed in women with adenomyosis and catalyzed the conversion of androgen to estrogen, can be decreased by GnRH agonist[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Our results show that after adjustment for confounding factors, GnRH agonist pre-treatment is associated with increased live births in patients with adenomyosis in FET cycles. With the increasing use of embryo freezing-thawing, pretreatment with GnRH agonist is recommended for adenomyosis patients in FET cycles.\u003c/p\u003e \u003cp\u003ePatient age has been considered to be a significant prognostic factor in reproductive medicine and frequently involved in assessing the probability of a live birth or pregnancy [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Uterine adenomyosis mostly occurs in women over the age of 35 years old and the average age of patients included in our study was up to 34, which was associated with adverse pregnancy outcomes in this study.\u003c/p\u003e \u003cp\u003eConsistent with previously published studies[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], our study showed that the increased live birth rate was significantly associated with blastocyst transfer than cleavage embryo transfer. Besides, twin pregnancy a well understood risk factor of adverse obstetric outcomes[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] was a strong collective factor in our model. Therefore, single blastocyst embryo transfer, which is highly recommended in ET cycles for its high live birth rate, is encouraged in patients with adenomyosis, especially those with enlarged uterus.\u003c/p\u003e \u003cp\u003eStill, some limitations of the present study have to be underlined. First, we could not avoid the measurement bias of uterine diameter induced by different operated clinicians. Second, diagnosis for adenomyosis relied on ultrasound results so that mild adenomyosis might have been misclassified. Third, the retrospective nature of the study cannot exclude all biases. Despite these limitations, our nomogram model to predict the live birth rate could be a useful tool in helping physicians and patients with adenomyosis undergoing the IVF/ICSI procedure to decide on embryo-transfer option and to pay special attentions during prenatal visits.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, an objective and accurate prediction nomogram model for live birth rate was drawn up and validated in infertility patients with adenomyosis. Relative risk assessment could be performed during infertility consultation and appropriate measures could be carried out in advance to minimize the probability of fetal loss. Furthermore, our results support the concept that pretreatment of GnRH-a for reducing lesion size before FET effectively increased the probability of live birth.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI, body mass index; FSH, follicular stimulating hormone; E2, estrogen; T, testosterone; HRT, Hormone replacement therapy; FET, frozen-thawed embryo transfer; IVF/ICSI, in vitro fertilization/ intracytoplasmic sperm injection; ART, assisted reproductive technology; GnRH-a, gonadotrophin-releasing hormone agonists; hCG, human chorionic gonadotropin; LBR, live birth rate; ROC, receiver operating characteristic curves; SD, standard deviation; ORs, odds ratios; CI, confidence interval.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and with the 1964 Helsinki declaration and its later amendments. This study was approved by the ethical standards of the Ethics Committee of The Sun Yat-Sen Memorial Hospital of China (SYSEC-KY-KS-2020-127). Requirement for inform consent has been waived by the institutional ethics committee due to the retrospective nature of the study, and pseudonymization of data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study was supported by the National Natural Science Foundation of China (81971332); Natural Science Foundation of Guangdong Province (2020A1515011126); and Sun Yat-Sen University Clinical Research 5010 Program (2016004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Liheng Che, Sun Yat-sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, for her technical support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQZ supervised the entire study, including the procedures, conception, design and completion of the study data, HL and CC revised the article. RY JL and XJ was responsible for the collection of data. YW contributed the data collection and analysis and drafted the article. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYounes G, Tulandi T: Effects of adenomyosis on in vitro fertilization treatment outcomes: a meta-analysis. Fertility and sterility 2017, 108(3):483\u0026ndash;490 e483.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerenczy A: Pathophysiology of adenomyosis. Human reproduction update 1998, 4(4):312\u0026ndash;322.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChapron C, Vannuccini S, Santulli P, Abrao MS, Carmona F, Fraser IS, Gordts S, Guo SW, Just PA, Noel JC et al: Diagnosing adenomyosis: an integrated clinical and imaging approach. Human reproduction update 2020, 26(3):392\u0026ndash;411.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu O, Schulze-Rath R, Grafton J, Hansen K, Scholes D, Reed SD: Adenomyosis incidence, prevalence and treatment: United States population-based study 2006\u0026ndash;2015. American journal of obstetrics and gynecology 2020, 223(1):94 e91-94 e10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarada T, Khine YM, Kaponis A, Nikellis T, Decavalas G, Taniguchi F: The Impact of Adenomyosis on Women's Fertility. Obstetrical \u0026amp; gynecological survey 2016, 71(9):557\u0026ndash;568.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuang CM, Chou P, Yen MS, Twu NF, Horng HC, Hsu WL: Adenomyosis and risk of preterm delivery. 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Journal of minimally invasive gynecology 2020, 27(2):408\u0026ndash;418 e403.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrimbizis GF, Mikos T, Tarlatzis B: Uterus-sparing operative treatment for adenomyosis. Fertility and sterility 2014, 101(2):472\u0026ndash;487.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Li R, Ouyang N, Dai K, Yuan P, Zheng L, Wang W: Investigating the impact of local inflammation on granulosa cells and follicular development in women with ovarian endometriosis. Fertility and sterility 2019, 112(5):882\u0026ndash;891 e881.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y, Liang X, Cai M, Gao L, Lan J, Yang X: Development and validation of a model for individualized prediction of cervical insufficiency risks in patients undergoing IVF/ICSI treatment. Reproductive biology and endocrinology: RB\u0026amp;E 2021, 19(1):6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao L, Li M, Wang Y, Zeng Z, Xie Y, Liu G, Li J, Zhang B, Liang X, Wei L et al: Overweight and high serum total cholesterol were risk factors for the outcome of IVF/ICSI cycles in PCOS patients and a PCOS-specific predictive model of live birth rate was established. Journal of endocrinological investigation 2020, 43(9):1221\u0026ndash;1228.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOuldamer L, Bendifallah S, Naoura I, Body G, Uzan C, Morice P, Ballester M, Darai E: Nomogram to predict live birth rate after fertility-sparing surgery for borderline ovarian tumours. Human reproduction (Oxford, England) 2016, 31(8):1732\u0026ndash;1737.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim YM, Kim SH, Kim JH, Sung JH, Choi SJ, Oh SY, Roh CR: Uterine wall thickness at the second trimester can predict subsequent preterm delivery in pregnancies with adenomyosis. Taiwanese journal of obstetrics \u0026amp; gynecology 2019, 58(5):598\u0026ndash;603.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang XP, Zhang YF, Shi R, Zhang YJ, Zhang XL, Hu XM, Hu XY, Hu YJ: Pregnancy outcomes of infertile women with ultrasound-diagnosed adenomyosis for in vitro fertilization and frozen-thawed embryo transfer. Archives of gynecology and obstetrics 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHawkins LK, Correia KF, Srouji SS, Hornstein MD, Missmer SA: Uterine length and fertility outcomes: a cohort study in the IVF population. Human reproduction (Oxford, England) 2013, 28(11):3000\u0026ndash;3006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNiu Z, Chen Q, Sun Y, Feng Y: Long-term pituitary downregulation before frozen embryo transfer could improve pregnancy outcomes in women with adenomyosis. Gynecological endocrinology: the official journal of the International Society of Gynecological Endocrinology 2013, 29(12):1026\u0026ndash;1030.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitawaki J: Adenomyosis: the pathophysiology of an oestrogen-dependent disease. Best practice \u0026amp; research Clinical obstetrics \u0026amp; gynaecology 2006, 20(4):493\u0026ndash;502.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonnez O, Donnez J: Gonadotropin-releasing hormone antagonist (linzagolix): a new therapy for uterine adenomyosis. Fertility and sterility 2020, 114(3):640\u0026ndash;645.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVannuccini S, Luisi S, Tosti C, Sorbi F, Petraglia F: Role of medical therapy in the management of uterine adenomyosis. Fertility and sterility 2018, 109(3):398\u0026ndash;405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIshihara H, Kitawaki J, Kado N, Koshiba H, Fushiki S, Honjo H: Gonadotropin-releasing hormone agonist and danazol normalize aromatase cytochrome P450 expression in eutopic endometrium from women with endometriosis, adenomyosis, or leiomyomas. Fertility and sterility 2003, 79 Suppl 1:735\u0026ndash;742.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoy SL, Cheung YB, Fortier MV, Ong CL, Tan HH, Nadarajah S, Chan JKY, Viardot-Foucault V: Age-related nomograms for antral follicle count and anti-Mullerian hormone for subfertile Chinese women in Singapore. PloS one 2017, 12(12):e0189830.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolden EC, Kashani BN, Morelli SS, Alderson D, Jindal SK, Ohman-Strickland PA, McGovern PG: Improved outcomes after blastocyst-stage frozen-thawed embryo transfers compared with cleavage stage: a Society for Assisted Reproductive Technologies Clinical Outcomes Reporting System study. Fertility and sterility 2018, 110(1):89\u0026ndash;94 e82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlujovsky D, Farquhar C, Quinteiro Retamar AM, Alvarez Sedo CR, Blake D: Cleavage stage versus blastocyst stage embryo transfer in assisted reproductive technology. The Cochrane database of systematic reviews 2016(6):CD002118.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePractice Committee of American Society for Reproductive M: Multiple gestation associated with infertility therapy: an American Society for Reproductive Medicine Practice Committee opinion. Fertility and sterility 2012, 97(4):825\u0026ndash;834.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Patient characteristics in the training and the validation cohorts\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eCharacteristics\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003en = 265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003eValidating set\u003c/p\u003e\n \u003cp\u003en = 159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eLive birth, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e79\u0026nbsp;(29.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e35 (22.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e34.05\u0026nbsp;\u0026plusmn;\u0026nbsp;4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e34.26\u0026nbsp;\u0026plusmn;\u0026nbsp;4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eInfertility duration,\u003c/p\u003e\n \u003cp\u003eyears\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e4.27\u0026nbsp;\u0026plusmn;\u0026nbsp;3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e4.57\u0026nbsp;\u0026plusmn;\u0026nbsp;3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e21.41\u0026nbsp;\u0026plusmn;\u0026nbsp;2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e21.14 \u0026plusmn; 2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.331\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eAMH, IU/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e3.07\u0026nbsp;\u0026plusmn;\u0026nbsp;2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e3.76\u0026nbsp;\u0026plusmn;\u0026nbsp;3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eFSH, IU/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e8.65 \u0026plusmn;\u0026nbsp;3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e7.98 \u0026plusmn;\u0026nbsp;2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eLH, IU/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e5.27 \u0026plusmn; 2.68\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e5.34\u0026nbsp;\u0026plusmn;\u0026nbsp;2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eE2, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e53.33\u0026nbsp;\u0026plusmn;\u0026nbsp;15.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e46.60\u0026nbsp;\u0026plusmn;\u0026nbsp;12.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eT, ng/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e0.43\u0026nbsp;\u0026plusmn;\u0026nbsp;0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e0.46\u0026nbsp;\u0026plusmn;\u0026nbsp;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.723\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eType of Adenomyosis, n (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eDiffuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e173 (65.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e103 (64.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eFocal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e92 (34.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e59 (35.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eUterine diameters prior ET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eWidth diameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e5.41 \u0026plusmn; 1.14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e5.38\u0026nbsp;\u0026plusmn;\u0026nbsp;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eAnteroposterior diameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e5.21 \u0026plusmn; 1.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e5.30\u0026nbsp;\u0026plusmn;\u0026nbsp;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eLong diameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e5.56\u0026nbsp;\u0026plusmn;\u0026nbsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e5.67\u0026nbsp;\u0026plusmn;\u0026nbsp;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eUterine volume\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e84.81 \u0026plusmn; 40.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e87.66 \u0026plusmn; 40.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eStage of embryo transfer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eCleavage, n (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e53(20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e22 (13.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eblastocyst, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e212 (80.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e137 (86.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eProtocol of FET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eHRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e115\u0026nbsp;(43.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e58\u0026nbsp;(36.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eGnRHa-HRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e104\u0026nbsp;(39.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e76\u0026nbsp;(47.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e46 (17.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e25 (15.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eEndometrial thickness (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e9.87\u0026nbsp;\u0026plusmn; 2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e9.91\u0026plusmn; 2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.889\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003ePregnancy type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e0.193\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eNo pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e142 (53.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e99 (62.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eSingleton pregnancy,\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e71 (26.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e37 (23.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.55497382198953%\"\u003e\n \u003cp\u003eTwin pregnancy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.781849912739965%\"\u003e\n \u003cp\u003e52 (19.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.352530541012218%\"\u003e\n \u003cp\u003e23 (14.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.31064572425829%\"\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\u003cp\u003e\u003cem\u003eAbbreviations: BMI, body mass index; AMH, anti-mullerian hormone; FSH, follicular stimulating hormone; E2, estrogen; T, testosterone; ET, embryo transfer; HRT, hormone replacement therapye;\u003c/em\u003e\u003cem\u003e\u0026nbsp;NC, nature cycle;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u0026nbsp;Continuous variable are expressed as mean \u0026plusmn; standard deviation, SD, categorical variables as absolute frequencies, n (%).\u0026nbsp;\u003c/em\u003e\u003cem\u003e*P \u0026lt; 0.05 was considered statistically significant.\u003c/em\u003e\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":"Adenomyosis, Uterine size, Live birth, GnRH-a, prediction model.","lastPublishedDoi":"10.21203/rs.3.rs-842214/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-842214/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThere is few predictive tools for live birth in women with adenomyosis, which provide further personalized and clinically specific information related to individualized decisions making during IVF/ICSI treatment.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 424 patients with adenomyosis underwent frozen-thawed embryo transfer (FET) from Jan 2013 to Dec 2019 at a public university hospital were included. The patients were randomly divided into training (n\u0026thinsp;=\u0026thinsp;265) and validation (n\u0026thinsp;=\u0026thinsp;159) samples for the building and testing of the nomogram, respectively. Multivariate logistic regression (MLR) was developed on the basis of clinical covariates assessed for their association with live birth.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn all, 183 (43.16%) patients became pregnant, and 114 (26.88%) had a live birth. In the multivariable analysis of the training cohort, probability of live birth was significantly correlated with the age\u0026thinsp;\u0026lt;\u0026thinsp;37 years old (odds ratio [OR], 3.465; 95% CI, 1.215\u0026ndash;9.885, P\u0026thinsp;=\u0026thinsp;0.020), uterine volume prior ET\u0026thinsp;\u0026lt;\u0026thinsp;102.02 cm\u003csup\u003e3\u003c/sup\u003e (OR, 8.141; 95% CI, 2.170\u0026ndash;10.542; P\u0026thinsp;=\u0026thinsp;0.002), blastocyst transfer (OR, 3.231; 95% CI, 1.065\u0026ndash;8.819, P\u0026thinsp;=\u0026thinsp;0.023), twin pregnancy (OR, 0.328; 95% CI, 0.104\u0026ndash;0.344, P\u0026thinsp;=\u0026thinsp;0.005) and protocol in FET (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The statistical nomogram was built based on the five variates, age, uterine volume prior embryo transfer, twin pregnancy, stage of transferred embryo and protocol of FET, with an area under the curve (AUC) of 0.837 (95% confidence interval: 0.741\u0026ndash;0.910) for the training cohort. The AUC for the validation cohort was 0.737 (95% confidence interval: 0.661\u0026ndash;0.813), showing a satisfactory goodness-of-fit and discrimination ability in this nomogram.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSingle blastocyst transfer, GnRH-a pretreated and smaller uterine size before embryo transfer contributed to increasing live birth rate in patients with adenomyosis. The user-friendly nomogram built on the risk factors of live birth in patients with adenomyosis, provides a useful guide for medical staff on individualized decisions making during the IVF/ICSI procedure.\u003c/p\u003e","manuscriptTitle":"A Validated Model for Individualized Prediction of Live Birth in Patients With Adenomyosis Undergoing Frozen-Thawed Embryo Transfer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-09-20 15:25:26","doi":"10.21203/rs.3.rs-842214/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":"5ee6d521-75be-4c72-a7a8-51f350a7c3d7","owner":[],"postedDate":"September 20th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":7297275,"name":"Maternal \u0026 Fetal Medicine"}],"tags":[],"updatedAt":"2022-03-21T12:29:22+00:00","versionOfRecord":[],"versionCreatedAt":"2021-09-20 15:25:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-842214","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-842214","identity":"rs-842214","version":["v1"]},"buildId":"B-jG_2CBjPDmsCi4Wdhf-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}