Impact of IVF/ICSI on Grades of Placenta Accreta Spectrum Disorders and Pregnancy Outcomes

Impact of IVF/ICSI on Grades of Placenta Accreta Spectrum Disorders and Pregnancy Outcomes | 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 Impact of IVF/ICSI on Grades of Placenta Accreta Spectrum Disorders and Pregnancy Outcomes Miao Hu, Lili Du, Lizi Zhang, Lin Lin, Yuliang Zhang, Shifeng Gu, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4983277/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 May, 2025 Read the published version in Reproductive Health → Version 1 posted 11 You are reading this latest preprint version Abstract Objective To investigate the impact of IVF/ICSI on grades of placenta accreta spectrum disorders and pregnancy outcomes. Methods Placenta accreta spectrum disorders patients who underwent cesarean section at a single clinical center from January 2018 to March 2023 were retrospectively included in this study. Baseline characteristics and outcomes were compared between the IVF/ICSI group and the spontaneous conception group. Binary logistic regression was used to explore the risk factors associated with adverse outcomes related to IVF/ICSI. A 1:1 ratio propensity score matching (PSM) was conducted to minimize selection bias between the two groups. Data analysis was performed using SPSS (version 25.0) software. Results No increase in the incidence of grades placenta was detected for IVF/ICSI group, and the difference is not statistically significant (P = 0.290). PAS grading is not associated with IVF/ICSI (OR = 0.76, 95%CI: 0.45 ~ 1.27, P = 0.290). In contrast, a significant risk factor for postpartum hemorrhage (OR = 9.20, 95%CI: 2.68 ~ 9.22, P < 0.001) and red cells transfusion ≥ 4U (OR = 3.71,95%CI:1.21 ~ 11.33, P = 0.021) was observed in IVF/ICSI group. No additional adverse pregnancy outcomes arose as a result of IVF/ICSI. Conclusion It is necessary to further investigation into the potential risk factors that might impact PAS grading. It has been shown that IVF/ICSI treatment is associated with a higher risk of postpartum hemorrhage and blood transfusion requirements. Therefore, in order to provide patients the best chance of recovery, professionals must carefully evaluate the patient's health as well as the available treatment options. IVF/ICSI grades of placenta outcomes postpartum hemorrhage transfusion Figures Figure 1 Introduction Placenta accreta spectrum (PAS) disorders refer to a group of conditions characterized by the abnormal invasion of placental villi into the uterine muscle to varying degrees (Jauniaux and Ayres-de-Campos, 2018 ). According to the clinical diagnostic criteria established by the International Federation of Obstetrics and Gynecology (FIGO) in 2019, PAS can be classified into grades 1–3. Grade 1 is termed adherent placenta, indicating that the placental villi adhere to the surface of the uterine muscle, while grades 2–3 are referred to as invasive placenta, signifying that the placental villi implant and penetrate into the uterine muscle (Jauniaux et al., 2019 ). PAS can result in serious adverse outcomes such as preterm birth, postpartum hemorrhage, acute organ failure, hemorrhagic shock, disseminated intravascular coagulation (DIC), and even maternal mortality (Fonseca and Ayres, 2021 ). Accumulating evidence has established a firm link between the depth of placental villous invasion and poor prognosis (Marcellin et al., 2018 ; Zhang et al., 2019 ; Riveros-Perez and Wood, 2018 ). PAS is associated with primary uterine abnormalities or secondary structural damage to the uterine wall (jauniaux et al., 2018 ). Recent years have seen an increase in individuals conceiving through in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) (hanevik and hessen, 2022 ). Some studies suggest that these patients are at a higher risk to suffer (or develop) PAS (fitzpatrick et al., 2012 , sugai et al., 2023 ). However, whether invasive placenta is the cause remains an area requiring further investigation. Given the rising utilization of IVF/ICSI in China (qiao et al., 2021 ), it is clinically significant to explore the impact of these assisted reproductive technologies on grades of PAS and pregnancy outcomes. Data and methods Patients The Department of Obstetrics and Gynecology at the Third Affiliated Hospital of Guangzhou Medical University serves as the critical care center for obstetrics and gynecology in Guangdong Province, providing comprehensive treatment to critically ill patients from across the region. We conducted a retrospective study on patients with PAS who underwent cesarean section delivery at our hospital between January 1, 2018 and March 31, 2023. The study adhered to the principles outlined in the World Medical Association Declaration of Helsinki and received approval from the Ethics Committee of the Third Affiliated Hospital of Guangzhou Medical University (approval number: 20221106). All participants provided informed consent during their hospitalization, granting permission for their clinical data to be used in research while safeguarding their privacy. Inclusion and exclusion criteria A total of 1007 patients were diagnosed with PAS and underwent cesarean section delivery. The classification system for PAS conforms to the clinical diagnosis criteria issued by FIGO in 2019 (Jauniaux et al., 2019 ). Exclusion criteria included gestational age less than 28 weeks (n = 33) and incomplete clinical data (n = 0). A total of 974 patients meet the inclusion criteria and are included in the study. Data collection Through the "Perinatal Medicine Database" and "Reproductive Medicine Database" established by the Third Affiliated Hospital of Guangzhou Medical University, we collected basic clinical characteristics of enrolled patients including age, body mass index, gravidity, parity, number of vaginal deliveries, number of cesarean sections, number of induced abortions, other etiologies of accreta placentation, progesterone supplementation in miscarriage prevention, scar pregnancy, placental location, vaginal bleeding, and placenta previa; maternal outcomes including PAS grades, postpartum hemorrhage, red blood cells transfusion ≥ 4U, and hysterectomy; and neonatal outcomes including preterm birth, neonatal birth weight, neonatal admission to NICU. Propensity score matching We used propensity score matching (PSM) to balance the clinical baseline characteristics between spontaneous conception group and IVF/ICSI group, thereby minimizing bias. The matching ratio is 1:1, with a caliper value of 0.02 SD. In the matching process, we took into consideration the clinical baseline characteristics, including age, body mass index, gravidity, parity, number of vaginal deliveries, number of cesarean sections, number of induced abortions, other etiologies of accreta placentation, progesterone supplementation in miscarriage prevention, scar pregnancy, placental location, vaginal bleeding and placenta previa. Statistical analysis The SPSS 25.0 software was utilized for data analysis. Quantitative data with non-normal distribution was denoted as M(P25 ~ P75), and inter-group comparisons were conducted using non-parametric tests. Frequency and rate are reported for the counting data, with inter-group comparisons performed using the χ2 test or Fisher’s exact test. Conditional logistic regression analysis was utilized to calculate odds ratios (OR) and corresponding 95% confidence intervals (CI) to explore the impact of IVF/ICSI on the grading of PAS; and pregnancy outcomes. A significance level of P < 0.05 is adopted. Results A total of 974 eligible patients were enrolled in the study based on predefined inclusion and exclusion criteria. Among them, 820 (84.2%) patients belonged to the spontaneous conception group, with 154 (15.8%) the IVF/ICSI group. After propensity score matching, each group is comprised of 123 patients. The matching rate for the IVF/ICSI group is 79.87%. (Refer to Fig. 1 ) Assessment of the efficacy of PSM on correcting baseline characteristics bias Before propensity score matching (PSM), the IVF/ICSI group exhibits significantly higher age (P = 0.001), a greater number of advanced age cases (P = 0.001), and increased progesterone supplementation in miscarriage prevention (P < 0.001) compared to the spontaneous conception group. Conversely, the spontaneous conception group demonstrates significantly higher gravidity (P < 0.001), parity (P < 0.001), cesarean sections (P < 0.001), induced abortions (P < 0.001), anterior placenta (P < 0.001), and placenta previa (P 0.05). (Refer to Table 1 ) Table 1 Baseline characteristics before and after PSM Characteristics Before PSM After PSM Spontaneous conception (n = 820) IVF/ICSI pregnancy (n = 154) P value Spontaneous conception (n = 123) IVF/ICSI pregnancy (n = 123) P Value Age [Year,M(P25 ~ P75 )] 34(30 ~ 37) 35(33 ~ 39) 0.001 35(32 ~ 37) 35(33 ~ 38) 0.403 Advanced age [n(%)] 370(45.1) 91(59.1) 0.001 64(52.0) 72(58.5) 0.097 Body mass index [kg/m 2 ,n(%) ] 0.469 0.825 < 18.5 88(10.7) 13(8.4) 13(10.6) 11(8.9) 18.5 ~ 24 555(67.7) 103(66.9) 87(70.7) 88(71.5) 24 ~ 28 140(17.1) 33(21.4) 18(14.6) 21(17.1) ≥ 28 37(4.5) 5(3.3) 5(4.1) 3(2.4) Gravidity [M(P25 ~ P75)] 4(3 ~ 5) 3(2 ~ 4) < 0.001 3(2 ~ 4) 3(2 ~ 4) 0.989 Parity [M(P25 ~ P75)] 1(1 ~ 2) 0(0 ~ 1) < 0.001 0(0 ~ 1) 0(0 ~ 1) 1.000 Number of vaginal deliveries [M(P25 ~ P75)] 0(0 ~ 0) 0(0 ~ 0) 0.332 0(0 ~ 0) 0(0 ~ 0) 0.704 Number of cesarean deliveries [n(%)] < 0.001 0.899 0 253(30.9) 108(70.1) 79(64.2) 78(63.4) 1 386(47.1) 36(23.4) 35(28.5) 35(28.5) 2 167(20.4) 9(5.8) 7(5.7) 9(7.3) ≥ 3 14(1.7) 1(0.6) 2(1.6) 1(0.8) Number of induced abortions [n(%)] 0.001 0.693 0 429(52.3) 106(68.8) 70(56.9) 79(64.2) 1 208(25.4) 30(19.5) 33(26.8) 28(22.8) 2 116(14.1) 13(8.4) 13(10.6) 11(8.9) ≥ 3 67(8.2) 5(3.2) 7(5.7) 5(4.1) Other etiologies of accreta placentation [n(%)] 303(37.0) 64(41.6) 0.279 48(39.0) 49(39.8) 0.896 Progesterone supplementation in miscarriage prevention [n(%)] 156(19.0) 61(39.6) < 0.001 41(33.3) 41(33.3) 1.000 Scar pregnancy [n(%)] 61(7.4) 8(5.2) 0.319 7(5.7) 6(4.9) 0.776 Placental location [n(%)] < 0.001 0.258 Anterior wall 462(56.3) 66(42.9) 61(49.6) 59(48.0) Posterior wall 221(27.0) 66(42.9) 36(29.3) 46(37.4) Others 137(16.7) 22(14.3) 26(21.1) 18(14.6) Vaginal bleeding [n(%)] 245(29.9) 43(27.9) 0.626 42(34.1) 33(26.8) 0.213 Placenta previa [n(%)] 531(64.8) 53(34.4) < 0.001 43(35.0) 48(39.0) 0.509 Advanced age :age ≥ 35years Other etiologies of accreta placentation: uterine curettage, manual delivery of the placenta,IUD,postpartum endometritis, hysteroscopic surgery, myomectomy for endometrial injury, etc. Comparison of maternal and neonatal outcomes before and after PSM Before propensity score matching (PSM), the IVF/ICSI group shows a lower incidence of invasive placenta (P < 0.001), postpartum hemorrhage (P < 0.001), red blood cells transfusion ≥ 4U (P < 0.001), and preterm delivery (P < 0.001) compared to the spontaneous conception group. No significant differences in hysterectomy (P = 0.254), birth weight (P = 0.399), and the number of newborns admitted to the NICU (P = 0.301) between the two groups were detected. After PSM, the IVF/ICSI group exhibits a significantly higher incidence of postpartum hemorrhage (P < 0.001) and red blood cells transfusion ≥ 4U (P = 0.044). In contrast, there are no statistically significant differences in PAS grades (P = 0.290), hysterectomy (P = 0.424), gestational weeks (P = 0.927), birth weight (P = 0.816), and the number of NICU admissions (P = 0.301) between the two groups (refer to Table 2 ). Table 2 Maternal and neonatal outcomes before and after PSM Outcomes Before PSM After PSM Spontaneous conception (n = 820) IVF/ICSI pregnancy (n = 154) P value Spontaneous conception (n = 123) IVF/ICSI pregnancy (n = 123) P value Maternal outcome PAS Grades [n(%)] < 0.001 0.290 Placenta crete 313(38.2) 103(66.9) 74(60.2) 82(66.7) Placenta increta 459(56.0) 50(32.5) 45(36.6) 40(32.5) Placenta percreta 48(5.9) 1(0.7) 4(3.3) 1(0.8) Postpartum hemorrhage [n(%)] 313(38.2) 25(16.2) < 0.001 3(2.4) 23(18.7) < 0.001 Red blood cells transfusion ≥ 4U [n(%)] 163(19.9) 13(8.4) < 0.001 5(4.1) 13(10.6) 0.044 Hysterectomy [n(%)] 159(19.4) 6(3.9) 0.254 9(7.3) 6(4.9) 0.424 Neonatal outcome Birth weeks [wk,n(%)] < 0.001 0.927 ≥ 28 ~ 34* 103(12.6) 22(14.3) 19(15.4) 18(14.6) 34 ~ 37* 377(46.0) 37(24.0) 33(26.8) 31(15.2) ≥ 37 340(41.5) 95(61.7) 71(57.7) 74(60.2) Birth weight [g,n(%)] 0.399 0.816 <1500 37(4.5) 10(6.5) 8(6.5) 9(7.3) 1500 ~ 2500 224(27.3) 36(23.4) 29(23.6) 25(20.3) ≥ 2500 559(68.2) 108(70.1) 86(69.9) 89(72.4) NICU [n(%)] 28(3.4) 2(1.3) 0.301 34(27.6) 27(22.0) 0.301 *preterm delivery Conditional Logistic Regression Analysis We then carried out conditional logistic regression analysis and found no link between IVF/ICSI treatment and the grades of PAS (OR = 0.76, 95% CI: 0.45–1.27, P = 0.290). In addition, IVF/ICSI did not increase the risk of hysterectomy (OR = 0.65, 95% CI: 0.22–1.88, P = 0.427), preterm birth (OR = 0.90, 95% CI: 0.54–1.50, P = 0.697), low birth weight infants (< 2500 g) (OR = 0.89, 95% CI: 0.51–1.54, P = 0.673), or neonates admitted to the NICU (OR = 0.66, 95% CI: 0.11–4.03, P = 0.654). Strikingly, however, IVF/ICSI was identified as a risk factor for postpartum hemorrhage (OR = 9.20, 95% CI: 2.68–9.20, P < 0.001) and red blood cell transfusion ≥ 4U (OR = 3.71, 95% CI: 1.21–11.33, P = 0.021 (Refer to Table 3 ) Table 3 Conditional Logistic Regression Analysis Outcomes OR 95%CI P value PAS grades 0.76 (0.45 ~ 1.27) 0.290 Postpartum hemorrhage 9.20 (2.68 ~ 9.22) <0.001 Red blood cells transfusion ≥ 4U 3.71 (1.21 ~ 11.33) 0.021 Hysterectomy 0.65 (0.22 ~ 1.88) 0.427 Birth week<37 0.90 (0.54 ~ 1.50) 0.697 Birth weight<2500g 0.89 (0.51 ~ 1.54) 0.673 NICU 0.66 (0.11 ~ 4.03) 0.654 Discussion Applying propensity score matching effectively rectify confounding biases Propensity Score Matching (PSM) effectively mitigates selection bias in observational studies, allowing a more reliable assessment of treatment or intervention impacts on study outcomes. Without PSM, we found that advanced age (P = 0.001) (Yin et al., 2024 ), progesterone supplementation in miscarriage prevention (P < 0.001) (Matsuzaki et al., 2021 ), gravidity (P < 0.001) (Zhao et al., 2024 ), parity (P < 0.001) (Zhao et al., 2024 ), cesarean sections (P < 0.001) (Calì et al., 2013 ), induced abortions (P < 0.001) (Li et al., 2023 ), and anterior wall (P < 0.001) (Zhu and Xie, 2019 ) and placenta previa (P < 0.001) (Kayem et al., 2024 ) are associated with PAS. When these baseline features are statistically different and have impacts on PAS, it cannot effectively explain whether PAS is related to IVF/ICSI. By ensuring consistency in individual baseline features across different groups and accounting for the confounding variables, PSM enhances internal validity and credibility of the research results (Huang Lihong and ChenFeng, 2019). Impact of IVF/ICSI on grades of PAS Currently, there is a lack of robust evidence regarding risk factors for PAS grades, due to the low incidence of PAS and an overreliance on pathological diagnosis. Over the past 40 years, the incidence rate of PAS has increased tenfold globally, ranging from 0.01–1.1% (Jauniaux et al., 2019 ). Prior to the publication of clinical grading criteria, the grading of PAS relied solely on the pathologist's conclusions. However, the proportion of patients undergoing partial or total hysterectomy due to PAS remains small. It is plausible that only a portion of the placenta is abnormally implanted, leading to false negatives in pathological diagnoses. Consequently, studies focusing solely on grades of PAS based on pathological findings are scarce. In recent years, as morbidity and adverse outcomes associated with PAS have risen, attention has shifted toward understanding risk factors for PAS classification. A multicenter retrospective study in the United States revealed that PAS incidence increases with the number of cesarean sections (ranging from 3–67% for 1 to 5 prior cesarean sections) (Calì et al., 2013 ). However, another meta-analysis found that placenta previa combined with cesarean section histories does not significantly affect PAS classification (Jauniaux and Bhide, 2017 ). Considering the impact of placenta previa and cesarean section histories on PAS, we turned our attention to IVF/ICSI. IVF/ICSI conception has been found by several groups to be associated with PAS incidence (Hou et al., 2021 , Kyozuka et al., 2019 ). In our study, we found no statistically significant difference in PAS grades between IVF/ICSI pregnancies and spontaneous pregnancies (P = 0.290). Furthermore, conditional logistic regression analysis also shows that IVF/ICSI does not affect the PAS grades (OR = 0.76, 95% CI: 0.45–1.27, P = 0.290). The effect of IVF/ICSI conception on PAS grades may be related to the endometrial thickness and estrogen levels (Matsuzaki et al., 2021 ). IVF/ICSI potentially raises risk of postpartum bleeding and blood transfusion In this study, we found that IVF/ICSI conception is associated with an increased risk of postpartum hemorrhage (OR = 9.20, 95% CI: 2.68–9.20, P < 0.001) and red blood cells transfusion ≥ 4U (OR = 3.71, 95% CI: 1.21–11.33, P = 0.021). These findings align with a retrospective cohort study that compared postnatal bleeding in 1064 IVF/ICSI pregnancies with 2059 spontaneous pregnancies. The incidence of severe postnatal bleeding is significantly higher in single pregnancies resulting from IVF/ICSI (aOR = 1.58, 95% CI: 1.12–2.24, P = 0.010) compared to spontaneous conceptions (Nyfløt et al., 2017 ). While propensity score matching corrected for confounding factors related to postpartum hemorrhage (such as advanced age, placenta previa, and grades), some variables remain unaccounted for. Detailed records of IVF/ICSI treatment specifics (e.g., anticoagulant drug dosages and withdrawal times) and reasons for using IVF/ICSI (e.g., endometriosis) are not available in the case records. These unmeasured factors may contribute to the increased risk observed. Notably, IVF/ICSI pregnancies represent a high-risk group for postpartum hemorrhage, emphasizing the importance of vigilant hemoglobin management during pregnancy and preparedness for blood product storage. If necessary, transferring patients to hospitals with rescue capabilities is advisable. Limitations of this study While this study provides valuable insights, it is essential to acknowledge its limitations. The data are derived from a single-center with a limited sample size. Although propensity score matching adjusts for numerous confounding factors, it only balances observed indicator variables. Additionally, SPSS propensity score matching achieves 1:1 matching between the experimental and control groups based on propensity scores but does not assess the balance of matched data. These limitations may introduce outcome bias. To validate the findings, prospective multi-center, large-sample case-control studies are warranted. Conclusion In summary, although IVF/ICSI conception is associated with the incidence of PAS, it does not influence PAS grades. However, it’s imperative to look for de novo risk factors affecting PAS severity. While IVF/ICSI pregnancies adds to the risk of postpartum bleeding and blood transfusion, they do not increase hysterectomy rates or adverse neonatal outcomes. Clinicians should consider patients’ expectations, medical history, local delivery management, and assistance capabilities when assessing IVF/ICSI pregnancy prognosis Declarations Disclosure Author Contributions: conceptualization, Miao Hu, Lili Du, Shuang Zhang and Dunjin Chen; methodology, Miao Hu and Lizi Zhang; software and analysis, Miao Hu ,Shuang Zhang, Lili Du and Dunjin Chen; Validation, Miao Hu, Lin Lin and Lizi Zhang; resources, Lili Du,Shuang Zhang and Dunjin Chen, data curation, Yuliang Zhang, Shifeng Gu, Zhongjia Gu, JingYing Liang, Siying Lai, Yu Liu, Minshan Huang, Yuanyuan Huang, Qingqing Huang,Shijun Luo. Founding National Key R&D Program (2022YFC2704501, 2022YFC2704503) Institutional Review Board Statement: The study adheres to the principles outlined in the World Medical Association Declaration of Helsinki and received approval from the Ethics Committee of the Third Affiliated Hospital of Guangzhou Medical University (approval number: 20221106). 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Huang Lihong & Chen Feng(2019), “The propensity score method and it`s application”,Chinese Journal of Preventive Medicine,No. 7, pp. 752-756. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 May, 2025 Read the published version in Reproductive Health → Version 1 posted Editorial decision: Revision requested 13 Jan, 2025 Reviewers agreed at journal 30 Nov, 2024 Reviewers agreed at journal 28 Nov, 2024 Reviews received at journal 18 Oct, 2024 Reviewers agreed at journal 17 Oct, 2024 Reviewers agreed at journal 17 Oct, 2024 Reviewers agreed at journal 13 Oct, 2024 Reviewers invited by journal 11 Oct, 2024 Editor assigned by journal 28 Aug, 2024 Submission checks completed at journal 28 Aug, 2024 First submitted to journal 27 Aug, 2024 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4983277","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":351419905,"identity":"a652c0a8-cc57-474d-85a0-b6126a40e307","order_by":0,"name":"Miao Hu","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Miao","middleName":"","lastName":"Hu","suffix":""},{"id":351419907,"identity":"e711a126-72be-45c5-9f0a-89227c3c9097","order_by":1,"name":"Lili Du","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Du","suffix":""},{"id":351419909,"identity":"11261ac8-46a7-427b-869c-0bcc40060dda","order_by":2,"name":"Lizi Zhang","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lizi","middleName":"","lastName":"Zhang","suffix":""},{"id":351419910,"identity":"9eddf96c-4c68-4275-9021-7c278070db0e","order_by":3,"name":"Lin Lin","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Lin","suffix":""},{"id":351419912,"identity":"b0bbedbb-8f0e-4f50-a2b0-193f66417fa2","order_by":4,"name":"Yuliang Zhang","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical 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University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Minshan","middleName":"","lastName":"Huang","suffix":""},{"id":351419920,"identity":"7d17bdfa-c201-4a6d-875c-72de6fa1de04","order_by":11,"name":"Yuanyuan Huang","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Huang","suffix":""},{"id":351419921,"identity":"e68a4d1c-842a-475c-9111-02bc2b9e5ff5","order_by":12,"name":"Qingqing Huang","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qingqing","middleName":"","lastName":"Huang","suffix":""},{"id":351419922,"identity":"7c5b1d51-adf8-47a1-9cbb-b502812e6fe8","order_by":13,"name":"Shijun Luo","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shijun","middleName":"","lastName":"Luo","suffix":""},{"id":351419926,"identity":"e832ae85-2557-4ad5-b4f2-656bbd91d097","order_by":14,"name":"Shuang Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYDACCShpAKI+MDAkgPk8hLVYgLUwziBBSwVYCzMPMVrkZ/cYfi74JWFvzn728GubX3V5ujMSGB+8bWOQN8ehxeDOGWPpmX0SzJY9eWnWuX1sxWY3EpgN57YxGO5swKFFIsdAmrdHgs3gQI6ZcW4PT+K2Gwls0rxtDAkGB3A4bEaO8W+gFh6D82/MjC17JEBa2H/j08JwI8dMmueHhITBjRzjxww/DMC2MOPTYnAjrcyat0HCwODGGzPG3oaExG1nHjZLzjknYbgBp8OSN9/m+VNnb3A+x/jDjz91iduOJx/88KbMRh6nw0CAsQ1MsUlAGIwNDLD4wg3+gEnmD1DGKBgFo2AUjAIUAACOglz4kA5NzwAAAABJRU5ErkJggg==","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Shuang","middleName":"","lastName":"Zhang","suffix":""},{"id":351419928,"identity":"ad74c1d1-c289-403f-93d7-a27d5abac6e9","order_by":15,"name":"Dunjin Chen","email":"","orcid":"","institution":"Third Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dunjin","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-08-27 09:26:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4983277/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4983277/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12978-025-02031-z","type":"published","date":"2025-05-19T15:57:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66886360,"identity":"0f73a87a-8596-469b-964b-45002f3ff938","added_by":"auto","created_at":"2024-10-17 13:48:49","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":39518,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient selection.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4983277/v1/d892525a2d877225fa8b2cd4.jpeg"},{"id":83460647,"identity":"bf35eb8a-8fdf-4e07-807c-08ac87a56351","added_by":"auto","created_at":"2025-05-26 16:13:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1102691,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4983277/v1/bb462000-dc7d-40fa-8818-fc5ea695e5bd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of IVF/ICSI on Grades of Placenta Accreta Spectrum Disorders and Pregnancy Outcomes","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePlacenta accreta spectrum (PAS) disorders refer to a group of conditions characterized by the abnormal invasion of placental villi into the uterine muscle to varying degrees (Jauniaux and Ayres-de-Campos, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). According to the clinical diagnostic criteria established by the International Federation of Obstetrics and Gynecology (FIGO) in 2019, PAS can be classified into grades 1\u0026ndash;3. Grade 1 is termed adherent placenta, indicating that the placental villi adhere to the surface of the uterine muscle, while grades 2\u0026ndash;3 are referred to as invasive placenta, signifying that the placental villi implant and penetrate into the uterine muscle (Jauniaux et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). PAS can result in serious adverse outcomes such as preterm birth, postpartum hemorrhage, acute organ failure, hemorrhagic shock, disseminated intravascular coagulation (DIC), and even maternal mortality (Fonseca and Ayres, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Accumulating evidence has established a firm link between the depth of placental villous invasion and poor prognosis (Marcellin et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Riveros-Perez and Wood, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePAS is associated with primary uterine abnormalities or secondary structural damage to the uterine wall (jauniaux et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Recent years have seen an increase in individuals conceiving through in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI) (hanevik and hessen, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Some studies suggest that these patients are at a higher risk to suffer (or develop) PAS (fitzpatrick et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, sugai et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, whether invasive placenta is the cause remains an area requiring further investigation. Given the rising utilization of IVF/ICSI in China (qiao et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), it is clinically significant to explore the impact of these assisted reproductive technologies on grades of PAS and pregnancy outcomes.\u003c/p\u003e"},{"header":"Data and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003e The Department of Obstetrics and Gynecology at the Third Affiliated Hospital of Guangzhou Medical University serves as the critical care center for obstetrics and gynecology in Guangdong Province, providing comprehensive treatment to critically ill patients from across the region. We conducted a retrospective study on patients with PAS who underwent cesarean section delivery at our hospital between January 1, 2018 and March 31, 2023. The study adhered to the principles outlined in the World Medical Association Declaration of Helsinki and received approval from the Ethics Committee of the Third Affiliated Hospital of Guangzhou Medical University (approval number: 20221106). All participants provided informed consent during their hospitalization, granting permission for their clinical data to be used in research while safeguarding their privacy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003eA total of 1007 patients were diagnosed with PAS and underwent cesarean section delivery. The classification system for PAS conforms to the clinical diagnosis criteria issued by FIGO in 2019 (Jauniaux et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Exclusion criteria included gestational age less than 28 weeks (n\u0026thinsp;=\u0026thinsp;33) and incomplete clinical data (n\u0026thinsp;=\u0026thinsp;0). A total of 974 patients meet the inclusion criteria and are included in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eThrough the \"Perinatal Medicine Database\" and \"Reproductive Medicine Database\" established by the Third Affiliated Hospital of Guangzhou Medical University, we collected basic clinical characteristics of enrolled patients including age, body mass index, gravidity, parity, number of vaginal deliveries, number of cesarean sections, number of induced abortions, other etiologies of accreta placentation, progesterone supplementation in miscarriage prevention, scar pregnancy, placental location, vaginal bleeding, and placenta previa; maternal outcomes including PAS grades, postpartum hemorrhage, red blood cells transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U, and hysterectomy; and neonatal outcomes including preterm birth, neonatal birth weight, neonatal admission to NICU.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePropensity score matching\u003c/h2\u003e \u003cp\u003eWe used propensity score matching (PSM) to balance the clinical baseline characteristics between spontaneous conception group and IVF/ICSI group, thereby minimizing bias. The matching ratio is 1:1, with a caliper value of 0.02 SD. In the matching process, we took into consideration the clinical baseline characteristics, including age, body mass index, gravidity, parity, number of vaginal deliveries, number of cesarean sections, number of induced abortions, other etiologies of accreta placentation, progesterone supplementation in miscarriage prevention, scar pregnancy, placental location, vaginal bleeding and placenta previa.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe SPSS 25.0 software was utilized for data analysis. Quantitative data with non-normal distribution was denoted as M(P25\u0026thinsp;~\u0026thinsp;P75), and inter-group comparisons were conducted using non-parametric tests. Frequency and rate are reported for the counting data, with inter-group comparisons performed using the χ2 test or Fisher\u0026rsquo;s exact test. Conditional logistic regression analysis was utilized to calculate odds ratios (OR) and corresponding 95% confidence intervals (CI) to explore the impact of IVF/ICSI on the grading of PAS; and pregnancy outcomes. A significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 is adopted.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 974 eligible patients were enrolled in the study based on predefined inclusion and exclusion criteria. Among them, 820 (84.2%) patients belonged to the spontaneous conception group, with 154 (15.8%) the IVF/ICSI group. After propensity score matching, each group is comprised of 123 patients. The matching rate for the IVF/ICSI group is 79.87%. (Refer to Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAssessment of the efficacy of PSM on correcting baseline characteristics bias\u003c/p\u003e \u003cp\u003eBefore propensity score matching (PSM), the IVF/ICSI group exhibits significantly higher age (P\u0026thinsp;=\u0026thinsp;0.001), a greater number of advanced age cases (P\u0026thinsp;=\u0026thinsp;0.001), and increased progesterone supplementation in miscarriage prevention (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to the spontaneous conception group. Conversely, the spontaneous conception group demonstrates significantly higher gravidity (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), parity (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), cesarean sections (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), induced abortions (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), anterior placenta (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and placenta previa (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than the IVF/ICSI group. After PSM, no statistically significant differences were observed in all baseline characteristics between the two groups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). (Refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics before and after PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAfter PSM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpontaneous conception\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;820)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVF/ICSI pregnancy\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;154)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003cp\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpontaneous conception\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIVF/ICSI pregnancy\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge [Year,M(P25\u0026thinsp;~\u0026thinsp;P75 )]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34(30\u0026thinsp;~\u0026thinsp;37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(33\u0026thinsp;~\u0026thinsp;39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35(32\u0026thinsp;~\u0026thinsp;37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35(33\u0026thinsp;~\u0026thinsp;38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.403\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdvanced age [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e370(45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91(59.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64(52.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72(58.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index [kg/m\u003csup\u003e2\u003c/sup\u003e,n(%) ]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88(10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18.5\u0026thinsp;~\u0026thinsp;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e555(67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103(66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87(70.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88(71.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u0026thinsp;~\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140(17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18(14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21(17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGravidity [M(P25\u0026thinsp;~\u0026thinsp;P75)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(3\u0026thinsp;~\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(2\u0026thinsp;~\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(2\u0026thinsp;~\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(2\u0026thinsp;~\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity [M(P25\u0026thinsp;~\u0026thinsp;P75)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(1\u0026thinsp;~\u0026thinsp;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0\u0026thinsp;~\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0(0\u0026thinsp;~\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0(0\u0026thinsp;~\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of vaginal deliveries\u003c/p\u003e \u003cp\u003e[M(P25\u0026thinsp;~\u0026thinsp;P75)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0\u0026thinsp;~\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0\u0026thinsp;~\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0(0\u0026thinsp;~\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0(0\u0026thinsp;~\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of cesarean deliveries [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e253(30.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108(70.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79(64.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78(63.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e386(47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35(28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35(28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167(20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9(7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of induced abortions [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e429(52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106(68.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70(56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79(64.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208(25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33(26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28(22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116(14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11(8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67(8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5(4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther etiologies of accreta placentation [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e303(37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64(41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48(39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49(39.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgesterone supplementation in miscarriage prevention [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156(19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61(39.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScar pregnancy [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61(7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6(4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacental location [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.258\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior wall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e462(56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61(49.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59(48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior wall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221(27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36(29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46(37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137(16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26(21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18(14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal bleeding [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245(29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42(34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33(26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacenta previa [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e531(64.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(34.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43(35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48(39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAdvanced age :age\u0026thinsp;\u0026ge;\u0026thinsp;35years\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOther etiologies of accreta placentation: uterine curettage, manual delivery of the placenta,IUD,postpartum endometritis, hysteroscopic surgery, myomectomy for endometrial injury, etc.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eComparison of maternal and neonatal outcomes before and after PSM\u003c/h2\u003e \u003cp\u003eBefore propensity score matching (PSM), the IVF/ICSI group shows a lower incidence of invasive placenta (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), postpartum hemorrhage (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), red blood cells transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and preterm delivery (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to the spontaneous conception group. No significant differences in hysterectomy (P\u0026thinsp;=\u0026thinsp;0.254), birth weight (P\u0026thinsp;=\u0026thinsp;0.399), and the number of newborns admitted to the NICU (P\u0026thinsp;=\u0026thinsp;0.301) between the two groups were detected. After PSM, the IVF/ICSI group exhibits a significantly higher incidence of postpartum hemorrhage (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and red blood cells transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U (P\u0026thinsp;=\u0026thinsp;0.044). In contrast, there are no statistically significant differences in PAS grades (P\u0026thinsp;=\u0026thinsp;0.290), hysterectomy (P\u0026thinsp;=\u0026thinsp;0.424), gestational weeks (P\u0026thinsp;=\u0026thinsp;0.927), birth weight (P\u0026thinsp;=\u0026thinsp;0.816), and the number of NICU admissions (P\u0026thinsp;=\u0026thinsp;0.301) between the two groups (refer to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMaternal and neonatal outcomes before and after PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAfter PSM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpontaneous conception\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;820)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVF/ICSI pregnancy\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;154)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003cp\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpontaneous conception\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIVF/ICSI pregnancy\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003cp\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eMaternal outcome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS Grades [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacenta crete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e313(38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103(66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74(60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82(66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacenta increta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e459(56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50(32.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45(36.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40(32.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlacenta percreta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48(5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostpartum hemorrhage [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e313(38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23(18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed blood cells transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163(19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(8.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13(10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHysterectomy [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e159(19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9(7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6(4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.424\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eNeonatal outcome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weeks [wk,n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;28\u0026thinsp;~\u0026thinsp;34*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103(12.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18(14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u0026thinsp;~\u0026thinsp;37*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e377(46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33(26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31(15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e340(41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95(61.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71(57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74(60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight [g,n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;1500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9(7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1500\u0026thinsp;~\u0026thinsp;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224(27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29(23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25(20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e559(68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108(70.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86(69.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89(72.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNICU [n(%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28(3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34(27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27(22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*preterm delivery\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eConditional Logistic Regression Analysis\u003c/h2\u003e \u003cp\u003eWe then carried out conditional logistic regression analysis and found no link between IVF/ICSI treatment and the grades of PAS (OR\u0026thinsp;=\u0026thinsp;0.76, 95% CI: 0.45\u0026ndash;1.27, P\u0026thinsp;=\u0026thinsp;0.290).\u003c/p\u003e \u003cp\u003eIn addition, IVF/ICSI did not increase the risk of hysterectomy (OR\u0026thinsp;=\u0026thinsp;0.65, 95% CI: 0.22\u0026ndash;1.88, P\u0026thinsp;=\u0026thinsp;0.427), preterm birth (OR\u0026thinsp;=\u0026thinsp;0.90, 95% CI: 0.54\u0026ndash;1.50, P\u0026thinsp;=\u0026thinsp;0.697), low birth weight infants (\u0026lt;\u0026thinsp;2500 g) (OR\u0026thinsp;=\u0026thinsp;0.89, 95% CI: 0.51\u0026ndash;1.54, P\u0026thinsp;=\u0026thinsp;0.673), or neonates admitted to the NICU (OR\u0026thinsp;=\u0026thinsp;0.66, 95% CI: 0.11\u0026ndash;4.03, P\u0026thinsp;=\u0026thinsp;0.654). Strikingly, however, IVF/ICSI was identified as a risk factor for postpartum hemorrhage (OR\u0026thinsp;=\u0026thinsp;9.20, 95% CI: 2.68\u0026ndash;9.20, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and red blood cell transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U (OR\u0026thinsp;=\u0026thinsp;3.71, 95% CI: 1.21\u0026ndash;11.33, P\u0026thinsp;=\u0026thinsp;0.021 (Refer to Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConditional Logistic Regression Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAS grades\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.45\u0026thinsp;~\u0026thinsp;1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostpartum hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(2.68\u0026thinsp;~\u0026thinsp;9.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed blood cells transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(1.21\u0026thinsp;~\u0026thinsp;11.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHysterectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.22\u0026thinsp;~\u0026thinsp;1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth week\u0026lt;37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.54\u0026thinsp;~\u0026thinsp;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight\u0026lt;2500g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.51\u0026thinsp;~\u0026thinsp;1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e(0.11\u0026thinsp;~\u0026thinsp;4.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eApplying propensity score matching effectively rectify confounding biases\u003c/h2\u003e \u003cp\u003ePropensity Score Matching (PSM) effectively mitigates selection bias in observational studies, allowing a more reliable assessment of treatment or intervention impacts on study outcomes. Without PSM, we found that advanced age (P\u0026thinsp;=\u0026thinsp;0.001) (Yin et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), progesterone supplementation in miscarriage prevention (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Matsuzaki et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), gravidity (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Zhao et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), parity (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Zhao et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), cesarean sections (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Cal\u0026igrave; et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), induced abortions (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Li et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and anterior wall (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Zhu and Xie, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and placenta previa (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Kayem et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) are associated with PAS. When these baseline features are statistically different and have impacts on PAS, it cannot effectively explain whether PAS is related to IVF/ICSI. By ensuring consistency in individual baseline features across different groups and accounting for the confounding variables, PSM enhances internal validity and credibility of the research results (Huang Lihong and ChenFeng, 2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImpact of IVF/ICSI on grades of PAS\u003c/h2\u003e \u003cp\u003eCurrently, there is a lack of robust evidence regarding risk factors for PAS grades, due to the low incidence of PAS and an overreliance on pathological diagnosis. Over the past 40 years, the incidence rate of PAS has increased tenfold globally, ranging from 0.01\u0026ndash;1.1% (Jauniaux et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Prior to the publication of clinical grading criteria, the grading of PAS relied solely on the pathologist's conclusions. However, the proportion of patients undergoing partial or total hysterectomy due to PAS remains small. It is plausible that only a portion of the placenta is abnormally implanted, leading to false negatives in pathological diagnoses. Consequently, studies focusing solely on grades of PAS based on pathological findings are scarce.\u003c/p\u003e \u003cp\u003eIn recent years, as morbidity and adverse outcomes associated with PAS have risen, attention has shifted toward understanding risk factors for PAS classification. A multicenter retrospective study in the United States revealed that PAS incidence increases with the number of cesarean sections (ranging from 3\u0026ndash;67% for 1 to 5 prior cesarean sections) (Cal\u0026igrave; et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, another meta-analysis found that placenta previa combined with cesarean section histories does not significantly affect PAS classification (Jauniaux and Bhide, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConsidering the impact of placenta previa and cesarean section histories on PAS, we turned our attention to IVF/ICSI. IVF/ICSI conception has been found by several groups to be associated with PAS incidence (Hou et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Kyozuka et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In our study, we found no statistically significant difference in PAS grades between IVF/ICSI pregnancies and spontaneous pregnancies (P\u0026thinsp;=\u0026thinsp;0.290). Furthermore, conditional logistic regression analysis also shows that IVF/ICSI does not affect the PAS grades (OR\u0026thinsp;=\u0026thinsp;0.76, 95% CI: 0.45\u0026ndash;1.27, P\u0026thinsp;=\u0026thinsp;0.290). The effect of IVF/ICSI conception on PAS grades may be related to the endometrial thickness and estrogen levels (Matsuzaki et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eIVF/ICSI potentially raises risk of postpartum bleeding and blood transfusion\u003c/h2\u003e \u003cp\u003eIn this study, we found that IVF/ICSI conception is associated with an increased risk of postpartum hemorrhage (OR\u0026thinsp;=\u0026thinsp;9.20, 95% CI: 2.68\u0026ndash;9.20, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and red blood cells transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U (OR\u0026thinsp;=\u0026thinsp;3.71, 95% CI: 1.21\u0026ndash;11.33, P\u0026thinsp;=\u0026thinsp;0.021). These findings align with a retrospective cohort study that compared postnatal bleeding in 1064 IVF/ICSI pregnancies with 2059 spontaneous pregnancies. The incidence of severe postnatal bleeding is significantly higher in single pregnancies resulting from IVF/ICSI (aOR\u0026thinsp;=\u0026thinsp;1.58, 95% CI: 1.12\u0026ndash;2.24, P\u0026thinsp;=\u0026thinsp;0.010) compared to spontaneous conceptions (Nyfl\u0026oslash;t et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile propensity score matching corrected for confounding factors related to postpartum hemorrhage (such as advanced age, placenta previa, and grades), some variables remain unaccounted for. Detailed records of IVF/ICSI treatment specifics (e.g., anticoagulant drug dosages and withdrawal times) and reasons for using IVF/ICSI (e.g., endometriosis) are not available in the case records. These unmeasured factors may contribute to the increased risk observed. Notably, IVF/ICSI pregnancies represent a high-risk group for postpartum hemorrhage, emphasizing the importance of vigilant hemoglobin management during pregnancy and preparedness for blood product storage. If necessary, transferring patients to hospitals with rescue capabilities is advisable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of this study\u003c/h2\u003e \u003cp\u003eWhile this study provides valuable insights, it is essential to acknowledge its limitations. The data are derived from a single-center with a limited sample size. Although propensity score matching adjusts for numerous confounding factors, it only balances observed indicator variables. Additionally, SPSS propensity score matching achieves 1:1 matching between the experimental and control groups based on propensity scores but does not assess the balance of matched data. These limitations may introduce outcome bias. To validate the findings, prospective multi-center, large-sample case-control studies are warranted.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, although IVF/ICSI conception is associated with the incidence of PAS, it does not influence PAS grades. However, it\u0026rsquo;s imperative to look for de novo risk factors affecting PAS severity. While IVF/ICSI pregnancies adds to the risk of postpartum bleeding and blood transfusion, they do not increase hysterectomy rates or adverse neonatal outcomes. Clinicians should consider patients\u0026rsquo; expectations, medical history, local delivery management, and assistance capabilities when assessing IVF/ICSI pregnancy prognosis\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor Contributions: conceptualization, Miao Hu,\u0026nbsp;Lili Du,\u0026nbsp;Shuang Zhang and Dunjin Chen; methodology, Miao Hu and Lizi Zhang; software and analysis, Miao Hu ,Shuang Zhang, Lili Du and Dunjin Chen; Validation, Miao Hu, Lin Lin and Lizi Zhang; resources, Lili Du,Shuang Zhang and Dunjin Chen, data curation,\u0026nbsp;Yuliang Zhang,\u0026nbsp;Shifeng Gu, Zhongjia Gu, JingYing Liang, Siying Lai,\u0026nbsp;Yu Liu,\u0026nbsp;Minshan Huang, Yuanyuan Huang, Qingqing Huang,Shijun Luo.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFounding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNational Key R\u0026amp;D Program (2022YFC2704501, 2022YFC2704503)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study adheres to the principles outlined in the World Medical Association Declaration of Helsinki and received approval from the Ethics Committee of the Third Affiliated Hospital of Guangzhou Medical University (approval number: 20221106).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eAll participants provided informed consent during their hospitalization, granting permission for their clinical data to be used in research while safeguarding their privacy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e Data supporting the study results can be provided by the request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e None.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCAL\u0026Igrave;, G., GIAMBANCO, L., PUCCIO, G. \u0026amp; FORLANI, F. (2013), \u0026quot;Morbidly adherent placenta: evaluation of ultrasound diagnostic criteria and \u0026nbsp;differentiation of placenta accreta from percreta\u0026quot;, Ultrasound Obstet Gynecol, Vol. 41 No. 4, pp. 406-12.\u003c/li\u003e\n \u003cli\u003eFITZPATRICK, K. E., SELLERS, S., SPARK, P., KURINCZUK, J. J., BROCKLEHURST, P. \u0026amp; KNIGHT, M. (2012), \u0026quot;Incidence and risk factors for placenta accreta/increta/percreta in the UK: a \u0026nbsp; national case-control study\u0026quot;, PLoS One, Vol. 7 No. 12, pp. e52893.\u003c/li\u003e\n \u003cli\u003eFONSECA, A. \u0026amp; AYRES, D. C. D. (2021), \u0026quot;Maternal morbidity and mortality due to placenta accreta spectrum disorders\u0026quot;, Best Pract Res Clin Obstet Gynaecol, Vol. 7284-91.\u003c/li\u003e\n \u003cli\u003eHANEVIK, H. I. \u0026amp; HESSEN, D. O. (2022), \u0026quot;IVF and human evolution\u0026quot;, Hum Reprod Update, Vol. 28 No. 4, pp. 457-479.\u003c/li\u003e\n \u003cli\u003eHOU, W., SHI, G., MA, Y., LIU, Y., LU, M., FAN, X. \u0026amp; SUN, Y. (2021), \u0026quot;Impact of preimplantation genetic testing on obstetric and neonatal outcomes: a \u0026nbsp;systematic review and meta-analysis\u0026quot;, Fertil Steril, Vol. 116 No. 4, pp. 990-1000.\u003c/li\u003e\n \u003cli\u003eJAUNIAUX, E. \u0026amp; AYRES-DE-CAMPOS, D. (2018), \u0026quot;FIGO consensus guidelines on placenta accreta spectrum disorders: Introduction\u0026quot;, Int J Gynaecol Obstet, Vol. 140 No. 3, pp. 261-264.\u003c/li\u003e\n \u003cli\u003eJAUNIAUX, E. \u0026amp; BHIDE, A. (2017), \u0026quot;Prenatal ultrasound diagnosis and outcome of placenta previa accreta after \u0026nbsp; cesarean delivery: a systematic review and meta-analysis\u0026quot;, Am J Obstet Gynecol, Vol. 217 No. 1, pp. 27-36.\u003c/li\u003e\n \u003cli\u003eJAUNIAUX, E., AYRES-DE-CAMPOS, D., LANGHOFF-ROOS, J., FOX, K. A. \u0026amp; COLLINS, S. (2019), \u0026quot;FIGO classification for the clinical diagnosis of placenta accreta spectrum \u0026nbsp; disorders\u0026quot;, Int J Gynaecol Obstet, Vol. 146 No. 1, pp. 20-24.\u003c/li\u003e\n \u003cli\u003eJAUNIAUX, E., BUNCE, C., GR\u0026Oslash;NBECK, L. \u0026amp; LANGHOFF-ROOS, J. (2019), \u0026quot;Prevalence and main outcomes of placenta accreta spectrum: a systematic review \u0026nbsp;and meta-analysis\u0026quot;, Am J Obstet Gynecol, Vol. 221 No. 3, pp. 208-218.\u003c/li\u003e\n \u003cli\u003eJAUNIAUX, E., CHANTRAINE, F., SILVER, R. M. \u0026amp; LANGHOFF-ROOS, J. (2018), \u0026quot;FIGO consensus guidelines on placenta accreta spectrum disorders: Epidemiology\u0026quot;, Int J Gynaecol Obstet, Vol. 140 No. 3, pp. 265-273.\u003c/li\u003e\n \u003cli\u003eKAYEM, G., SECO, A., VENDITTELLI, F., CRENN, H. C., DUPONT, C., BRANGER, B., HUISSOUD, C., FRESSON, J., WINER, N., LANGER, B., ROZENBERG, P., MOREL, O., BONNET, M. P., PERROTIN, F., AZRIA, E., CARBILLON, L., CHIESA, C., RAYNAL, P., RUDIGOZ, R. C., PATRIER, S., BEUCHER, G., DREYFUS, M., SENTILHES, L. \u0026amp; DENEUX-THARAUX, C. (2024), \u0026quot;Risk factors for placenta accreta spectrum disorders in women with any prior \u0026nbsp; cesarean and a placenta previa or low lying: a prospective population-based \u0026nbsp;study\u0026quot;, Sci Rep, Vol. 14 No. 1, pp. 6564.\u003c/li\u003e\n \u003cli\u003eKYOZUKA, H., YAMAGUCHI, A., SUZUKI, D., FUJIMORI, K., HOSOYA, M., YASUMURA, S., YOKOYAMA, T., SATO, A. \u0026amp; HASHIMOTO, K. (2019), \u0026quot;Risk factors for placenta accreta spectrum: findings from the Japan environment \u0026nbsp;and Children\u0026apos;s study\u0026quot;, BMC Pregnancy Childbirth, Vol. 19 No. 1, pp. 447.\u003c/li\u003e\n \u003cli\u003eLI, R., TANG, X., QIU, X., WANG, W. \u0026amp; WANG, Q. (2023), \u0026quot;Associations of characteristics of previous induced abortion with different \u0026nbsp;grades of current placenta accreta spectrum disorders\u0026quot;, J Matern Fetal Neonatal Med, Vol. 36 No. 2, pp. 2253349.\u003c/li\u003e\n \u003cli\u003eMARCELLIN, L., DELORME, P., BONNET, M. P., GRANGE, G., KAYEM, G., TSATSARIS, V. \u0026amp; GOFFINET, F. (2018), \u0026quot;Placenta percreta is associated with more frequent severe maternal morbidity than \u0026nbsp;placenta accreta\u0026quot;, Am J Obstet Gynecol, Vol. 219 No. 2, pp. 193.e1-193.e9.\u003c/li\u003e\n \u003cli\u003eMATSUZAKI, S., NAGASE, Y., TAKIUCHI, T., KAKIGANO, A., MIMURA, K., LEE, M., MATSUZAKI, S., UEDA, Y., TOMIMATSU, T., ENDO, M. \u0026amp; KIMURA, T. (2021), \u0026quot;Antenatal diagnosis of placenta accreta spectrum after in vitro \u0026nbsp;fertilization-embryo transfer: a systematic review and meta-analysis\u0026quot;, Sci Rep, Vol. 11 No. 1, pp. 9205.\u003c/li\u003e\n \u003cli\u003eNYFL\u0026Oslash;T, L. T., SANDVEN, I., OLDEREID, N. B., STRAY-PEDERSEN, B. \u0026amp; VANGEN, S. (2017), \u0026quot;Assisted reproductive technology and severe postpartum haemorrhage: a \u0026nbsp;case-control study\u0026quot;, BJOG, Vol. 124 No. 8, pp. 1198-1205.\u003c/li\u003e\n \u003cli\u003eQIAO, J., WANG, Y., LI, X., JIANG, F., ZHANG, Y., MA, J., SONG, Y., MA, J., FU, W., PANG, R., ZHU, Z., ZHANG, J., QIAN, X., WANG, L., WU, J., CHANG, H. M., LEUNG, P., MAO, M., MA, D., GUO, Y., QIU, J., LIU, L., WANG, H., NORMAN, R. J., LAWN, J., BLACK, R. E., RONSMANS, C., PATTON, G., ZHU, J., SONG, L. \u0026amp; HESKETH, T. (2021), \u0026quot;A Lancet Commission on 70 years of women\u0026apos;s reproductive, maternal, newborn, \u0026nbsp;child, and adolescent health in China\u0026quot;, Lancet, Vol. 397 No. 10293, pp. 2497-2536.\u003c/li\u003e\n \u003cli\u003eRIVEROS-PEREZ, E. \u0026amp; WOOD, C. (2018), \u0026quot;Retrospective analysis of obstetric and anesthetic management of patients with \u0026nbsp;placenta accreta spectrum disorders\u0026quot;, Int J Gynaecol Obstet, Vol. 140 No. 3, pp. 370-374.\u003c/li\u003e\n \u003cli\u003eSUGAI, S., YAMAWAKI, K., SEKIZUKA, T., HAINO, K., YOSHIHARA, K. \u0026amp; NISHIJIMA, K. (2023), \u0026quot;Pathologically diagnosed placenta accreta spectrum without placenta previa: a \u0026nbsp;systematic review and meta-analysis\u0026quot;, Am J Obstet Gynecol MFM, Vol. 5 No. 8, pp. 101027.\u003c/li\u003e\n \u003cli\u003eYIN, S., ZHOU, Y., ZHAO, C., YANG, J., YUAN, P., ZHAO, Y., QI, H. \u0026amp; WEI, Y. (2024), \u0026quot;Association of Paternal Age Alone and Combined with Maternal Age with Perinatal \u0026nbsp;Outcomes: A Prospective Multicenter Cohort Study in China\u0026quot;, J Epidemiol Glob Health, Vol. 14 No. 1, pp. 120-130.\u003c/li\u003e\n \u003cli\u003eZHANG, H., DOU, R., YANG, H., ZHAO, X., CHEN, D., DING, Y., DING, H., CUI, S., ZHANG, W., XIN, H., GU, W., HU, Y., DING, G., QI, H., FAN, L., MA, Y., LU, J., YANG, Y., LIN, L., LUO, X., ZHANG, X. \u0026amp; FAN, S. (2019), \u0026quot;Maternal and neonatal outcomes of placenta increta and percreta from a \u0026nbsp;multicenter study in China\u0026quot;, J Matern Fetal Neonatal Med, Vol. 32 No. 16, pp. 2622-2627.\u003c/li\u003e\n \u003cli\u003eZHAO, J., LI, Q., LIAO, E., SHI, H., LUO, X., ZHANG, L., QI, H., ZHANG, H. \u0026amp; LI, J. (2024), \u0026quot;Incidence, risk factors and maternal outcomes of unsuspected placenta accreta \u0026nbsp;spectrum disorders: a retrospective cohort study\u0026quot;, BMC Pregnancy Childbirth, Vol. 24 No. 1, pp. 76.\u003c/li\u003e\n \u003cli\u003eZHU, L. \u0026amp; XIE, L. (2019), \u0026quot;Value of ultrasound scoring system for assessing risk of pernicious placenta \u0026nbsp; previa with accreta spectrum disorders and poor pregnancy outcomes\u0026quot;, J Med Ultrason (2001), Vol. 46 No. 4, pp. 481-487.\u003c/li\u003e\n \u003cli\u003eHuang Lihong \u0026amp; Chen Feng(2019), \u0026ldquo;The propensity score method and it`s application\u0026rdquo;,Chinese Journal of Preventive Medicine,No. 7, pp. 752-756.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"IVF/ICSI, grades of placenta, outcomes, postpartum hemorrhage, transfusion","lastPublishedDoi":"10.21203/rs.3.rs-4983277/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4983277/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo investigate the impact of IVF/ICSI on grades of placenta accreta spectrum disorders and pregnancy outcomes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePlacenta accreta spectrum disorders patients who underwent cesarean section at a single clinical center from January 2018 to March 2023 were retrospectively included in this study. Baseline characteristics and outcomes were compared between the IVF/ICSI group and the spontaneous conception group. Binary logistic regression was used to explore the risk factors associated with adverse outcomes related to IVF/ICSI. A 1:1 ratio propensity score matching (PSM) was conducted to minimize selection bias between the two groups. Data analysis was performed using SPSS (version 25.0) software.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eNo increase in the incidence of grades placenta was detected for IVF/ICSI group, and the difference is not statistically significant (P\u0026thinsp;=\u0026thinsp;0.290). PAS grading is not associated with IVF/ICSI (OR\u0026thinsp;=\u0026thinsp;0.76, 95%CI: 0.45\u0026thinsp;~\u0026thinsp;1.27, P\u0026thinsp;=\u0026thinsp;0.290). In contrast, a significant risk factor for postpartum hemorrhage (OR\u0026thinsp;=\u0026thinsp;9.20, 95%CI: 2.68\u0026thinsp;~\u0026thinsp;9.22, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and red cells transfusion\u0026thinsp;\u0026ge;\u0026thinsp;4U (OR\u0026thinsp;=\u0026thinsp;3.71,95%CI:1.21\u0026thinsp;~\u0026thinsp;11.33, P\u0026thinsp;=\u0026thinsp;0.021) was observed in IVF/ICSI group. No additional adverse pregnancy outcomes arose as a result of IVF/ICSI.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIt is necessary to further investigation into the potential risk factors that might impact PAS grading. It has been shown that IVF/ICSI treatment is associated with a higher risk of postpartum hemorrhage and blood transfusion requirements. Therefore, in order to provide patients the best chance of recovery, professionals must carefully evaluate the patient's health as well as the available treatment options.\u003c/p\u003e","manuscriptTitle":"Impact of IVF/ICSI on Grades of Placenta Accreta Spectrum Disorders and Pregnancy Outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-17 13:48:45","doi":"10.21203/rs.3.rs-4983277/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-13T14:25:02+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"83983935930945596246437839913635245050","date":"2024-11-30T20:29:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315318134728669865482199829234729518693","date":"2024-11-28T20:17:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-18T17:22:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155351813770081834965724596254484241261","date":"2024-10-17T22:00:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333500296576547022574671909830981648754","date":"2024-10-17T20:59:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"236744448441058553656815005903425695730","date":"2024-10-13T07:06:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-11T19:29:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-28T08:09:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-28T08:09:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Reproductive Health","date":"2024-08-27T09:24:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"reproductive-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"reph","sideBox":"Learn more about [Reproductive Health](http://reproductive-health-journal.biomedcentral.com)","snPcode":"12978","submissionUrl":"https://submission.nature.com/new-submission/12978/3","title":"Reproductive Health","twitterHandle":"@Reprod_Health","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"24f86d8c-546d-457b-ba9e-07a81ef47455","owner":[],"postedDate":"October 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-26T16:09:15+00:00","versionOfRecord":{"articleIdentity":"rs-4983277","link":"https://doi.org/10.1186/s12978-025-02031-z","journal":{"identity":"reproductive-health","isVorOnly":false,"title":"Reproductive Health"},"publishedOn":"2025-05-19 15:57:51","publishedOnDateReadable":"May 19th, 2025"},"versionCreatedAt":"2024-10-17 13:48:45","video":"","vorDoi":"10.1186/s12978-025-02031-z","vorDoiUrl":"https://doi.org/10.1186/s12978-025-02031-z","workflowStages":[]},"version":"v1","identity":"rs-4983277","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4983277","identity":"rs-4983277","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}