Correlation Between Chronic Endometritis and Early Pregnancy Loss: a prospective cohort study

Correlation Between Chronic Endometritis and Early Pregnancy Loss: a prospective cohort study | 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 Correlation Between Chronic Endometritis and Early Pregnancy Loss: a prospective cohort study Lijie Wang, Lu Jiang, Fei Yang, Fang Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8780845/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Early Pregnancy Loss (EPL) refers to embryonic loss occurring before 10 weeks of gestation, including biochemical pregnancy. Chronic Endometritis is a chronic inflammation of the endometrial lining. The association between chronic endometritis and early pregnancy loss remains controversial, with inconsistent findings and insufficient evidence from existing studies. Therefore, this study was conducted to address this research gap. Methods This prospective cohort study enrolled 1,059 patients with definitive pregnancy outcomes completed the study from December 2020 to December 2024. Using independent samples t-test, analysis of variance (ANOVA), and chi-square test were used to compare differences between groups, while logistic regression analysis was applied to explore the association between CE and EPL. Results The prevalence of CE among patients with pregnancy loss was 39.8% (431/1,059). The incidence of early pregnancy loss was 10.05% in the non-CE group and 28.07% in the CE group. With the increase in CE severity, the incidence of EPL gradually increased: 15.82% in the mild CE group, 22.58% in the moderate CE group, and 33.94% in the severe CE group, with a statistically significant difference between groups (P < 0.001). Multivariate logistic regression analysis showed that CE was an independent risk factor for EPL. After adjustment, patients with CE had a 37% increased risk of EPL (odds ratio OR = 1.37, 95% CI: 1.14–1.67, P = 0.003). Subgroup analysis revealed that the association between CE and EPL was more pronounced in patients aged ≥ 30 years and those with ≥ 3 previous pregnancy losses. Conclusion Chronic endometritis has a high prevalence among patients with pregnancy loss, and its severity is an independent risk factor for subsequent early pregnancy loss. The impact of CE on EPL is more significant in subgroups of older patients and those with multiple previous pregnancy losses. Clinically, screening for CE and assessment of its severity should be performed in patients with pregnancy loss, especially in high-risk subgroups, to optimize pregnancy outcomes. Trial registration This study was registered in the Chinese Clinical Trial Registry with the registration number of ChiCTR2000039414 (27/10/2020) Pregnancy loss Chronic endometritis Pregnancy outcome Logistic regression Figures Figure 1 Background Pregnancy loss (PL) is clinically defined as the spontaneous cessation of fetal development before 24 weeks of gestation. Early pregnancy loss (EPL) refers to embryonic loss occurring before 10 weeks of gestation, including biochemical pregnancy[ 1 ]. Approximately 25% of clinically recognized pregnancies result in Early pregnancy loss, making it the most common complication of pregnancy. The majority of EPL are attributed to random numerical chromosomal abnormalities[ 2 , 3 ]. Other risk factors include a history of early pregnancy loss, genital tract pathogen infections, advanced age, extremes in body mass index (BMI), smoking, alcohol consumption, physical trauma, psychological stress, exposure to air pollution, and pesticide exposure, among others[ 4 , 5 ]. Chronic endometritis (CE) is defined as chronic inflammation of the endometrial lining. Patients with CE are often asymptomatic; however, they may present with clinical manifestations such as pelvic pain, dyspareunia, abnormal vaginal bleeding, or vaginal discharge[ 6 ]. Studies report a prevalence of CE among RPL patients ranging from 13% to 56%[ 7 – 9 ]. The gold standard for diagnosing CE is the histological identification of plasma cells in the endometrial stroma via CD138 immunohistochemical assessment [ 10 ]. The pathophysiology of CE may have a relationship with the endometrial microbiome is widely accepted[ 11 ], as evidenced by the effectiveness of antibiotic treatment in reducing stromal infiltration[ 12 , 13 ]. It is believed that plasma cell infiltration of the endometrium may affect endometrial receptivity and result in RPL[ 14 , 15 ]. Several studies have showed the impact of CE on pregnancy outcomes in women with RPL[ 6 ]. CE patients suffer from repeated planting failure, abortion, premature birth, declined implantation rate of embryos in vitro fertilization (IVF) and other adverse pregnancy outcomes[ 16 , 17 ] However, whether chronic endometritis is associated with early pregnancy loss remains controversial, as existing research findings are inconsistent and the evidence is insufficient to clarify the relationship[ 18 ]. Therefore, this study aims to explore the impact of chronic endometritis on early pregnancy loss and their potential association using a prospective cohort study. Methods Study design and population This prospective cohort study enrolled 3,090 women with a history of at least one pregnancy loss who attended the Reproductive Center of the Second Hospital of Lanzhou University (Lanzhou, China) between December 2020 and December 2024. Ethical approval was granted (Ethics Approval No. 2019A-231). Detailed information regarding the cohort design has been described in our previous publication[ 19 ]. PL was defined as pregnancy losses prior to 24 weeks of gestation with the same partner. We collected comprehensive patient data, including obstetric history, age, educational background, ethnicity, Ethnicity, Menstrual Cycle, age at menarche, age at first pregnancy, body mass index (BMI), the number and types of previous pregnancy losses, History of Pelvic Surgery, Type of Pregnancy Loss and the final outcome of the current pregnancy. In addition, Clinical testing indicators included: serum immune indicators (complement C3, complement C4, immunoglobulin A, immunoglobulin M), inflammatory factor indicators (interleukin-6, interleukin-10, interferon-γ, tumor necrosis factor-α), coagulation function indicators, glucose and lipid metabolism indicators, blood routine, liver function indicators, renal function indicators, uterine ultrasound findings, and endometrial immunohistochemical indicators. Patient inclusion criteria were as follows: (1)A history of at least two pregnancy losses before 24 weeks of gestation (including biochemical pregnancy), with the diagnosis of pregnancy loss based on the guidelines of the European Society of Human Reproduction and Embryology (ESHRE)[ 1 , 5 ]; (2)Age between 18 and 42 years;(3) Patients who underwent hysteroscopy and endometrial immunohistochemistry;(4)3–7 days after menstruation cessation;(5)No oral antibiotics or hormonal medications within 3 months prior to enrollment;(6)No vaginal medications within 3 months prior to hysteroscopy. Exclusion Criteria: (1) Patients lost to follow-up with no available pregnancy outcome by December 2024;(2) Subsequent pregnancy outcomes including ectopic pregnancy, hydatidiform mole, induced abortion due to fetal malformation, or pregnancy duration of less than 10 weeks by the follow-up cutoff date;(3) Patients with subsequent pregnancies was twin pregnancies. Measurements of serum indicators and immunohistochemical staining of the endometrium Serum Indicators: Venous blood (5 ml) was collected from the cubital vein of participants in a fasting state using standard dry blood collection tubes, and all samples were sent to the Clinical Laboratory of the Second Hospital of Lanzhou University for testing within 4 hours. Endometrial Sample IHC: Endometrial tissue was collected via curettage with a curette during hysteroscopy (3–5 days after menstruation cessation) for all patients. The tissue was rinsed with normal saline to remove residual bloodstains on the surface, then placed in a cryopreservation tube, fixed with 4% paraformaldehyde, embedded in paraffin, and sent to the Department of Pathology of the Second Hospital of Lanzhou University. Subsequently, we followed up on the results of hematoxylin-eosin (HE) staining and CD138 immunohistochemical (IHC) staining for histopathological examination of endometrial specimens. All staining procedures and result evaluations were performed by the same group of senior physicians with professional titles. Pregnancy outcomes The primary outcome metrics analyzed in this study included early pregnancy loss (EPL), ongoing pregnancy (OP), and live birth in the subsequent pregnancies of patients with pregnancy loss (PL). EPL was defined as pregnancy loss occurring at a gestational age of less than 10 weeks, including biochemical pregnancy. OP was defined as a viable pregnancy lasting past 10 weeks of gestation. A live birth was defined as a pregnancy that reached or exceeded 28 weeks of gestation. All patients enrolled in the study were followed up every six months via the electronic medical record system or telephone to monitor their pregnancy status, with the follow-up of this study concluding in December 2025. Statistical analysis Data were presented as the mean ± standard deviation (SD) for continuous variables and as counts and percentages for categorical variables. Differences between two groups were assessed using the independent samples t-test, while those among three or more groups were analyzed via one-way analysis of variance (ANOVA). For categorical variables, the two-sided Pearson’s chi-square test or Fisher’s exact test was used as appropriate. Pearson correlation analysis was also conducted where applicable. The Bonferroni correction was applied for multiple group comparisons. Variables with a P value < 0.1 in univariate analyses were included in multivariate logistic regression models to calculate odds ratios (ORs) for the associations between risk factors and infertility, non-live birth, and subsequent pregnancy loss. A two-tailed P value < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS for Windows, Version 27.0 (SPSS Inc., Chicago, IL, USA). Results Baseline characteristics A total of 1059 patients with pregnancy loss and definitive pregnancy outcomes were finally enrolled in this study, with the detailed enrollment flow shown in Fig. 1. The baseline characteristics of the participants summarized in Table 1 . Among them, 431 patients were diagnosed with chronic endometritis and 628 with non-chronic endometritis, yielding a prevalence of 39.8% (431/1059) of CE in the pregnancy loss (PL) population. The mean age of the participants was 30.91 ± 4.49 years. No statistically significant differences were observed between the CE and non-CE groups in terms of age (P = 0.729), body mass index (BMI) (P = 0.284), educational background (P = 0.297), ethnicity (P = 0.643), age at menarche (P = 0.731), menstrual cycle regularity (P = 0.324), history of induced abortion (P = 0.513), history of live birth (P = 0.255), total number of pregnancies (P = 0.848), total number of pregnancy losses (P = 0.709), history of pelvic surgery, and type of pregnancy loss (P = 0.588). Table 1 Baseline Characteristics of CE Patients Before Pregnancy Variables Total Patients Non-CE CE P Sample Size 1059 628 431 P-value Age (years) 30.91 ± 4.49 30.82 ± 4.43 31.00 ± 4.54 0.729 BMI (kg/m 2 ) 22.71 ± 2.23 22.84 ± 3.33 22.58 ± 3.13 0.284 Ethnicity 0.643 Han (n, %) 964 (91.06%) 578 (90.56%) 382 (90.62%) Hui (n, %) 53 (4.96%) 38 (5.96%) 22 (5.30%) Tibetan (n, %) 21 (1.95%) 10 (1.50%) 10 (2.45%) Other Ethnicities (n, %) 15 (1.49%) 12 (1.98%) 7 (1.63%) Age at Menarche (years) 13.46 ± 1.37 13.44 ± 1.38 13.48 ± 1.39 0.731 Menstrual Cycle 0.324 Regular (n, %) 905 (85.45%) 552 (86.48%) 355 (84.25%) Irregular (n, %) 154 (14.55%) 86 (13.52%) 66 (15.75%) History of Live Birth 0.255 None (n, %) 898 (82.05%) 550 (86.2%) 334 (79.45%) Yes (n, %) 197 (17.95%) 88 (13.88%) 87 (20.55%) Total Pregnancy (TPs) 2.81 ± 1.18 2.84 ± 1.11 2.79 ± 1.27 0.848 Pregnancy Losses (PLs) 2.37 ± 0.69 2.35 ± 0.75 2.37 ± 0.82 0.709 History of Pelvic Surgery 0.516 None (n, %) 860 (81.25%) 544 (85.23%) 330 (78.35%) Yes (n, %) 199 (18.75%) 94 (14.77%) 91 (21.65%) Type of Pregnancy Loss 0.588 Primary (n, %) 791 (72.25%) 454 (71.2%) 309 (73.35%) Secondary (n, %) 304 (27.75%) 184 (28.80%) 112 (26.65%) Baseline Characteristics of Different Degrees of CE Before Pregnancy In this study, chronic endometritis (CE) was diagnosed based on positive endometrial CD138 expression, and CE was classified into three severity grades according to the number of CD138-positive cells: mild CE (CD138 (+) ≥ 1/high-power field [HPF]), moderate CE (2/HPF < CD138 (+) < 5/HPF), and severe CE (CD138 (+) ≥ 5/HPF)[ 20 , 21 ]. In Table 2 , we compared with the non-CE group, the CE group had a higher incidence of endometrial micropolyps, elevated immunoglobulin G (IgG), increased homocysteine (Hcy) levels, elevated interleukin-6 (IL-6), Mycoplasma positivity, and increased bilateral uterine artery blood flow resistance, indicating that these factors were associated with an elevated risk of CE, with statistically significant differences (P < 0.05). Additionally, elevated IL-6 and tumor necrosis factor-α (TNF-α) were also correlated with an increased risk of CE, with statistically significant differences (P < 0.05). No statistically significant differences were observed between the CE and non-CE groups in the remaining test indicators, including free triiodothyronine (FT3), free tetraiodothyronine (FT4), thyroid-stimulating hormone (TSH), D-dimer (D-Dimer),, immunoglobulin A (IgA), immunoglobulin M (IgM), complement C3, complement C4, fasting blood glucose, fasting insulin, neutrophils (NE), total cholesterol (CHO), low-density lipoprotein cholesterol (LDL-C), carbohydrate antigen 125 (CA125), 25-hydroxyvitamin D3 (25-OH-D3), urea, creatinine, uric acid, high-sensitivity C-reactive protein, interferon-γ, endometrial thickness, bilateral uterine artery pulsatility index (PI), bilateral uterine artery systolic/diastolic velocity ratio (S/D) (P > 0.05). Table 2 Baseline Characteristics of Different Degrees of CE Before Pregnancy Variable Total Patients Non-CE CE P Mild CE Moderate CE Severe CE CD138(-) CD138(+)≥1/HPF 2<CD138(+)<5/HPF CD138(+)≥5/HPF P-value Sample Size 1059 628 122 162 147 Endometrial Micropolyps 0.024 Absent (n, %) 1004(94.81%) 605(96.27%) 118(96.44%) 148(91.28%) 139(94.63%) Present (n, %) 55(5.19%) 23(3.28%) 4(3.56%) 14(8.72%) 8(5.37%) T3 (uIU /mL) 3.88 ± 1.67 3.95 ± 1.66 3.78 ± 1.54 3.91 ± 1.23 3.81 ± 1.19 0.762 T4 (uIU /mL) 16.66 ± 2.60 16.75 ± 2.75 16.52 ± 3.27 16.32 ± 2.53 16.57 ± 3.12 0.469 TSH (uIU /mL) 3.95 ± 2.95 3.75 ± 1.61 3.57 ± 1.75 3.59 ± 2.13 4.19 ± 3.15 0.154 D-Dimer (mg/L) 0.23 ± 0.21 0.22 ± 0.27 0.24 ± 0.19 0.22 ± 0.17 0.23 ± 0.2 0.546 CA125 21.48 ± 12.45 18.75 ± 12.45 20.39 ± 13.39 22.53 ± 11.38 21.57 ± 10.98 0.357 Complement C3 1.22 ± 0.19 1.23 ± 0.19 1.22 ± 0.18 1.19 ± 0.16 1.23 ± 0.21 0.951 Complement C4 0.35 ± 0.18 0.33 ± 0.12 0.34 ± 0.13 0.38 ± 0.16 0.35 ± 0.21 0.607 Immunoglobulin G 11.96 ± 2.45 10.36 ± 2.21 11.78 ± 2.09 12.36 ± 2.23 12.87 ± 2.90 0.042 Immunoglobulin A 2.39 ± 1.75 2.36 ± 0.96 2.40 ± 1.11 2.56 ± 1.29 2.31 ± 2.10 0.996 Immunoglobulin M 1.51 ± 0.71 1.54 ± 0.59 1.56 ± 0.67 1.48 ± 0.75 1.52 ± 1.12 0.598 Hcy (umol/L) 11.53 ± 4.45 8.59 ± 2.92 10.90 ± 0.38 11.23 ± 2.51 12.58 ± 3.21 0.048 CHO (mmol/L) 4.14 ± 0.78 4.1 ± 0.77 4.13 ± 0.49 4.14 ± 0.72 4.17 ± 0.73 0.484 TG (mmol/L) 1.18 ± 0.59 1.13 ± 0.51 1.14 ± 0.57 1.20 ± 0.78 1.21 ± 0.81 0.616 HDL (mmol/L) 1.34 ± 0.35 1.41 ± 0.36 1.35 ± 0.31 1.30 ± 0.29 1.32 ± 0.32 0.524 LDL (mmol/L) 2.61 ± 0.63 2.59 ± 0.58 2.54 ± 0.75 2.62 ± 0.64 2.64 ± 0.59 0.251 Neutrophil Ratio 0.74 ± 0.18 0.79 ± 0.19 0.76 ± 0.21 0.69 ± 0.14 0.71 ± 0.25 0.645 Platelet Count✖109 234.13 ± 83.27 232.67 ± 91.1 234.21 ± 60.98 234.28 ± 70.54 235.19 ± 81.26 0.789 CRP 2.23 ± 0.63 2.21 ± 0.52 2.24 ± 0.71 2.19 ± 0.58 2.34 ± 0.62 0.553 Urea (mmol/L) 4.36 ± 1.24 4.19 ± 1.18 4.41 ± 1.15 4.45 ± 1.25 4.38 ± 1.29 0.601 Creatinine (µmol/L) 53.03 ± 7.62 52.68 ± 7.40 53.21 ± 7.54 52.79 ± 8.18 53.99 ± 7.33 0.561 Uric Acid (µmol/L) 271.48 ± 57.16 264.81 ± 51.10 265.60 ± 55.64 280.16 ± 60.91 271.88 ± 65.64 0.147 Vaginal pH Value 0.142 Normal (n, %) 909(85.81%) 566(90.16%) 105(86.45%) 137(84.19%) 121(82.46%) Abnormal (n, %) 150(14.19%) 62(9.84%) 17(13.55%) 26(15.81%) 26(17.54%) Mycoplasma 0.032 Negative (n, %) 783(73.94%) 514(81.81%) 97(79.48%) 115(70.84%) 94(63.62%) Positive (n, %) 276(26.06%) 114(18.19%) 25(20.52%) 47(29.16%) 53(36.38%) IL-6(pg/ml) 0.033 Normal (n, %) 785(74.08%) 511(81.36%) 86(78.52%) 114(70.63%) 97(65.81%) Elevated (n, %) 274(25.92%) 117(18.64%) 26(21.48%) 48(29.37%) 50(34.19%) Interferon-γ(pg/ml) 0.528 Normal (n, %) 1027(96.99%) 613(97.62%) 118(96.71%) 157(97.03%) 142(96.59%) Elevated (n, %) 32(3.01%) 15(2.38%) 4(3.29%) 5(2.97%) 5(3.41%) TNF-α(pg/ml) 0.013 Normal (n, %) 970(91.63%) 596(94.86%) 102(91.48%) 146(90.19%) 132(89.98%) Elevated (n, %) 89(8.37%) 32(5.14%) 10(8.52%) 16(9.81%) 15(10.02%) Endometrial Thickness 6.86 ± 1.94 7.02 ± 1.98 7.10 ± 2.26 6.54 ± 1.78 6.79 ± 2.18 0.229 Right_PI 2.16 ± 0.59 2.22 ± 0.52 2.18 ± 0.57 2.07 ± 0.61 2.19 ± 0.68 0.223 Right_RI 0.81 ± 0.07 0.75 ± 0.08 0.79 ± 0.07 0.87 ± 0.09 0.84 ± 0.08 0.042 Right _S/D 5.26 ± 1.85 5.46 ± 2.25 5.19 ± 1.53 5.12 ± 1.65 5.13 ± 1.76 0.213 Left_PI 2.13 ± 0.67 2.14 ± 0.79 2.15 ± 0.52 2.11 ± 0.65 2.13 ± 0.71 0.083 Left_RI 0.81 ± 0.11 0.78 ± 0.08 0.79 ± 0.08 0.82 ± 0.18 0.84 ± 0.14 0.024 Left _S/D 5.32 ± 1.93 5.50 ± 1.93 5.41 ± 1.77 5.24 ± 1.71 5.39 ± 1.82 0.671 Correlation Analysis Between Chronic Endometritis and Differentially Significant Indicators Spearman correlation analysis revealed that chronic endometritis was positively correlated with endometrial micropolyps (P = 0.043, r = 0.145), homocysteine (Hcy) (P = 0.031, r = 0.116), Mycoplasma positivity (P = 0.014, r = 0.210), right uterine artery resistance index (R_RI) (P = 0.040, r = 0.143), and left uterine artery resistance index (L_RI) (P = 0.042, r = 0.134). A positive r value indicates that the risk of CE increases with the elevation of the above indicators. However, no correlation was observed between CE and immunoglobulin G (IgG) (P > 0.05). The detailed results are presented in Table 3. Table 3 Correlation between relevant differential indicators and CE in the study population Endometrial Polyps IgG Hcy Mycoplasma R_RI L_RI IL-6 TNF-α P 0.043 0.165 0.031 0.014 0.040 0.042 0.031 0.024 r 0.145 0.064 0.116 0.210 0.143 0.134 0.157 0.113 Correlation Analysis Between Chronic Endometritis and Early Pregnancy Loss Pregnancy Outcomes Among Different Chronic Endometritis Groups At the end of the follow-up period, among the 1059 enrolled patients, the incidence of early pregnancy loss was 10.05% in the non-chronic endometritis (Non-CE) group. In the chronic endometritis group, 121 patients experienced EPL in subsequent pregnancies, with an incidence rate of 28.07% (121/431). Further analysis revealed that the incidence of EPL showed a significant upward trend with the increasing severity of CE: 15.82% in the mild CE group, 22.58% in the moderate CE group, and 33.94% in the severe CE group. The difference between groups was statistically significant (P < 0.001), and the detailed results are presented in Table 4. Table 4 Pregnancy Outcomes in Patients with CE Variable Total Patients Non-CE CE P -value CD138(-) CD138 ≥ 1/HPF 2<CD138(+)<5/HPF CD138 ≥ 5/HPF Pregnancy Outcome < 0.001 OP 865 (80.41%) 565 (89.95%) 103 (84.18%) 109 (67.42%) 98 (60.06%) EPL 194 (19.59%) 63 (10.05%) 19 (15.82%) 53 (32.58%) 49 (39.94%) The results of correlation analysis between chronic endometritis and early pregnancy loss The logistic regression analysis showed in Table 5 that the presence of CE at baseline significantly increased the risk of EPL in subsequent pregnancies, and this association remained stable across different adjusted models: In the unadjusted model, patients with CD138 positivity had a 47% increased risk of EPL (OR = 1.47; 95% CI: 1.10–1.75; P = 0.001). In Model I (adjusted for age and body mass index [BMI]), the above correlation remained statistically significant (OR = 1.38; 95% CI: 1.21–1.49; P = 0.003). In the fully adjusted Model II (incorporating other confounding variables), patients with CE still had a 37% increased risk of EPL (OR = 1.37; 95% CI: 1.14–1.67; P = 0.003). The aforementioned association was also significant among subgroups with different degrees of CD138 positivity. Using CD138 ≥ 1/HPF (mild CE) as the reference group: In the unadjusted model, the risk of EPL increased significantly from moderate CE (2<CD138(+)<5/HPF) to severe CE (CD138 ≥ 5/HPF) (moderate CE: OR = 1.59, 95% CI: 1.19–2.81; severe CE: OR = 3.26, 95% CI: 1.26–5.79; P = 0.004). In Model I (adjusted for age and BMI), the risk of EPL remained significantly elevated in patients with moderate to severe CE (moderate CE: OR = 1.68, 95% CI: 1.41–2.84; severe CE: OR = 3.32, 95% CI: 1.12–4.87; P = 0.003). With further adjustment for age, BMI, and other confounding factors in Model II, the risk of EPL continued to increase (moderate CE: OR = 1.81, 95% CI: 1.46–3.88; severe CE: OR = 4.55, 95% CI: 1.91–6.49; P = 0.002). Table 5 Logistic Regression Analysis of the Risk Between CE and EPL Variable Non-adjusted Adjust I Adjust II CD138(+) 1.47 (1.10, 1.75) 0.001 1.38 (1.21, 1.49) 0.003 1.37 (1.14, 1.67) 0.003 CD138(+)分级 CD138(+) ≥ 1/HPF Reference Reference Reference 2<CD138(+)<5/HPF 1.59 (1.19, 2.81) 0.018 1.68 (1.41, 2.84) 0.0201 1.81 (1.46, 3.88) 0.0251 CD138(+) ≥ 5/HPF 3.26 (1.29, 5.79) 0.004 3.32 (1.12, 4.87) 0.003 4.55 (1.91, 6.49) 0.002 Adjust I: Adjusted for age and BMI Adjust II: Adjusted for age, BMI, and confounding variables (including endometrial polyps, homocysteine (Hcy), right uterine artery resistance index (R_RI), left uterine artery resistance index (L_RI), Mycoplasma positivity.) Subgroup Analysis and Interaction Test for the Correlation Between Chronic Endometritis and Early Pregnancy Loss We further performed stratified analysis shown in Table 6 to explore the stability of the relationship between CE severity and the subsequent risk of EPL after stratifying by age, BMI, and number of previous pregnancy losses (PLs). After adjusting for the aforementioned confounding factors, the results were as follows: (1) Age subgroup: After adjusting for confounding variables, CE significantly increased the risk of EPL in PL patients aged ≥ 30 years (OR = 1.41; 95% CI: 1.06–1.89; P = 0.005); however, in PL patients under 30 years of age, CE was not associated with an increased risk of subsequent EPL (P > 0.05). (2) BMI subgroup: After adjusting for confounding variables, CE significantly increased the risk of recurrent EPL in PL patients regardless of whether their BMI was < 24 kg/m² (OR = 1.31; 95% CI: 1.09–1.63; P = 0.020) or ≥ 24 kg/m² (OR = 1.43; 95% CI: 1.21–3.95; P = 0.005). (3) PLs subgroup: CE was significantly associated with an increased risk of EPL in RPL patients with either ≤ 2 previous pregnancy losses (OR = 1.28; 95% CI: 1.06–1.83; P = 0.023) or ≥ 3 previous pregnancy losses (OR = 3.08; 95% CI: 1.26–4.78; P = 0.008). Additionally, among patients with ≥ 3 previous pregnancy losses, the number of CD138-positive cells was higher and CE severity was greater, suggesting that the more previous pregnancy losses a patient has, the more attention should be paid to the screening and severity assessment of endometritis. Table 6 Subgroup Analysis and Interaction Test for the Correlation Between CE and Subsequent EPL Subgroup EPL event (%) Crude OR (95%CI) P -value Adjust OR (95%CI) P -value P for interaction Age < 30(year) 0.108 CD138(+) 1.23 (1.01, 1.41) < 0.001 1.27 (0.88, 1.71) 0.091 CD138 (+)-level CD138(+) ≥ 1/HPF 40 (20.36%) Reference Reference 2<CD138(+)<5/HPF 52 (26.58%) 1.37 (0.81, 2.71) 0.104 1.27 (0.36, 4.18) 0.378 CD138(+) ≥ 5/HPF 58 (29.93%) 1.41(1.19, 7.05) < 0.001 1.40 (0.56, 7.86) 0.242 Age ≥ 30 (year) CD138(+) 1.34 (1.23, 1.45) < 0.001 1.41 (1.06, 1.89) 0.005 CD138(+)-level CD138(+) ≥ 1/HPF 49 (25.46%) Reference Reference 2<CD138(+)<5/HPF 55 (28.43%) 3.91 (1.21, 5.13) 0.006 3.15 (1.85, 8.93) 0.019 CD138(+) ≥ 5/HPF 59 (29.74%) 6.18 (5.06, 10.77) < 0.001 7.26 (1.39, 10.39) < 0.001 BMI < 24 kg/m 2 0.144 CD138(+) 1.29 (1.51, 1.78) < 0.001 1.31 (1.09, 1.63) 0.020 CD138(+)-level CD138(+) ≥ 1/HPF 42 (21.62%) Reference Reference 2<CD138(+)<5/HPF 48 (24.96%) 2.28 (1.43, 6.06) 0.004 5.43 (0.59, 10.56) 0.088 CD138(+) ≥ 5/HPF 58 (29.73%) 7.41 (5.38, 19.62) < 0.001 8.52 (1.42, 17.56) 0.027 BMI ≥ 24 kg/m 2 CD138(+) 1.22 (1.09, 1.97) < 0.001 1.43 (1.21, 3.95) 0.005 CD138(+)-level CD138(+) ≥ 1/HPF 42 (21.84%) Reference Reference 2<CD138(+)<5/HPF 56 (28.73%) 1.48 (0.65, 3.88) 0.287 3.46 (0.43, 12.58) 0.356 CD138(+) ≥ 5/HPF 65 (33.41%) 5.78 (1.85, 14.49) 0.003 8.61 (1.64, 14.89) 0.011 PLs ≤ 2 0.349 CD138(+) 1.34 (1.15, 1.59) < 0.001 1.28 (1.06, 1.83) 0.023 CD138(+)-level CD138(+) ≥ 1/HPF 44 (22.51%) Reference Reference 2<CD138(+)<5/HPF 49 (25.22%) 1.62 (0.81, 3.19) 0.087 1.79 (0.76, 9.41) 0.071 CD138(+) ≥ 5/HPF 55 (28.40%) 4.79 (2.41, 11.89) 0.002 4.46 (1.78, 10.66) 0.003 PLs ≥ 3 CD138(+) 2.66 (1.35, 3.81) < 0.001 3.08 (1.26, 4.78) 0.003 CD138(+)-level CD138(+) ≥ 1/HPF 48 (24.47%) Reference Reference 2<CD138(+)<5/HPF 55 (28.43%) 2.30 (1.18, 7.88) 0.019 7 CD138(+) ≥ 5/HPF 67 (34.49%) 8.27 (3.15, 14.78) < 0.001 8.79 (1.13, 17.61) 0.004 Discussion The results of this study demonstrated that chronic endometritis (CE) was significantly associated with an increased risk of EPL in patients with pregnancy loss. Meanwhile, endometrial micropolyps, elevated Hcy levels, increased bilateral uterine artery blood flow resistance, vaginal Mycoplasma positivity, as well as elevated levels of IL-6 and TNF-α, were all closely correlated with the severity of CE. Additionally, linear regression analysis revealed a non-linear association between CE and the subsequent risk of EPL, with a higher severity of CE correlating with an increased risk of subsequent EPL. These findings hold important clinical significance and provide a reliable basis for the clinical management of PL patients and further in-depth research in related fields. Chronic endometritis is characterized by insidious and non-specific clinical symptoms, often overlooked by clinicians[ 22 ]. However, in recent years, its hazards to women's reproductive health have become increasingly prominent. It has emerged as a crucial predisposing factor for unexplained infertility, recurrent implantation failure, and recurrent miscarriage, significantly impairing the pregnancy outcomes of assisted reproductive technology[ 9 , 23 , 24 ]. In the endometrial tissue of patients with CE, the expression of the pro-inflammatory cytokine interleukin-17 is increased, while the expression of anti-inflammatory mediators such as IL-10 is decreased[ 25 ]. Meanwhile, a large number of B cells infiltrate and differentiate into plasma cells, which disrupts the dynamic balance between pro-inflammatory and anti-inflammatory cytokines secreted by immune cells in the endometrium, leading to abnormal immune cell infiltration and imbalance in the inflammatory cytokine network[ 26 , 27 ]. These pathological changes result in reduced endometrial receptivity and abnormal decidualization, thereby impairing embryo implantation and pregnancy maintenance[ 28 , 29 ]. Additionally, the immunoglobulins secreted by plasma cells may exert embryotoxicity, further increasing the risk of EPL[ 22 , 30 ]. The pulsatility index PI and RI of the uterine artery are of great significance for maintaining the normal function of the endometrium, as well as for embryo implantation and development[ 31 , 32 ]. The core mechanism by which CE induces abnormal uterine artery blood flow lies in inflammation-mediated vascular microenvironment disorders: persistent inflammatory infiltration disrupts the dynamic balance of local inflammatory factors in the endometrium, thereby triggering tissue edema, vasospasm, and vascular endothelial damage, ultimately leading to increased uterine artery blood flow resistance. This is maybe cause EPL [ 33 , 34 ]. Chronic endometritis reduced endometrial receptivity and exacerbate the progression of invasive lesions in uterine blood vessels. Study results demonstrate that women with a history of untreated CE exhibit increased vascular resistance in the placental bed; furthermore, the more significant the abnormality of the blood flow velocity curve at this stage, the more severe the subsequent progression of preeclampsia will be[ 35 , 36 ]. Our study found that vaginal Mycoplasma positivity is associated with chronic endometritis and EPL. The mechanisms by which vaginal microecological imbalance drives the occurrence and development of CE related EPL are multifaceted[ 37 – 39 ]. The direct damaging effect of pathogenic bacteria—after colonizing the endometrium, pathogenic bacteria such as Escherichia coli and Streptococcus can form biofilms to evade immune clearance, leading to recurrent and persistent inflammation[ 40 ]. The signaling pathway activation by dysregulated flora—the imbalanced flora triggers the NF-κB signaling pathway via TLR, prompting the massive release of pro-inflammatory cytokines such as IL-1β and IL-6. This further induces endometrial stromal edema and plasma cell infiltration, which are also the core pathological features of CE[ 41 , 42 ]. Finally, the downstream interfering effect of inflammatory factors further disrupted the expression of embryo implantation-related genes such as HOXA10 and integrin αvβ3, impair endometrial receptivity, and ultimately exacerbate reproductive function damage[ 43 , 44 ]. In the subgroup analysis of the correlation between CE and EPL, age, BMI, and the number of previous pregnancy losses are all high-risk factors for EPL. A high BMI may increase the risk of CE by establishing a chronic inflammatory microenvironment and disrupting endocrine-immune balance[ 45 , 46 ]. This association is particularly prominent in special populations with comorbid adenomyosis or recurrent reproductive failure[ 47 ]. For women with a high BMI and advanced age, especially those with fertility needs, reasonable weight management may help reduce the risk of endometrial inflammation and EPL outcomes. Conclusion In summary, CE is highly prevalent in PL patients, and its severity is an independent risk factor for subsequent EPL. The association between CE and EPL varies across different subgroups, with more significant effects in older patients and those with multiple previous pregnancy losses. These findings emphasize the importance of screening for CE and evaluating its severity in the clinical management of PL patients, particularly in high-risk subgroups, which may provide valuable insights for optimizing pregnancy outcomes. Declarations The data that support the findings of this study are available from the corresponding author upon reasonable request. Authors’ contributions Lijie Wang and Fang Wang planned and designed the study. Wang Lijie and Lu Jiang collected the data. Fei Yang performed the analysis. Wang Lijie and Fei Yang interpreted the results. Lijie Wang contributed to writing the manuscript. All the authors reviewed and approved the final manuscript. Corresponding author: Fang Wang Funding Supported by Medical Innovation and Development Project of Lanzhou University, Grant No. lzuyxcx-2022-137) The Science Foundation of Lanzhou University Second Hospital (Grant No. YJS-BD-19). Ethics approval and consent to participate Ethics approval and Consent to participate” section- “This study adhered to the principles outlined in the Declaration of Helsinki. Approval was obtained from the Research Ethics Committee of the Second Hospital of Lanzhou University (approval number [NO.2019 A-231]), and written consent was obtained from all participating women. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Cavalcante MB, et al. ESHRE guideline update 2022: New perspectives in the management of couples with recurrent pregnancy loss. Am J Reprod Immunol. 2023;90(2):e13739. Shorter JM, Atrio JM, Schreiber CA. Management of early pregnancy loss, with a focus on patient centered care. Semin Perinatol. 2019;43(2):84–94. Vitez SF, Forman EJ, Williams Z. Preimplantation genetic diagnosis in early pregnancy loss(). Semin Perinatol. 2019;43(2):116–20. Mehra VM, et al. Diagnosis and management of early pregnancy loss. CMAJ. 2024;196(34):E1162–8. Pymar H, et al. Guideline 460: Diagnosis and Management of Intrauterine Early Pregnancy Loss. J Obstet Gynaecol Can. 2025;47(Suppl 1):102914. Alvares FCC, Sousa FTR, Oliveira ECF. Chronic Endometritis and Recurrent Pregnancy Loss: A review of evidence and underlying mechanisms. JBRA Assist Reprod; 2025. Zargar M, et al. Evaluating Chronic Endometritis in Women with Recurrent Implantation Failure and Recurrent Pregnancy Loss by Hysteroscopy and Immunohistochemistry. J Minim Invasive Gynecol. 2020;27(1):116–21. Vitagliano A, et al. Effects of chronic endometritis therapy on in vitro fertilization outcome in women with repeated implantation failure: a systematic review and meta-analysis. Fertil Steril. 2018;110(1):103–e1121. Ticconi C, et al. Chronic endometritis and recurrent reproductive failure: a systematic review and meta-analysis. Front Immunol. 2024;15:1427454. Liu J, et al. Impact of antibiotic treatment for chronic endometritis on pregnancy outcomes in women with reproductive failures (RIF and RPL): A systematic review and meta-analysis. Front Med (Lausanne). 2022;9:980511. Chen Q, et al. The alteration of intrauterine microbiota in chronic endometritis patients based on 16S rRNA sequencing analysis. Ann Clin Microbiol Antimicrob. 2023;22(1):4. Kitaya K, et al. Endometritis: new time, new concepts. Fertil Steril. 2018;110(3):344–50. Puente E, et al. Chronic Endometritis: Old Problem, Novel Insights and Future Challenges. Int J Fertil Steril. 2020;13(4):250–6. Zhang C, et al. Analysis of the risk factors of chronic endometritis in infertile women. BMC Womens Health. 2025;25(1):378. Zeng S, et al. Research update for the immune microenvironment of chronic endometritis. J Reprod Immunol. 2022;152:103637. Vitagliano A et al. Chronic Endometritis in Infertile Women: Impact of Untreated Disease, Plasma Cell Count and Antibiotic Therapy on IVF Outcome-A Systematic Review and Meta-Analysis. Diagnostics (Basel), 2022. 12(9). Cicinelli E, et al. Prevalence of chronic endometritis in repeated unexplained implantation failure and the IVF success rate after antibiotic therapy. Hum Reprod. 2015;30(2):323–30. Pirtea P, et al. Endometrial causes of recurrent pregnancy losses: endometriosis, adenomyosis, and chronic endometritis. Fertil Steril. 2021;115(3):546–60. Yang X, et al. Reproductive factors and subsequent pregnancy outcomes in patients with prior pregnancy loss. BMC Pregnancy Childbirth. 2024;24(1):219. Li Y, et al. The effect of the number of endometrial CD138 + cells on the pregnancy outcomes of infertile patients in the proliferative phase. Front Endocrinol (Lausanne). 2024;15:1437781. Yasuo T, Kitaya K. Challenges in Clinical Diagnosis and Management of Chronic Endometritis. Diagnostics (Basel), 2022. 12(11). Szafarowska M et al. Micropolyps, Plasma Cells, and Pregnancy: Reevaluating Diagnostic and Therapeutic Strategies in Chronic Endometritis. J Clin Med, 2025. 14(18). Darici E, Blockeel C, Mackens S. Should we stop screening for chronic endometritis? Reprod Biomed Online. 2023;46(1):3–5. Espinos JJ, et al. Impact of chronic endometritis in infertility: a SWOT analysis. Reprod Biomed Online. 2021;42(5):939–51. Chen P, et al. Interaction Between Chronic Endometritis Caused Endometrial Microbiota Disorder and Endometrial Immune Environment Change in Recurrent Implantation Failure. Front Immunol. 2021;12:748447. Li Y, et al. Evaluation of peripheral and uterine immune status of chronic endometritis in patients with recurrent reproductive failure. Fertil Steril. 2020;113(1):187–e1961. Marron K, Walsh D, Harrity C. Detailed endometrial immune assessment of both normal and adverse reproductive outcome populations. J Assist Reprod Genet. 2019;36(2):199–210. Holzer I, et al. Is Chronic Endometritis Associated with Tubal Infertility? A Prospective Cohort Study. J Minim Invasive Gynecol. 2021;28(11):1876–81. Saxtorph MH, et al. Assessing endometrial receptivity after recurrent implantation failure: a prospective controlled cohort study. Reprod Biomed Online. 2020;41(6):998–1006. Shi Y, et al. Research trends and hotspots of recurrent spontaneous abortion with immune dysfunction: A bibliometric analysis from 2004 to 2024. Med (Baltim). 2025;104(26):e43059. La Verde M, et al. The association between fetal Doppler and uterine artery blood volume flow in term pregnancies: a pilot study. Ultraschall Med. 2024;45(2):184–9. Browne VA, et al. Uterine artery blood flow, fetal hypoxia and fetal growth. Philos Trans R Soc Lond B Biol Sci. 2015;370(1663):20140068. Koo HS, et al. Resistance of uterine radial artery blood flow was correlated with peripheral blood NK cell fraction and improved with low molecular weight heparin therapy in women with unexplained recurrent pregnancy loss. Am J Reprod Immunol. 2015;73(2):175–84. Jiang H, Bo Z. Application value of ultrasound elastography for screening of early pregnancy cervical insufficiency: a retrospective case-control study. J Matern Fetal Neonatal Med. 2024;37(1):2299111. Makarov OG, et al. Role of uterine blood flow disturbances in the development of late gestosis. Wiad Lek. 2018;71(9):1719–21. Velauthar L, et al. First-trimester uterine artery Doppler and adverse pregnancy outcome: a meta-analysis involving 55,974 women. Ultrasound Obstet Gynecol. 2014;43(5):500–7. Peuranpaa P, et al. Female reproductive tract microbiota and recurrent pregnancy loss: a nested case-control study. Reprod Biomed Online. 2022;45(5):1021–31. Gao X et al. Clinical Relevance of Vaginal and Endometrial Microbiome Investigation in Women with Repeated Implantation Failure and Recurrent Pregnancy Loss. Int J Mol Sci, 2024. 25(1). Yuan X, et al. Vaginal microbiome and recurrent pregnancy loss. Infect Immun. 2025;93(8):e0005325. Ncib K et al. Microbial Diversity and Pathogenic Properties of Microbiota Associated with Aerobic Vaginitis in Women with Recurrent Pregnancy Loss. Diagnostics (Basel), 2022. 12(10). Khan MZ et al. An Overview of Bioactive Compounds' Role in Modulating the Nrf2/Keap1/NF-kappaB Pathway to Alleviate Lipopolysaccharide-Induced Endometritis. Int J Mol Sci, 2024. 25(19). Yan X, Jiao J, Wang X. Inflammatory mechanisms and therapeutic advances in chronic endometritis. Front Immunol. 2025;16:1616217. Zhang H, et al. Chronic endometritis and the endometrial microbiota: implications for reproductive success in patients with recurrent implantation failure. Ann Clin Microbiol Antimicrob. 2024;23(1):49. Bourdiec A, et al. Regulation of inflammatory and angiogenesis mediators in a functional model of decidualized endometrial stromal cells. Reprod Biomed Online. 2016;32(1):85–95. Deng H, et al. Systematic low-grade chronic inflammation and intrinsic mechanisms in polycystic ovary syndrome. Front Immunol. 2024;15:1470283. Li J, et al. Prevalence and risk factors for chronic endometritis in patients with adenomyosis and infertility: a retrospective cohort study. BMC Womens Health. 2024;24(1):403. Li J, et al. Analysis of pregnancy outcomes in patients with recurrent implantation failure complicated with chronic endometritis. Front Cell Dev Biol. 2023;11:1088586. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8780845","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":604549666,"identity":"d82b6b61-bb21-4823-82cd-e4961cd914ad","order_by":0,"name":"Lijie Wang","email":"","orcid":"","institution":"Lanzhou University Second Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lijie","middleName":"","lastName":"Wang","suffix":""},{"id":604549667,"identity":"3f948bc2-57ab-402a-a1ce-12f95aa5daa3","order_by":1,"name":"Lu Jiang","email":"","orcid":"","institution":"Lanzhou University Second Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Jiang","suffix":""},{"id":604549668,"identity":"170dd183-dce1-4aa7-a672-3f098e7bbdb7","order_by":2,"name":"Fei Yang","email":"","orcid":"","institution":"Lanzhou University Second Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Yang","suffix":""},{"id":604549669,"identity":"761766d4-7a9e-4add-a530-a60708160747","order_by":3,"name":"Fang Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYLCCChDB3twAohgbiNJyBkTwHCRZi0QikVr4pc8YMBxss8uTj3zY/JmHwUZ2wwHmZw/waZHsywFpSS42vJ3YYMzDkGa84QCbuQE+LQZneAyYP25jTtw4O7EhmYfhcOKGAzxsEvi02AO1MBzcVp+4cebBhsM8DP8JazHgAWs5nDhfgrGxmYfhAGEtEmfYChgO/jueuIEnsZlxjkGy8czDbGZ4tfD3MG9gOHCmOnF+++HDH95U2Mn2HW9+hlcLAwOH+Q+wCw+ASSBmxq8eCNgfgCn5BoIqR8EoGAWjYKQCAEL5S08MhUsPAAAAAElFTkSuQmCC","orcid":"","institution":"Lanzhou University Second Hospital","correspondingAuthor":true,"prefix":"","firstName":"Fang","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-02-04 02:09:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8780845/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8780845/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104546987,"identity":"dd1b08b4-ab4a-41dc-9697-6626bf82d03c","added_by":"auto","created_at":"2026-03-13 07:30:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59840,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8780845/v1/ed6ba3abf3d452cd9c7f226f.jpg"},{"id":108719338,"identity":"951af8e5-f687-4b21-93a9-1757951218df","added_by":"auto","created_at":"2026-05-07 15:41:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":696255,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8780845/v1/84b76081-7563-4e69-bd76-69accb4f60a4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation Between Chronic Endometritis and Early Pregnancy Loss: a prospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003ePregnancy loss (PL) is clinically defined as the spontaneous cessation of fetal development before 24 weeks of gestation. Early pregnancy loss (EPL) refers to embryonic loss occurring before 10 weeks of gestation, including biochemical pregnancy[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Approximately 25% of clinically recognized pregnancies result in Early pregnancy loss, making it the most common complication of pregnancy. The majority of EPL are attributed to random numerical chromosomal abnormalities[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Other risk factors include a history of early pregnancy loss, genital tract pathogen infections, advanced age, extremes in body mass index (BMI), smoking, alcohol consumption, physical trauma, psychological stress, exposure to air pollution, and pesticide exposure, among others[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChronic endometritis (CE) is defined as chronic inflammation of the endometrial lining. Patients with CE are often asymptomatic; however, they may present with clinical manifestations such as pelvic pain, dyspareunia, abnormal vaginal bleeding, or vaginal discharge[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Studies report a prevalence of CE among RPL patients ranging from 13% to 56%[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The gold standard for diagnosing CE is the histological identification of plasma cells in the endometrial stroma via CD138 immunohistochemical assessment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe pathophysiology of CE may have a relationship with the endometrial microbiome is widely accepted[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], as evidenced by the effectiveness of antibiotic treatment in reducing stromal infiltration[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It is believed that plasma cell infiltration of the endometrium may affect endometrial receptivity and result in RPL[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Several studies have showed the impact of CE on pregnancy outcomes in women with RPL[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. CE patients suffer from repeated planting failure, abortion, premature birth, declined implantation rate of embryos in vitro fertilization (IVF) and other adverse pregnancy outcomes[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHowever, whether chronic endometritis is associated with early pregnancy loss remains controversial, as existing research findings are inconsistent and the evidence is insufficient to clarify the relationship[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Therefore, this study aims to explore the impact of chronic endometritis on early pregnancy loss and their potential association using a prospective cohort study.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eThis prospective cohort study enrolled 3,090 women with a history of at least one pregnancy loss who attended the Reproductive Center of the Second Hospital of Lanzhou University (Lanzhou, China) between December 2020 and December 2024. Ethical approval was granted (Ethics Approval No. 2019A-231). Detailed information regarding the cohort design has been described in our previous publication[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. PL was defined as pregnancy losses prior to 24 weeks of gestation with the same partner.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe collected comprehensive patient data, including obstetric history, age, educational background, ethnicity, Ethnicity, Menstrual Cycle, age at menarche, age at first pregnancy, body mass index (BMI), the number and types of previous pregnancy losses, History of Pelvic Surgery, Type of Pregnancy Loss and the final outcome of the current pregnancy. In addition, Clinical testing indicators included: serum immune indicators (complement C3, complement C4, immunoglobulin A, immunoglobulin M), inflammatory factor indicators (interleukin-6, interleukin-10, interferon-γ, tumor necrosis factor-α), coagulation function indicators, glucose and lipid metabolism indicators, blood routine, liver function indicators, renal function indicators, uterine ultrasound findings, and endometrial immunohistochemical indicators.\u003c/p\u003e \u003cp\u003ePatient inclusion criteria were as follows: (1)A history of at least two pregnancy losses before 24 weeks of gestation (including biochemical pregnancy), with the diagnosis of pregnancy loss based on the guidelines of the European Society of Human Reproduction and Embryology (ESHRE)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]; (2)Age between 18 and 42 years;(3) Patients who underwent hysteroscopy and endometrial immunohistochemistry;(4)3\u0026ndash;7 days after menstruation cessation;(5)No oral antibiotics or hormonal medications within 3 months prior to enrollment;(6)No vaginal medications within 3 months prior to hysteroscopy. Exclusion Criteria: (1) Patients lost to follow-up with no available pregnancy outcome by December 2024;(2) Subsequent pregnancy outcomes including ectopic pregnancy, hydatidiform mole, induced abortion due to fetal malformation, or pregnancy duration of less than 10 weeks by the follow-up cutoff date;(3) Patients with subsequent pregnancies was twin pregnancies.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasurements of serum indicators and immunohistochemical staining of the endometrium\u003c/h3\u003e\n\u003cp\u003eSerum Indicators: Venous blood (5 ml) was collected from the cubital vein of participants in a fasting state using standard dry blood collection tubes, and all samples were sent to the Clinical Laboratory of the Second Hospital of Lanzhou University for testing within 4 hours.\u003c/p\u003e \u003cp\u003eEndometrial Sample IHC: Endometrial tissue was collected via curettage with a curette during hysteroscopy (3\u0026ndash;5 days after menstruation cessation) for all patients. The tissue was rinsed with normal saline to remove residual bloodstains on the surface, then placed in a cryopreservation tube, fixed with 4% paraformaldehyde, embedded in paraffin, and sent to the Department of Pathology of the Second Hospital of Lanzhou University. Subsequently, we followed up on the results of hematoxylin-eosin (HE) staining and CD138 immunohistochemical (IHC) staining for histopathological examination of endometrial specimens. All staining procedures and result evaluations were performed by the same group of senior physicians with professional titles.\u003c/p\u003e\n\u003ch3\u003ePregnancy outcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome metrics analyzed in this study included early pregnancy loss (EPL), ongoing pregnancy (OP), and live birth in the subsequent pregnancies of patients with pregnancy loss (PL). EPL was defined as pregnancy loss occurring at a gestational age of less than 10 weeks, including biochemical pregnancy. OP was defined as a viable pregnancy lasting past 10 weeks of gestation. A live birth was defined as a pregnancy that reached or exceeded 28 weeks of gestation. All patients enrolled in the study were followed up every six months via the electronic medical record system or telephone to monitor their pregnancy status, with the follow-up of this study concluding in December 2025.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for continuous variables and as counts and percentages for categorical variables. Differences between two groups were assessed using the independent samples t-test, while those among three or more groups were analyzed via one-way analysis of variance (ANOVA). For categorical variables, the two-sided Pearson\u0026rsquo;s chi-square test or Fisher\u0026rsquo;s exact test was used as appropriate. Pearson correlation analysis was also conducted where applicable. The Bonferroni correction was applied for multiple group comparisons. Variables with a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in univariate analyses were included in multivariate logistic regression models to calculate odds ratios (ORs) for the associations between risk factors and infertility, non-live birth, and subsequent pregnancy loss. A two-tailed P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were performed using SPSS for Windows, Version 27.0 (SPSS Inc., Chicago, IL, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 1059 patients with pregnancy loss and definitive pregnancy outcomes were finally enrolled in this study, with the detailed enrollment flow shown in Fig.\u0026nbsp;1. The baseline characteristics of the participants summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Among them, 431 patients were diagnosed with chronic endometritis and 628 with non-chronic endometritis, yielding a prevalence of 39.8% (431/1059) of CE in the pregnancy loss (PL) population. The mean age of the participants was 30.91\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49 years. No statistically significant differences were observed between the CE and non-CE groups in terms of age (P\u0026thinsp;=\u0026thinsp;0.729), body mass index (BMI) (P\u0026thinsp;=\u0026thinsp;0.284), educational background (P\u0026thinsp;=\u0026thinsp;0.297), ethnicity (P\u0026thinsp;=\u0026thinsp;0.643), age at menarche (P\u0026thinsp;=\u0026thinsp;0.731), menstrual cycle regularity (P\u0026thinsp;=\u0026thinsp;0.324), history of induced abortion (P\u0026thinsp;=\u0026thinsp;0.513), history of live birth (P\u0026thinsp;=\u0026thinsp;0.255), total number of pregnancies (P\u0026thinsp;=\u0026thinsp;0.848), total number of pregnancy losses (P\u0026thinsp;=\u0026thinsp;0.709), history of pelvic surgery, and type of pregnancy loss (P\u0026thinsp;=\u0026thinsp;0.588).\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 of CE Patients Before Pregnancy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-CE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.91\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.82\u0026thinsp;\u0026plusmn;\u0026thinsp;4.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.71\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.84\u0026thinsp;\u0026plusmn;\u0026thinsp;3.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHan (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e964 (91.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e578 (90.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e382 (90.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHui (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (4.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (5.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (5.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTibetan (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (1.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (1.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (2.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Ethnicities (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (1.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (1.98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (1.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at Menarche (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual Cycle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e905 (85.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e552 (86.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e355 (84.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregular (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154 (14.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (13.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (15.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Live Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e898 (82.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e550 (86.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e334 (79.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197 (17.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (13.88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87 (20.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Pregnancy (TPs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy Losses (PLs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.709\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of Pelvic Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.516\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e860 (81.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e544 (85.23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e330 (78.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e199 (18.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (14.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91 (21.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Pregnancy Loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e791 (72.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e454 (71.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309 (73.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e304 (27.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184 (28.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112 (26.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBaseline Characteristics of Different Degrees of CE Before Pregnancy\u003c/h3\u003e\n\u003cp\u003eIn this study, chronic endometritis (CE) was diagnosed based on positive endometrial CD138 expression, and CE was classified into three severity grades according to the number of CD138-positive cells: mild CE (CD138 (+)\u0026thinsp;\u0026ge;\u0026thinsp;1/high-power field [HPF]), moderate CE (2/HPF\u0026thinsp;\u0026lt;\u0026thinsp;CD138 (+)\u0026thinsp;\u0026lt;\u0026thinsp;5/HPF), and severe CE (CD138 (+)\u0026thinsp;\u0026ge;\u0026thinsp;5/HPF)[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, we compared with the non-CE group, the CE group had a higher incidence of endometrial micropolyps, elevated immunoglobulin G (IgG), increased homocysteine (Hcy) levels, elevated interleukin-6 (IL-6), Mycoplasma positivity, and increased bilateral uterine artery blood flow resistance, indicating that these factors were associated with an elevated risk of CE, with statistically significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, elevated IL-6 and tumor necrosis factor-α (TNF-α) were also correlated with an increased risk of CE, with statistically significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No statistically significant differences were observed between the CE and non-CE groups in the remaining test indicators, including free triiodothyronine (FT3), free tetraiodothyronine (FT4), thyroid-stimulating hormone (TSH), D-dimer (D-Dimer),, immunoglobulin A (IgA), immunoglobulin M (IgM), complement C3, complement C4, fasting blood glucose, fasting insulin, neutrophils (NE), total cholesterol (CHO), low-density lipoprotein cholesterol (LDL-C), carbohydrate antigen 125 (CA125), 25-hydroxyvitamin D3 (25-OH-D3), urea, creatinine, uric acid, high-sensitivity C-reactive protein, interferon-γ, endometrial thickness, bilateral uterine artery pulsatility index (PI), bilateral uterine artery systolic/diastolic velocity ratio (S/D) (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\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\u003eBaseline Characteristics of Different Degrees of CE Before Pregnancy\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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal Patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNon-CE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMild CE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModerate CE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSevere CE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCD138(-)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCD138(+)\u0026ge;1/HPF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCD138(+)\u0026ge;5/HPF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\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\u003eSample Size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e147\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\u003eEndometrial Micropolyps\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbsent (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1004(94.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e605(96.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e118(96.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e148(91.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e139(94.63%)\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\u003ePresent (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55(5.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(3.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(3.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14(8.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8(5.37%)\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\u003eT3 (uIU /mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4 (uIU /mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.32\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.57\u0026thinsp;\u0026plusmn;\u0026thinsp;3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSH (uIU /mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Dimer (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.48\u0026thinsp;\u0026plusmn;\u0026thinsp;12.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.75\u0026thinsp;\u0026plusmn;\u0026thinsp;12.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.39\u0026thinsp;\u0026plusmn;\u0026thinsp;13.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.53\u0026thinsp;\u0026plusmn;\u0026thinsp;11.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.57\u0026thinsp;\u0026plusmn;\u0026thinsp;10.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplement C3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplement C4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.96\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.78\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunoglobulin M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHcy (umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.59\u0026thinsp;\u0026plusmn;\u0026thinsp;2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.23\u0026thinsp;\u0026plusmn;\u0026thinsp;2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHO (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet Count✖109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e234.13\u0026thinsp;\u0026plusmn;\u0026thinsp;83.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232.67\u0026thinsp;\u0026plusmn;\u0026thinsp;91.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e234.21\u0026thinsp;\u0026plusmn;\u0026thinsp;60.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e234.28\u0026thinsp;\u0026plusmn;\u0026thinsp;70.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e235.19\u0026thinsp;\u0026plusmn;\u0026thinsp;81.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.03\u0026thinsp;\u0026plusmn;\u0026thinsp;7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.68\u0026thinsp;\u0026plusmn;\u0026thinsp;7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.21\u0026thinsp;\u0026plusmn;\u0026thinsp;7.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.79\u0026thinsp;\u0026plusmn;\u0026thinsp;8.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.99\u0026thinsp;\u0026plusmn;\u0026thinsp;7.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric Acid (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e271.48\u0026thinsp;\u0026plusmn;\u0026thinsp;57.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e264.81\u0026thinsp;\u0026plusmn;\u0026thinsp;51.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e265.60\u0026thinsp;\u0026plusmn;\u0026thinsp;55.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e280.16\u0026thinsp;\u0026plusmn;\u0026thinsp;60.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e271.88\u0026thinsp;\u0026plusmn;\u0026thinsp;65.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal pH Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e909(85.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e566(90.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105(86.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e137(84.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e121(82.46%)\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\u003eAbnormal (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150(14.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62(9.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(13.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26(15.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26(17.54%)\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\u003eMycoplasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.032\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e783(73.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e514(81.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97(79.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115(70.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94(63.62%)\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\u003ePositive (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e276(26.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114(18.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25(20.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47(29.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53(36.38%)\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\u003eIL-6(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e785(74.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e511(81.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86(78.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e114(70.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97(65.81%)\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\u003eElevated (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e274(25.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117(18.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(21.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48(29.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50(34.19%)\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\u003eInterferon-γ(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1027(96.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e613(97.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e118(96.71%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e157(97.03%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e142(96.59%)\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\u003eElevated (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32(3.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(2.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(3.29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(2.97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5(3.41%)\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\u003eTNF-α(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e970(91.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e596(94.86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102(91.48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e146(90.19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e132(89.98%)\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\u003eElevated (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89(8.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(5.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(8.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16(9.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15(10.02%)\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\u003eEndometrial Thickness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.10\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight_PI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight_RI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight _S/D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.46\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\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\u003eLeft_PI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft_RI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft _S/D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003ch3\u003eCorrelation Analysis Between Chronic Endometritis and Differentially Significant Indicators\u003c/h3\u003e\n\u003cp\u003eSpearman correlation analysis revealed that chronic endometritis was positively correlated with endometrial micropolyps (P = 0.043, r = 0.145), homocysteine (Hcy) (P = 0.031, r = 0.116), Mycoplasma positivity (P = 0.014, r = 0.210), right uterine artery resistance index (R_RI) (P = 0.040, r = 0.143), and left uterine artery resistance index (L_RI) (P = 0.042, r = 0.134). A positive r value indicates that the risk of CE increases with the elevation of the above indicators. However, no correlation was observed between CE and immunoglobulin G (IgG) (P \u0026gt; 0.05). The detailed results are presented in Table 3.\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eCorrelation between relevant differential indicators and CE in the study population\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEndometrial Polyps\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIgG\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHcy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMycoplasma\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR_RI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eL_RI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIL-6\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTNF-α\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003cp\u003eCorrelation Analysis Between Chronic Endometritis and Early Pregnancy Loss Pregnancy Outcomes Among Different Chronic Endometritis Groups\u003c/p\u003e\n \u003cp\u003eAt the end of the follow-up period, among the 1059 enrolled patients, the incidence of early pregnancy loss was 10.05% in the non-chronic endometritis (Non-CE) group. In the chronic endometritis group, 121 patients experienced EPL in subsequent pregnancies, with an incidence rate of 28.07% (121/431). Further analysis revealed that the incidence of EPL showed a significant upward trend with the increasing severity of CE: 15.82% in the mild CE group, 22.58% in the moderate CE group, and 33.94% in the severe CE group. The difference between groups was statistically significant (P \u0026lt; 0.001), and the detailed results are presented in Table 4.\u003c/p\u003e\n \u003cdiv\u003e \u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePregnancy Outcomes in Patients with CE\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTotal Patients\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-CE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCD138(-)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCD138 ≥ 1/HPF\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCD138 ≥ 5/HPF\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePregnancy Outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e865 (80.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e565 (89.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e103 (84.18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e109 (67.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98 (60.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEPL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e194 (19.59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63 (10.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (15.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53 (32.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49 (39.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eThe results of correlation analysis between chronic endometritis and early pregnancy loss\u003c/h2\u003e\n \u003cp\u003eThe logistic regression analysis showed in Table\u0026nbsp;5 that the presence of CE at baseline significantly increased the risk of EPL in subsequent pregnancies, and this association remained stable across different adjusted models: In the unadjusted model, patients with CD138 positivity had a 47% increased risk of EPL (OR = 1.47; 95% CI: 1.10–1.75; P = 0.001). In Model I (adjusted for age and body mass index [BMI]), the above correlation remained statistically significant (OR = 1.38; 95% CI: 1.21–1.49; P = 0.003). In the fully adjusted Model II (incorporating other confounding variables), patients with CE still had a 37% increased risk of EPL (OR = 1.37; 95% CI: 1.14–1.67; P = 0.003).\u003c/p\u003e\n \u003cp\u003eThe aforementioned association was also significant among subgroups with different degrees of CD138 positivity. Using CD138 ≥ 1/HPF (mild CE) as the reference group: In the unadjusted model, the risk of EPL increased significantly from moderate CE (2\u0026lt;CD138(+)\u0026lt;5/HPF) to severe CE (CD138 ≥ 5/HPF) (moderate CE: OR = 1.59, 95% CI: 1.19–2.81; severe CE: OR = 3.26, 95% CI: 1.26–5.79; P = 0.004). In Model I (adjusted for age and BMI), the risk of EPL remained significantly elevated in patients with moderate to severe CE (moderate CE: OR = 1.68, 95% CI: 1.41–2.84; severe CE: OR = 3.32, 95% CI: 1.12–4.87; P = 0.003). With further adjustment for age, BMI, and other confounding factors in Model II, the risk of EPL continued to increase (moderate CE: OR = 1.81, 95% CI: 1.46–3.88; severe CE: OR = 4.55, 95% CI: 1.91–6.49; P = 0.002).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eLogistic Regression Analysis of the Risk Between CE and EPL\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-adjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust I\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust II\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.47 (1.10, 1.75) 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.38 (1.21, 1.49) 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.37 (1.14, 1.67) 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)分级\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 1/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.59 (1.19, 2.81) 0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.68 (1.41, 2.84) 0.0201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.81 (1.46, 3.88) 0.0251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.26 (1.29, 5.79) 0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.32 (1.12, 4.87) 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.55 (1.91, 6.49) 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eAdjust I: Adjusted for age and BMI\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eAdjust II: Adjusted for age, BMI, and confounding variables (including endometrial polyps, homocysteine (Hcy), right uterine artery resistance index (R_RI), left uterine artery resistance index (L_RI), Mycoplasma positivity.)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eSubgroup Analysis and Interaction Test for the Correlation Between Chronic Endometritis and Early Pregnancy Loss\u003c/h2\u003e\n \u003cp\u003eWe further performed stratified analysis shown in Table\u0026nbsp;6 to explore the stability of the relationship between CE severity and the subsequent risk of EPL after stratifying by age, BMI, and number of previous pregnancy losses (PLs). After adjusting for the aforementioned confounding factors, the results were as follows: (1) Age subgroup: After adjusting for confounding variables, CE significantly increased the risk of EPL in PL patients aged ≥ 30 years (OR = 1.41; 95% CI: 1.06–1.89; P = 0.005); however, in PL patients under 30 years of age, CE was not associated with an increased risk of subsequent EPL (P \u0026gt; 0.05). (2) BMI subgroup: After adjusting for confounding variables, CE significantly increased the risk of recurrent EPL in PL patients regardless of whether their BMI was \u0026lt; 24 kg/m² (OR = 1.31; 95% CI: 1.09–1.63; P = 0.020) or ≥ 24 kg/m² (OR = 1.43; 95% CI: 1.21–3.95; P = 0.005). (3) PLs subgroup: CE was significantly associated with an increased risk of EPL in RPL patients with either ≤ 2 previous pregnancy losses (OR = 1.28; 95% CI: 1.06–1.83; P = 0.023) or ≥ 3 previous pregnancy losses (OR = 3.08; 95% CI: 1.26–4.78; P = 0.008). Additionally, among patients with ≥ 3 previous pregnancy losses, the number of CD138-positive cells was higher and CE severity was greater, suggesting that the more previous pregnancy losses a patient has, the more attention should be paid to the screening and severity assessment of endometritis.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSubgroup Analysis and Interaction Test for the Correlation Between CE and Subsequent EPL\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSubgroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEPL event (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrude OR (95%CI) \u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust OR (95%CI) \u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge \u0026lt; 30(year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23 (1.01, 1.41) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.27 (0.88, 1.71) 0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138 (+)-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 1/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40 (20.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52 (26.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.37 (0.81, 2.71) 0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.27 (0.36, 4.18) 0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58 (29.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.41(1.19, 7.05) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40 (0.56, 7.86) 0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge ≥ 30 (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34 (1.23, 1.45) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.41 (1.06, 1.89) 0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 1/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49 (25.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55 (28.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.91 (1.21, 5.13) 0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.15 (1.85, 8.93) 0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59 (29.74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.18 (5.06, 10.77) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.26 (1.39, 10.39) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI \u0026lt; 24 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29 (1.51, 1.78) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31 (1.09, 1.63) 0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 1/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42 (21.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48 (24.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.28 (1.43, 6.06) 0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.43 (0.59, 10.56) 0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58 (29.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.41 (5.38, 19.62) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.52 (1.42, 17.56) 0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI ≥ 24 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22 (1.09, 1.97) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.43 (1.21, 3.95) 0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 1/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42 (21.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56 (28.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48 (0.65, 3.88) 0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.46 (0.43, 12.58) 0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65 (33.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.78 (1.85, 14.49) 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.61 (1.64, 14.89) 0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLs ≤ 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34 (1.15, 1.59) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.28 (1.06, 1.83) 0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 1/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44 (22.51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49 (25.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.62 (0.81, 3.19) 0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.79 (0.76, 9.41) 0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55 (28.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.79 (2.41, 11.89) 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.46 (1.78, 10.66) 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLs ≥ 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.66 (1.35, 3.81) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.08 (1.26, 4.78) 0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+)-level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 1/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48 (24.47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026lt;CD138(+)\u0026lt;5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55 (28.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.30 (1.18, 7.88) 0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCD138(+) ≥ 5/HPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67 (34.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.27 (3.15, 14.78) \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.79 (1.13, 17.61) 0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n"},{"header":"Discussion","content":"\u003cp\u003eThe results of this study demonstrated that chronic endometritis (CE) was significantly associated with an increased risk of EPL in patients with pregnancy loss. Meanwhile, endometrial micropolyps, elevated Hcy levels, increased bilateral uterine artery blood flow resistance, vaginal Mycoplasma positivity, as well as elevated levels of IL-6 and TNF-α, were all closely correlated with the severity of CE. Additionally, linear regression analysis revealed a non-linear association between CE and the subsequent risk of EPL, with a higher severity of CE correlating with an increased risk of subsequent EPL. These findings hold important clinical significance and provide a reliable basis for the clinical management of PL patients and further in-depth research in related fields.\u003c/p\u003e \u003cp\u003eChronic endometritis is characterized by insidious and non-specific clinical symptoms, often overlooked by clinicians[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, in recent years, its hazards to women's reproductive health have become increasingly prominent. It has emerged as a crucial predisposing factor for unexplained infertility, recurrent implantation failure, and recurrent miscarriage, significantly impairing the pregnancy outcomes of assisted reproductive technology[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In the endometrial tissue of patients with CE, the expression of the pro-inflammatory cytokine interleukin-17 is increased, while the expression of anti-inflammatory mediators such as IL-10 is decreased[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Meanwhile, a large number of B cells infiltrate and differentiate into plasma cells, which disrupts the dynamic balance between pro-inflammatory and anti-inflammatory cytokines secreted by immune cells in the endometrium, leading to abnormal immune cell infiltration and imbalance in the inflammatory cytokine network[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These pathological changes result in reduced endometrial receptivity and abnormal decidualization, thereby impairing embryo implantation and pregnancy maintenance[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, the immunoglobulins secreted by plasma cells may exert embryotoxicity, further increasing the risk of EPL[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe pulsatility index PI and RI of the uterine artery are of great significance for maintaining the normal function of the endometrium, as well as for embryo implantation and development[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The core mechanism by which CE induces abnormal uterine artery blood flow lies in inflammation-mediated vascular microenvironment disorders: persistent inflammatory infiltration disrupts the dynamic balance of local inflammatory factors in the endometrium, thereby triggering tissue edema, vasospasm, and vascular endothelial damage, ultimately leading to increased uterine artery blood flow resistance. This is maybe cause EPL [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Chronic endometritis reduced endometrial receptivity and exacerbate the progression of invasive lesions in uterine blood vessels. Study results demonstrate that women with a history of untreated CE exhibit increased vascular resistance in the placental bed; furthermore, the more significant the abnormality of the blood flow velocity curve at this stage, the more severe the subsequent progression of preeclampsia will be[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study found that vaginal Mycoplasma positivity is associated with chronic endometritis and EPL. The mechanisms by which vaginal microecological imbalance drives the occurrence and development of CE related EPL are multifaceted[\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The direct damaging effect of pathogenic bacteria\u0026mdash;after colonizing the endometrium, pathogenic bacteria such as Escherichia coli and Streptococcus can form biofilms to evade immune clearance, leading to recurrent and persistent inflammation[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The signaling pathway activation by dysregulated flora\u0026mdash;the imbalanced flora triggers the NF-κB signaling pathway via TLR, prompting the massive release of pro-inflammatory cytokines such as IL-1β and IL-6. This further induces endometrial stromal edema and plasma cell infiltration, which are also the core pathological features of CE[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Finally, the downstream interfering effect of inflammatory factors further disrupted the expression of embryo implantation-related genes such as HOXA10 and integrin αvβ3, impair endometrial receptivity, and ultimately exacerbate reproductive function damage[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the subgroup analysis of the correlation between CE and EPL, age, BMI, and the number of previous pregnancy losses are all high-risk factors for EPL. A high BMI may increase the risk of CE by establishing a chronic inflammatory microenvironment and disrupting endocrine-immune balance[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. This association is particularly prominent in special populations with comorbid adenomyosis or recurrent reproductive failure[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. For women with a high BMI and advanced age, especially those with fertility needs, reasonable weight management may help reduce the risk of endometrial inflammation and EPL outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, CE is highly prevalent in PL patients, and its severity is an independent risk factor for subsequent EPL. The association between CE and EPL varies across different subgroups, with more significant effects in older patients and those with multiple previous pregnancy losses. These findings emphasize the importance of screening for CE and evaluating its severity in the clinical management of PL patients, particularly in high-risk subgroups, which may provide valuable insights for optimizing pregnancy outcomes.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLijie Wang and Fang Wang planned and designed the study. Wang Lijie and Lu Jiang collected the data. Fei Yang performed the analysis. Wang Lijie and Fei Yang interpreted the results. Lijie Wang contributed to writing the manuscript. All the authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author:\u0026nbsp;\u003c/strong\u003eFang Wang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupported by Medical Innovation and Development Project of Lanzhou University, Grant No. lzuyxcx-2022-137)\u003c/p\u003e\n\u003cp\u003eThe Science Foundation of Lanzhou University Second Hospital (Grant No. YJS-BD-19).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and Consent to participate\u0026rdquo; section- \u0026ldquo;This study adhered to the principles outlined in the Declaration of Helsinki. Approval was obtained from the Research Ethics Committee of the Second Hospital of Lanzhou University (approval number [NO.2019\u0026nbsp;A-231]), and written consent was obtained from all participating women.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCavalcante MB, et al. ESHRE guideline update 2022: New perspectives in the management of couples with recurrent pregnancy loss. Am J Reprod Immunol. 2023;90(2):e13739.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShorter JM, Atrio JM, Schreiber CA. Management of early pregnancy loss, with a focus on patient centered care. 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Front Cell Dev Biol. 2023;11:1088586.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pregnancy loss, Chronic endometritis, Pregnancy outcome, Logistic regression","lastPublishedDoi":"10.21203/rs.3.rs-8780845/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8780845/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEarly Pregnancy Loss (EPL) refers to embryonic loss occurring before 10 weeks of gestation, including biochemical pregnancy. Chronic Endometritis is a chronic inflammation of the endometrial lining. The association between chronic endometritis and early pregnancy loss remains controversial, with inconsistent findings and insufficient evidence from existing studies. Therefore, this study was conducted to address this research gap.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis prospective cohort study enrolled 1,059 patients with definitive pregnancy outcomes completed the study from December 2020 to December 2024. Using independent samples t-test, analysis of variance (ANOVA), and chi-square test were used to compare differences between groups, while logistic regression analysis was applied to explore the association between CE and EPL.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of CE among patients with pregnancy loss was 39.8% (431/1,059). The incidence of early pregnancy loss was 10.05% in the non-CE group and 28.07% in the CE group. With the increase in CE severity, the incidence of EPL gradually increased: 15.82% in the mild CE group, 22.58% in the moderate CE group, and 33.94% in the severe CE group, with a statistically significant difference between groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Multivariate logistic regression analysis showed that CE was an independent risk factor for EPL. After adjustment, patients with CE had a 37% increased risk of EPL (odds ratio OR\u0026thinsp;=\u0026thinsp;1.37, 95% CI: 1.14\u0026ndash;1.67, P\u0026thinsp;=\u0026thinsp;0.003). Subgroup analysis revealed that the association between CE and EPL was more pronounced in patients aged\u0026thinsp;\u0026ge;\u0026thinsp;30 years and those with \u0026ge;\u0026thinsp;3 previous pregnancy losses.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eChronic endometritis has a high prevalence among patients with pregnancy loss, and its severity is an independent risk factor for subsequent early pregnancy loss. The impact of CE on EPL is more significant in subgroups of older patients and those with multiple previous pregnancy losses. Clinically, screening for CE and assessment of its severity should be performed in patients with pregnancy loss, especially in high-risk subgroups, to optimize pregnancy outcomes.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003eThis study was registered in the Chinese Clinical Trial Registry with the registration number of ChiCTR2000039414 (27/10/2020)\u003c/p\u003e","manuscriptTitle":"Correlation Between Chronic Endometritis and Early Pregnancy Loss: a prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-13 07:30:30","doi":"10.21203/rs.3.rs-8780845/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fe684dc3-094d-4237-a429-0ed0ca2b6d5f","owner":[],"postedDate":"March 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T15:41:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-13 07:30:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8780845","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8780845","identity":"rs-8780845","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}