Establishment of a predictive model for histological chorioamnionitis in patients with preterm premature rupture of membranes: a single center retrospective study

Establishment of a predictive model for histological chorioamnionitis in patients with preterm premature rupture of membranes: a single center retrospective 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 Establishment of a predictive model for histological chorioamnionitis in patients with preterm premature rupture of membranes: a single center retrospective study Jindi Zhang, Hanglin Wu, Fangyuan Zheng, Xia Liu, Yun Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8063652/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 Objective: The aim of this study is to explore the risk factors for histological chorioamnionitis(HC) in patients with preterm premature rupture of membranes(PPROM), and further establish a simple and efficient predictive model for early prediction of the occurrence of HC. Methods: This study is a retrospective case-control study that included 308 patients with PPROM divided into a case group and a control group in a 1:1 ratio. The final pathological results of the placenta in the case group showed chorioamnionitis, while the control group was negative. This study collected relevant clinical and examination data of each research subject before delivery. Univariate and multivariate analysis were used to compare the data between the two groups, explore the risk factors for HC. And then a scoring formula was established based on the OR value to predict the occurrence of HC. Results: Univariate analysis showed statistical differences between the two groups in aspects age, gestational weeks(GW), time from the rupture to delivery(Duration), reproductive tract pathogens(RTP) cultivation, frequency of vaginal examinations(VE), antibiotic beginning time(ABT), glucocorticoids(GC) administering, Temperature(T), white blood cell(WBC) count and C-reactive protein(CRP). Multivariate analysis showed that VE, ABT, RTP, WBC and CRP were independent risk factors of HC. The AUC of ROC curve based on the established prediction formula reached 0.902, the sensitivity was 80.7%, the specificity was 86.2%, and the optimal cutoff value was 7.621. Conclusions: VE, ABT, RTP, WBC and CRP are independent risk factors for HC in PPROM patients. The prediction formula (0.60×VE+0.27×ABT+1.50+0.23×WBC+0.06×CRP) has good predictive value for the occurrence of HC. Individuals with a score above 7.621 have a significantly increased risk of developing HC. vaginal examinations preterm premature rupture of membrane chorioamnionitis predict Figures Figure 1 Introduction Premature rupture of membranes (PPROM) represents one of the leading causes of preterm birth, occurring in approximately 2–4% of pregnancies globally[1]. PPROM substantially elevates the risk of neonatal complications, including infection, respiratory distress syndrome, and cerebral palsy[2]. Histologic chorioamnionitis (HC) frequently complicates PPROM and is strongly associated with adverse maternal and neonatal outcomes, such as sepsis and neonatal encephalopathy[3]. PPROM is defined as spontaneous rupture of the fetal membranes prior to the onset of labor in pregnancies before 37 weeks of gestation[4]. Its etiology is multifactorial, involving several pathological mechanisms that may act independently or synergistically[5]. Chorioamnionitis represents a common obstetric complication, characterized by a reciprocal causal relationship with PPROM[6]. Ascending infection from the vagina and cervix is the most prevalent route of microbial invasion[7]. Following membrane rupture, the uterine cavity becomes exposed to the external environment, allowing bacteria to ascend and trigger a local inflammatory response. This leads to the release of abundant chemokines and inflammatory mediators [8], prompting massive neutrophil migration into the chorion and amnion, and resulting in HC[9]. Furthermore, infection by various microorganisms markedly increases intrauterine levels of endotoxins, cytokines (e.g., TNF-α), matrix metalloproteinases, and prostaglandins. These factors promote degradation of the extracellular matrix, cervical remodeling, loss of membrane integrity, uterine contractions, and ultimately membrane rupture[10]. Both PPROM and HC are associated with elevated risks of adverse maternal and fetal outcomes, including umbilical cord prolapse, fetal distress, neonatal infection, and preterm delivery[11]. Current research primarily focuses on clinical chorioamnionitis, which is characterized by overt signs such as fever and leukocytosis. In contrast, HC poses diagnostic challenges due to its frequently asymptomatic nature and the requirement of histopathological confirmation post-delivery. This often leads to delayed diagnosis and missed opportunities for timely intervention, thereby increasing the risk of adverse pregnancy outcomes[12]. Moreover, the risk factors for HC remain incompletely elucidated, and the scarcity of quantitative studies on dynamic biomarkers has hindered the development of reliable predictive tools for clinical use. Materials and methods Participants This study selected approximately 308 eligible pregnant women with premature rupture of membranes who were hospitalized in Hangzhou Women’s Hospital from May 2020 to April 2025. Based on the pathological results of the postpartum placenta, they were divided into a case group and a control group in a 1:1 ratio according to whether the pathological result of placenta is chorioamnionitis. The pathological diagnosis of chorioamnionitis is initially diagnosed by a pathologist with more than 5 years of experience and reviewed by another senior pathologist with more than 10 years of experience. The diagnostic criteria are based on the 2016 Amsterdam criteria[13]. All data in this study were obtained from hospital information systems. In addition, as this study is a retrospective study using data or specimens obtained from previous clinical diagnosis, treatment, and disease monitoring, the ethics committee has exempted the ethics of this study. The study was approved by the Ethics Committee of Hangzhou Women’s Hospital(Medical Ethics Review No.2025-121). Due to the retrospective design and the absence of identifiable information in the specimens and laboratory data utilized, the ethics committee exempted this study from the informed consent requirement. All patient data wrer kept strictly confidential. In addition, the study was conducted in accordance with the Declaration of Helsinki. Inclusion criteria: ① Premature rupture of membranes occurring at ≥ 28 weeks of pregnancy; ② Fetal survival; ③ Pathological diagnosis results of placenta can be obtained. Exclusion criteria: ① Accompanied by severe pregnancy complications (including severe preeclampsia, severe intrahepatic cholestasis of pregnancy, severe autoimmune disease, cardiovascular disease, liver and kidney disease, malignant tumors, and severe infections, etc.); ② Lack of clinical data such as laboratory tests, prenatal records, placental pathological diagnosis results, etc; ③ Fetal death. ④ Cervica cerclage before rupture of membranes. Clinical data collection This study included clinical and laboratory indicators such as age, gravidity, parity, body mass index(BMI), reproductive tract pathogens(RTP) cultivation, gestational weeks(GW) at the time of rupture, time from the rupture to delivery(Duration), frequency of vaginal examinations(VE), antibiotic beginning time(ABT), Temperature(T), white blood cell(WBC) count, C-reactive protein(CRP), whether labor analgesia(LA) was performed, whether glucocorticoids were administered, white blood cell count(WBC), C-reactive protein levels,(CRP) of two groups of research subjects. Among them, RTP cultivation was the first sample taken after membrane rupture occurred, and the frequency of VE is counted from membrane rupture to delivery. Instruments and reagents Complete blood count and C-reactive protein was detected by the automated five-part differential blood cell analyzer(Sysmex XN-2000, Japan). The testing program is strictly completed by the inspector in accordance with the operating specifications. Statistical Analysis In data processing, firstly, Shapro-Wilk test was conducted as the normality test to verify the normality distribution of various data items. In this study, most of the data were skewed distributions. Secondly, compare the data differences of each variable between the two groups through univariate analysis. Among them, the measurement data adopts Mann-Whitney U test, and the technical data adopts chi-square test to achieve single factor analysis. Further explore the independent risk factors for the occurrence of HC through multiple factor analysis. Finally, based on the obtained OR values, the relevant variable data of the two groups of research subjects were graded and quantified to obtain a predictive formula model. The total score of each research subject was calculated, and the predictive value of this formula model for HC was evaluated through the receiver operating characteristic(ROC) curve. Results Clinical data comparison between the HC group and control group There was no significant statistical difference in terms of BMI(Z=0.568, P>0.05), Gravidity(χ2=0.325, P>0.05), Parity(χ2=1.887, P>0.05) and GC(χ2=28.894, P>0.05) between these groups. However, statistically significant differences were observed on age(Z=2.050, P<0.05), GW(Z=-6.873, P<0.001), Duration(Z=9.635, P<0.001)), VE(Z=7.702, P<0.001), ABT(Z=4.825, P<0.001), RTP(χ2=15.013, P<0.001), GC(χ2=28.894, P<0.001), T(Z=6.153, P<0.001), WBC(Z=7.896, P<0.001) and CRP(Z=6.974, P<0.001, Table 1). Results of Binary Regression Analysis The outcomes of binary logistic regression analysis revealed that Parity[OR=4.561(1.334-15.600), P=0.016], VE[OR=1.830(1.497-2.237), P<0.001], ABT[1.305(1.112-1.530), P=0.001], RTP[4.470(1.859-10.748), P<0.001], LA[0.225(0.076-0.668), P=0.007], WBC[1.255(1.061-1.486), P=0.008] and CRP[1.058(1.004-1.114),P=0.036] exhibited significant associations with HC (Table 2). Establishment of the predictive models Based on the above binary regression analysis results, combined with the OR values of various variables, VE, ABT, RTP, and WBC were ultimately selected, and the corresponding β values [β=ln (OR)] were calculated to obtain the predicted total score for each research subject (Table 3). Predictive Value of the model incorporating VE, ABT, RTP and WBC As the ROC curve on the prediction formula showing, the area under the curve(AUC) was 0.902(0.867-0.936), and the model has good sensitivity(80.7%) and specificity(86.2%)(Fig 1). The Yoden index is 0.669, and the optimal cutoff value is 7.621. This result means that the prediction model has the best classification performance with a total calculation of 7.621 (Table 4). Discussion Preterm premature rupture of membranes (PPROM) and chorioamnionitis are frequently encountered in clinical obstetrics[ 14 ]. The prognosis for the fetus is inversely correlated with the gestational age at the time of infection—the earlier the infection occurs, the more adverse the outcomes. It has been reported that approximately 40% of patients with PPROM present with typical clinical signs such as fever and uterine tenderness[ 15 ]. Moreover, the incidence of chorioamnionitis exceeds 33% when membrane rupture persists for more than 24 hours[ 16 ]. Existing evidence has established associations between histological chorioamnionitis (HC) and maternal age, smoking, and systemic infection markers—including CRP and PCT—findings that are consistent with the present study[ 17 ]. Currently, numerous studies have established a correlation between WBC, CRP and the onset of chorioamnionitis, which are also included among the diagnostic criteria for clinical chorioamnionitis[ 18 – 20 ]. In this study, both WBC and CRP were associated with HC and therefore incorporated into the predictive model. This study demonstrated a positive association between the frequency of vaginal examinations and the occurrence of HC. This relationship may be attributed to the direct transfer of pathogens via examination gloves to the cervical os, as well as repeated mechanical disruption of the cervical mucus plug, facilitating bacterial translocation[ 21 ] These findings align with those reported in the cohort study by Gluck et al[ 22 ]. This study showed that a positive vaginal secretion culture is associated with a 3.47-fold increased risk of chorioamnionitis, underscoring the potential value of screening for lower genital tract colonization in late pregnancy. Furthermore, in cases complicated by reproductive tract infections, the local release of inflammatory cytokines such as IL-6 and TNF-α may compromise fetal membrane integrity and enhance susceptibility to intrauterine infection[ 23 ]. Several predictive models for chorioamnionitis have been reported in the literature. Studies have identified biomarkers in amniotic fluid—including CRP, NLR, IL-1β, TNF-α, and MMP-9—as valuable predictors of HC[ 24 , 25 ]. In a retrospective cohort analysis, Galletta et al. developed a model incorporating abdominal pain, uterine activity (palpable contractions), fever, latency > 3 days, and C-reactive protein. This model achieved an AUC of 0.726 in ROC curve, demonstrating modest predictive utility[ 26 ]. Based on multivariable analysis, our study derived the following predictive equation: 0.6×VE + 0.27×ABT + 1.50 + 0.23×WBC + 0.06×CRP. This model exhibits a larger AUC, along with improved sensitivity and specificity, suggesting strong potential for clinical translation. Additionally, while univariate analysis revealed no significant association between parity and HC, the multivariate model identified multiparity as an independent risk factor, conferring an increased risk for HC. This elevated risk in multiparous women may be attributed to factors such as prior cervical injury, increased cervical laxity, and enhanced susceptibility to ascending bacterial transmission[ 27 ]. Interestingly, this study observed an association between labor analgesia and a reduced risk of HC, a finding that diverges from some previous reports[ 28 , 29 ]. The conventional view holds that labor analgesia may be linked to intrapartum fever, potentially prolonged labor duration, and an increased risk of amniotic fluid contamination, thereby elevating the chorioamnionitis risk[ 30 , 31 ]. The discrepancy observed here may be attributable to the limited sample size in the present investigation. Currently, dynamic clinical indicators such as RPT and VE remain underexplored, with no existing reports on their use in predicting HC. This study successfully developed a novel prediction model that is cost-effective, straightforward, and accurate. By enabling clinicians to identify high-risk patients and initiate timely, individualized preventive measures, this tool can reduce either the incidence or severity of HC, thereby significantly improving maternal and neonatal prognoses. This study has several limitations: (Ⅰ) As a single-center investigation with a limited sample size, the findings require validation in larger, multi-center cohorts. Nonetheless, this work provides a foundational framework for such future research. (Ⅱ) The inclusion was restricted to pregnancies at 28 + 0 to 36 + 6 weeks of gestation, thereby excluding patients at the extremes of gestational age and limiting the generalizability of the model across the entire preterm spectrum. (Ⅲ) Some participants received antimicrobial therapy for conditions such as bleeding or uterine contractions prior to membrane rupture, which may have confounded the analysis of infection-related outcomes. Future studies should consider either excluding or stratifying such cases. Conclusion VE, ABT, RTP, WBC, and CRP were identified as independent risk factors for HC in patients with PPROM. The resulting predictive model established in this study ( 0.6×VE + 0.27×ABT + 1.50 + 0.23×WBC + 0.06×CRP) demonstrated good predictive value for HC occurrence in PPROM patients. Patients with a calculated score exceeding 7.621 were at substantially higher risk for HC, warranting more proactive clinical management.. Declarations Acknowledgments: Not applicable. Human Ethics and Consent to Participate declarations The study was approved by the Ethics Committee of Hangzhou Women’s Hospital(Medical Ethics Review No.2025-121). Due to the retrospective design and the absence of identifiable information in the specimens and laboratory data utilized, the ethics committee exempted this study from the informed consent requirement. All patient data wrer kept strictly confidential. In addition, the study was conducted in accordance with the Declaration of Helsinki. Author Contributions Yun Wang conceived and designed this study. Fangyuan Zheng collected all the data. Jindi Zhang conducted the statistical analysis and drafted the manuscript. Hanglin Wu and Xia Liu designed all the charts. Hanglin Wu, Jindi Zhang and Yun Wang participated in the explanation of the results. All of the authors critically reviewed the manuscript and approved the final version. Competing interests: On behalf of all authors, the corresponding author states that there is no conflict of interest. Funding: This work was supported by grants from Hangzhou Medical and Health Technology Project(A20252098). Availability of Data and Materials: The datasets used and analyzed during this study are available from the corresponding author on reasonable request. References Chen, Chih-Cheng, et al. Evaluating the diagnostic value of the early postnatal immature-to-total neutrophil ratio in histological chorioamnionitis. Pediatrics and neonatology vol. 66, 4 (2025): 293-294. doi: 10.1016/j.pedneo.2025.05.001. Guo, L, Han, W, Su, Y, et al. Perinatal risk factors for neonatal early-onset sepsis: a meta-analysis of observational studies. J MATERN-FETAL NEO M. 2023; 36 (2): 2259049. doi: 10.1080/14767058.2023.2259049. Sotodate, Genichiro, et al. 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Ling, L, Liu, B, Li, C, et al. Development and validation of a prediction model for intrapartum fever related to chorioamnionitis in parturients undergoing epidural analgesia. Sci Rep. 2024; 14 Sci Rep. doi: 10.1038/s41598-024-82722-y. Jia, L, Cao, H, Guo, Y, et al. Evaluation of Epidural Analgesia Use During Labor and Infection in Full-term Neonates Delivered Vaginally. JAMA Netw Open. 2021; 4 (9): e2123757. doi: 10.1001/jamanetworkopen.2021.23757. Tables Table 1.Univariate analysis of clinical data between two groups. Indicators Control Group (n=154) HC Group (n=154) Z/χ2 P Age(years) 30.00(28.00-33.00) 31.00(29.00-34.00) 2.050 0.040 * BMI(Kg/m 2 ) 26.04(23.44-27.93) 25.81(23.67-28.04) 0.568 0.570 Gravidity 0.325 0.648 =1 83(53.90) 78(50.65) ≧2 71(46.10) 76(49.35) Parity 1.887 0.212 =0 114(74.03) 103(66.88) ≧1 40(25.97) 54(33.12) GW(weeks) 35.00(33.00-35.00) 33.00(30.00-34.00) -6.873 ＜0.001 ** Duration 13.00(6.00-31.00) 76.50(26.00-153.00) 9.635 ＜0.001 ** VE 4.00(2.00-6.00) 7.00(4.00-9.00) 7.702 ＜0.001 ** ABT 2.00(1.00-3.00) 3.00(2.00-6.00) 4.825 ＜0.001 ** RTP 15.013 ＜0.001 ** =0 94(61.04) 60(38.96) =1 60(38.96) 94(61.04) GC 28.894 ＜0.001 ** =0 94(61.04) 47(30.52) =1 60(38.96) 107(69.48) LA 0.880 0.422 =0 114(74.03) 121(78.57) =1 40(25.97) 33(21.43) T 37.20(37.10-37.30) 37.40(37.20-37.80) 6.153 ＜0.001 ** WBC 8.80(7.50-10.30) 12.0(9.50-15.00) 7.896 ＜0.001 ** CRP 2.70(1.57-5.25) 7.72(2.90-20.90) 6.974 ＜0.001 ** The quantitative data were expressed by median and percentile [M (P 25 -P 75 )], and qualitative data were expressed by n(%). * , P<0.05; ** , P<0.001. HC, Histologic chorioamnionitis; BMI, Body mass index; GW, Gestational weeks; VE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; GC, glucocorticoids; LA, Labor analgesia; T, Temperature; WBC, White blood cell; CRP, C-Reactive protein. Table 2. Binary regression analysis of clinical data between two groups. Indicators B SE Wald df P OR(95%CI) Age 0.070 0.057 1.526 1 0.217 1.073(0.960-1.199) Gravidity -1.35 0.560 0.058 1 0.810 0.874(0.292-2.618) Parity 1.518 0.627 5.581 1 0.016 * 4.561(1.334-15.600) BMI -0.016 0.061 0.072 1 0.788 0.984(0.873-1.108) GW -0.098 0.079 1.564 1 0.211 0.906(0.777-1.057) Duration 0.002 0.002 1.180 1 0.277 1.002(0.998-1.007) VE 0.605 0.102 34.816 1 <0.001 ** 1.830(1.497-2.237) ABT 0.266 0.081 10.668 1 0.001 * 1.305(1.112-1.530) RTP 1.497 0.448 11.193 1 <0.001 ** 4.470(1.859-10.748) GC 0.617 0.468 1.739 1 0.187 1.853(0.741-4.637) LA -1.494 0.556 7.218 1 0.007 * 0.225(0.076-0.668) T 0.681 0.691 0.973 1 0.324 1.977(0.510-7.659) WBC 0.227 0.086 7.015 1 0.008 * 1.255(1.061-1.486) CRP 0.056 0.027 4.420 1 0.036 * 1.058(1.004-1.114) BMI, Body mass index; GW, Gestational weeks; VE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; GC, glucocorticoids; LA, Labor analgesia; T, Temperature; WBC, White blood cell; CRP, C-Reactive protein.; CI, confidence interval; * , P<0.05; ** , P<0.001. Table 3. Calculate regression coefficients and construct prediction model Indicators VE ABT RTP WBC CRP β 0.60 0.27 1.50 0.23 0.06 Score 0.60×VE 0.27×ABT 1.50 0.23×WBC 0.06×CRP Formula 0.60×VE+0.27×ABT+1.50+0.23×WBC+0.06×CRP VE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; WBC, White blood cell; CRP, C-Reactive protein. Table 4. The predictive value of the model incorporating VE, ABT, RTP, WBC and CRP Youden Sensitivity Specificity Cut-off AUC(95%CI) P 0.669 0.807 0.862 7.621 0.902(0.867-0.936) <0.001 VE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; WBC, White blood cell; CRP, C-Reactive protein; CI, confidence interval. Additional Declarations No competing interests reported. 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14:08:46","extension":"html","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":106514,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8063652/v1/86e47eba45f324f54aa0c848.html"},{"id":96791835,"identity":"05714a93-ec09-4eae-a023-b8d3a865c510","added_by":"auto","created_at":"2025-11-26 06:59:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27911,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of the model incorporating VE, ABT, RTP, WBC and CRP. VE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; WBC, White blood cell; CRP, C-Reactive protein.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8063652/v1/6f703d48c2c9b1f57123b65b.png"},{"id":101257766,"identity":"2f6cc694-c624-47a2-ae64-2ea8601cf1c9","added_by":"auto","created_at":"2026-01-27 19:25:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":916564,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8063652/v1/7794e0ec-eaff-4ff9-b30c-6124924a3a52.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEstablishment of a predictive model for histological chorioamnionitis in patients with preterm premature rupture of membranes: a single center retrospective study\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePremature rupture of membranes (PPROM) represents one of the leading causes of preterm birth, occurring in approximately 2\u0026ndash;4% of pregnancies globally[1]. PPROM substantially elevates the risk of neonatal complications, including infection, respiratory distress syndrome, and cerebral palsy[2]. Histologic chorioamnionitis (HC) frequently complicates PPROM and is strongly associated with adverse maternal and neonatal outcomes, such as sepsis and neonatal encephalopathy[3].\u003c/p\u003e\n\u003cp\u003ePPROM is defined as spontaneous rupture of the fetal membranes prior to the onset of labor in pregnancies before 37 weeks of gestation[4]. Its etiology is multifactorial, involving several pathological mechanisms that may act independently or synergistically[5]. Chorioamnionitis represents a common obstetric complication, characterized by a reciprocal causal relationship with PPROM[6]. Ascending infection from the vagina and cervix is the most prevalent route of microbial invasion[7]. Following membrane rupture, the uterine cavity becomes exposed to the external environment, allowing bacteria to ascend and trigger a local inflammatory response. This leads to the release of abundant chemokines and inflammatory mediators [8], prompting massive neutrophil migration into the chorion and amnion, and resulting in HC[9]. Furthermore, infection by various microorganisms markedly increases intrauterine levels of endotoxins, cytokines (e.g., TNF-\u0026alpha;), matrix metalloproteinases, and prostaglandins. These factors promote degradation of the extracellular matrix, cervical remodeling, loss of membrane integrity, uterine contractions, and ultimately membrane rupture[10]. Both PPROM and HC are associated with elevated risks of adverse maternal and fetal outcomes, including umbilical cord prolapse, fetal distress, neonatal infection, and preterm delivery[11].\u003c/p\u003e\n\u003cp\u003eCurrent research primarily focuses on clinical chorioamnionitis, which is characterized by overt signs such as fever and leukocytosis. In contrast, HC poses diagnostic challenges due to its frequently asymptomatic nature and the requirement of histopathological confirmation post-delivery. This often leads to delayed diagnosis and missed opportunities for timely intervention, thereby increasing the risk of adverse pregnancy outcomes[12]. Moreover, the risk factors for HC remain incompletely elucidated, and the scarcity of quantitative studies on dynamic biomarkers has hindered the development of reliable predictive tools for clinical use.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eParticipants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;This study selected approximately 308 eligible pregnant women with premature rupture of membranes who were hospitalized in Hangzhou Women\u0026rsquo;s Hospital from May 2020 to April 2025. Based on the pathological results of the postpartum placenta, they were divided into a case group and a control group in a 1:1 ratio according to whether the pathological result of placenta is chorioamnionitis. The pathological diagnosis of chorioamnionitis is initially diagnosed by a pathologist with more than 5 years of experience and reviewed by another senior pathologist with more than 10 years of experience. The diagnostic criteria are based on the 2016 Amsterdam criteria[13]. All data in this study were obtained from hospital information systems. In addition, as this study is a retrospective study using data or specimens obtained from previous clinical diagnosis, treatment, and disease monitoring, the ethics committee has exempted the ethics of this study. The study was approved by the Ethics Committee of Hangzhou Women\u0026rsquo;s Hospital(Medical Ethics Review No.2025-121). Due to the retrospective design and the absence of identifiable information in the specimens and laboratory data utilized, the ethics committee exempted this study from the informed consent requirement. All patient data wrer kept strictly confidential. In addition, the study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e①\u0026nbsp;Premature rupture of membranes occurring at \u0026ge; 28 weeks of pregnancy;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e②\u0026nbsp;Fetal survival;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e③\u0026nbsp;Pathological diagnosis results of placenta can be obtained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion criteria:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e①\u0026nbsp;Accompanied by severe pregnancy complications (including severe preeclampsia, severe intrahepatic cholestasis of pregnancy, severe autoimmune disease, cardiovascular disease, liver and kidney disease, malignant tumors, and severe infections, etc.);\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e②\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eLack of clinical data such as laboratory tests, prenatal records, placental pathological diagnosis results, etc;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e③\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eFetal death.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e④\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eCervica cerclage before rupture of membranes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical data collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included clinical and laboratory indicators such as age, gravidity, parity, body mass index(BMI), reproductive tract pathogens(RTP) cultivation, gestational weeks(GW) at the time of rupture, time from the rupture to delivery(Duration), frequency of vaginal examinations(VE), antibiotic beginning time(ABT), Temperature(T), white blood cell(WBC) count, C-reactive protein(CRP), whether labor analgesia(LA) was performed, whether glucocorticoids were administered, white blood cell count(WBC), C-reactive protein levels,(CRP) of two groups of research subjects. Among them, RTP cultivation was the first sample taken after membrane rupture occurred, and the frequency of VE is counted from membrane rupture to delivery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInstruments and reagents\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComplete blood count and C-reactive protein was detected by the automated five-part differential blood cell analyzer(Sysmex XN-2000, Japan). The testing program is strictly completed by the inspector in accordance with the operating specifications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e In data processing, firstly, Shapro-Wilk test was conducted as the normality test to verify the normality distribution of various data items. In this study, most of the data were skewed distributions. Secondly, compare the data differences of each variable between the two groups through univariate analysis. Among them, the measurement data adopts Mann-Whitney U test, and the technical data adopts chi-square test to achieve single factor analysis. Further explore the independent risk factors for the occurrence of HC through multiple factor analysis. Finally, based on the obtained OR values, the relevant variable data of the two groups of research subjects were graded and quantified to obtain a predictive formula model. The total score of each research subject was calculated, and the predictive value of this formula model for HC was evaluated through the receiver operating characteristic(ROC) curve.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical data comparison between the HC group and control group\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no significant statistical difference in terms of BMI(Z=0.568, P\u0026gt;0.05), Gravidity(\u0026chi;2=0.325, P\u0026gt;0.05), Parity(\u0026chi;2=1.887, P\u0026gt;0.05) and GC(\u0026chi;2=28.894, P\u0026gt;0.05) between these groups. However, statistically significant differences were observed on age(Z=2.050, P\u0026lt;0.05), GW(Z=-6.873, P\u0026lt;0.001), Duration(Z=9.635, P\u0026lt;0.001)), VE(Z=7.702, P\u0026lt;0.001), ABT(Z=4.825, P\u0026lt;0.001), RTP(\u0026chi;2=15.013, P\u0026lt;0.001), GC(\u0026chi;2=28.894, P\u0026lt;0.001), T(Z=6.153, P\u0026lt;0.001), WBC(Z=7.896, P\u0026lt;0.001) and CRP(Z=6.974, P\u0026lt;0.001, Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResults of Binary Regression Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe outcomes of binary logistic regression analysis revealed that Parity[OR=4.561(1.334-15.600), P=0.016], VE[OR=1.830(1.497-2.237), P\u0026lt;0.001], ABT[1.305(1.112-1.530), P=0.001], RTP[4.470(1.859-10.748), P\u0026lt;0.001], LA[0.225(0.076-0.668), P=0.007], WBC[1.255(1.061-1.486), P=0.008] and CRP[1.058(1.004-1.114),P=0.036] exhibited significant associations with HC (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEstablishment of the predictive models\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the above binary regression analysis results, combined with the OR values of various variables, VE, ABT, RTP, and WBC were ultimately selected, and the corresponding \u0026beta; values [\u0026beta;=ln (OR)] were calculated to obtain the predicted total score for each research subject (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePredictive Value of the model incorporating VE, ABT, RTP and WBC\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs the ROC curve on the prediction formula showing, the area under the curve(AUC) was 0.902(0.867-0.936), and the model has good sensitivity(80.7%) and specificity(86.2%)(Fig 1). The Yoden index is 0.669, and the optimal cutoff value is 7.621. This result means that the prediction model has the best classification performance with a total calculation of 7.621 (Table 4).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePreterm premature rupture of membranes (PPROM) and chorioamnionitis are frequently encountered in clinical obstetrics[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The prognosis for the fetus is inversely correlated with the gestational age at the time of infection\u0026mdash;the earlier the infection occurs, the more adverse the outcomes. It has been reported that approximately 40% of patients with PPROM present with typical clinical signs such as fever and uterine tenderness[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Moreover, the incidence of chorioamnionitis exceeds 33% when membrane rupture persists for more than 24 hours[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Existing evidence has established associations between histological chorioamnionitis (HC) and maternal age, smoking, and systemic infection markers\u0026mdash;including CRP and PCT\u0026mdash;findings that are consistent with the present study[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCurrently, numerous studies have established a correlation between WBC, CRP and the onset of chorioamnionitis, which are also included among the diagnostic criteria for clinical chorioamnionitis[\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In this study, both WBC and CRP were associated with HC and therefore incorporated into the predictive model.\u003c/p\u003e\u003cp\u003eThis study demonstrated a positive association between the frequency of vaginal examinations and the occurrence of HC. This relationship may be attributed to the direct transfer of pathogens via examination gloves to the cervical os, as well as repeated mechanical disruption of the cervical mucus plug, facilitating bacterial translocation[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] These findings align with those reported in the cohort study by Gluck et al[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study showed that a positive vaginal secretion culture is associated with a 3.47-fold increased risk of chorioamnionitis, underscoring the potential value of screening for lower genital tract colonization in late pregnancy. Furthermore, in cases complicated by reproductive tract infections, the local release of inflammatory cytokines such as IL-6 and TNF-α may compromise fetal membrane integrity and enhance susceptibility to intrauterine infection[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral predictive models for chorioamnionitis have been reported in the literature. Studies have identified biomarkers in amniotic fluid\u0026mdash;including CRP, NLR, IL-1β, TNF-α, and MMP-9\u0026mdash;as valuable predictors of HC[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In a retrospective cohort analysis, Galletta et al. developed a model incorporating abdominal pain, uterine activity (palpable contractions), fever, latency\u0026thinsp;\u0026gt;\u0026thinsp;3 days, and C-reactive protein. This model achieved an AUC of 0.726 in ROC curve, demonstrating modest predictive utility[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Based on multivariable analysis, our study derived the following predictive equation: 0.6\u0026times;VE\u0026thinsp;+\u0026thinsp;0.27\u0026times;ABT\u0026thinsp;+\u0026thinsp;1.50\u0026thinsp;+\u0026thinsp;0.23\u0026times;WBC\u0026thinsp;+\u0026thinsp;0.06\u0026times;CRP. This model exhibits a larger AUC, along with improved sensitivity and specificity, suggesting strong potential for clinical translation.\u003c/p\u003e\u003cp\u003eAdditionally, while univariate analysis revealed no significant association between parity and HC, the multivariate model identified multiparity as an independent risk factor, conferring an increased risk for HC. This elevated risk in multiparous women may be attributed to factors such as prior cervical injury, increased cervical laxity, and enhanced susceptibility to ascending bacterial transmission[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eInterestingly, this study observed an association between labor analgesia and a reduced risk of HC, a finding that diverges from some previous reports[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The conventional view holds that labor analgesia may be linked to intrapartum fever, potentially prolonged labor duration, and an increased risk of amniotic fluid contamination, thereby elevating the chorioamnionitis risk[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The discrepancy observed here may be attributable to the limited sample size in the present investigation.\u003c/p\u003e\u003cp\u003eCurrently, dynamic clinical indicators such as RPT and VE remain underexplored, with no existing reports on their use in predicting HC. This study successfully developed a novel prediction model that is cost-effective, straightforward, and accurate. By enabling clinicians to identify high-risk patients and initiate timely, individualized preventive measures, this tool can reduce either the incidence or severity of HC, thereby significantly improving maternal and neonatal prognoses.\u003c/p\u003e\u003cp\u003eThis study has several limitations: (Ⅰ) As a single-center investigation with a limited sample size, the findings require validation in larger, multi-center cohorts. Nonetheless, this work provides a foundational framework for such future research. (Ⅱ) The inclusion was restricted to pregnancies at 28\u0026thinsp;+\u0026thinsp;0 to 36\u0026thinsp;+\u0026thinsp;6 weeks of gestation, thereby excluding patients at the extremes of gestational age and limiting the generalizability of the model across the entire preterm spectrum. (Ⅲ) Some participants received antimicrobial therapy for conditions such as bleeding or uterine contractions prior to membrane rupture, which may have confounded the analysis of infection-related outcomes. Future studies should consider either excluding or stratifying such cases.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eVE, ABT, RTP, WBC, and CRP were identified as independent risk factors for HC in patients with PPROM. The resulting predictive model established in this study ( 0.6\u0026times;VE\u0026thinsp;+\u0026thinsp;0.27\u0026times;ABT\u0026thinsp;+\u0026thinsp;1.50\u0026thinsp;+\u0026thinsp;0.23\u0026times;WBC\u0026thinsp;+\u0026thinsp;0.06\u0026times;CRP) demonstrated good predictive value for HC occurrence in PPROM patients. Patients with a calculated score exceeding 7.621 were at substantially higher risk for HC, warranting more proactive clinical management..\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Hangzhou Women\u0026rsquo;s Hospital(Medical Ethics Review No.2025-121). Due to the retrospective design and the absence of identifiable information in the specimens and laboratory data utilized, the ethics committee exempted this study from the informed consent requirement. All patient data wrer kept strictly confidential. In addition, the study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYun Wang conceived and designed this study. Fangyuan Zheng collected all the data. Jindi Zhang conducted the statistical analysis and drafted the manuscript. Hanglin Wu and Xia Liu\u0026nbsp;designed all the charts.\u0026nbsp;Hanglin Wu, Jindi Zhang and Yun Wang participated in the explanation of the results. All of the authors critically reviewed the manuscript and approved the final version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by grants from Hangzhou Medical and Health Technology Project(A20252098).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials:\u0026nbsp;\u003c/strong\u003eThe datasets used and analyzed during this study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen, Chih-Cheng, et al. Evaluating the diagnostic value of the early postnatal immature-to-total neutrophil ratio in histological chorioamnionitis. Pediatrics and neonatology vol. 66, 4 (2025): 293-294. doi: 10.1016/j.pedneo.2025.05.001.\u003c/li\u003e\n\u003cli\u003eGuo, L, Han, W, Su, Y, et al. Perinatal risk factors for neonatal early-onset sepsis: a meta-analysis of observational studies. J MATERN-FETAL NEO M. 2023; 36 (2): 2259049. doi: 10.1080/14767058.2023.2259049.\u003c/li\u003e\n\u003cli\u003eSotodate, Genichiro, et al. Predictive score using umbilical vein leucine-rich \u0026alpha;-2 glycoprotein as a useful biomarker for diagnosing histological chorioamnionitis in preterm infants. The journal of obstetrics and gynaecology research vol. 51, 6 (2025): e16344. doi: 10.1111/jog.16344.\u003c/li\u003e\n\u003cli\u003eUshida, Takafumi, et al. Effect of chorioamnionitis on postnatal growth in very preterm infants: a population-based study in Japan. Archives of gynecology and obstetrics vol. 311, 5 (2024): 1321-1330. doi: 10.1007/s00404-024-07757-y.\u003c/li\u003e\n\u003cli\u003eRivera, Joanne N Qui\u0026ntilde;ones, et al. Outcomes after cerclage and preterm prelabor rupture of membranes: data from the International Collaborative for Cerclage Longitudinal Evaluation And Research (IC-CLEAR). American journal of obstetrics \u0026amp; gynecology MFM (2025): 101753. doi: 10.1016/j.ajogmf.2025.101753.\u003c/li\u003e\n\u003cli\u003ePanneflek, Timothy J R, et al. The effect of histological and subclinical chorioamnionitis and funisitis on breathing effort in premature infants at birth: a retrospective cohort study. EUROPEAN JOURNAL OF PEDIATRICS vol. 183, 12 (2024): 5497-5507. doi: 10.1007/s00431-024-05815-w.\u003c/li\u003e\n\u003cli\u003eBalogh, D\u0026oacute;ra Csenge, et al. Association of Meconium-Stained Amniotic Fluid and Histological Chorioamnionitis with Fetal Inflammatory Response in Preterm Deliveries. Children (Basel, Switzerland) vol. 12, 4 (2025): doi: 10.3390/children12040477.\u003c/li\u003e\n\u003cli\u003eLanzarone, Valeria, et al. Diagnostic tests for the prediction of histological chorioamnionitis and funisitis in pregnant women with preterm premature rupture of membranes: A systematic review. The Australian \u0026amp; New Zealand journal of obstetrics \u0026amp; gynaecology vol. 65, 1 (2024): 13-24. doi: 10.1111/ajo.13864.\u003c/li\u003e\n\u003cli\u003eKay, VR, Liang, I, Twiss, J, et al. Mode of delivery in chorioamnionitis: impact on neonatal and maternal outcomes. BMC Pregnancy Childbirth. 2024; 24 (1): 693. doi: 10.1186/s12884-024-06877-2.\u003c/li\u003e\n\u003cli\u003eTakahashi, Y, Fee, EL, Takahashi, T, et al. Interleukin-1 Receptor Antagonists Partially Inhibited Histological Injury but Not Tissue Inflammation in a Sheep Model of Pregnancy. REPROD SCI. 2025; 32 (4): 1213-1227. doi: 10.1007/s43032-024-01781-8.\u003c/li\u003e\n\u003cli\u003eGilboa, I, Gabbai, D, Lavie, A, et al. Clinical chorioamnionitis is a major risk factor for failed vacuum-assisted births - A retrospective cohort study. Eur J Obstet Gynecol Reprod Biol. 2025; 313 114632. doi: 10.1016/j.ejogrb.2025.114632.\u003c/li\u003e\n\u003cli\u003eCornet, MC, Kuzniewicz, MW, Scheffler, AW, et al. Maternal Fever During Labor and the Risk of Neonatal Encephalopathy: Duration and magnitude of hyperthermia. Am J Obstet Gynecol. 2025; doi: 10.1016/j.ajog.2025.07.046.\u003c/li\u003e\n\u003cli\u003eKhong, TY, Mooney, EE, Ariel, I, et al. Sampling and Definitions of Placental Lesions: Amsterdam Placental Workshop Group Consensus Statement. ARCH PATHOL LAB MED. 2016; 140 (7): 698-713. doi: 10.5858/arpa.2015-0225-CC.\u003c/li\u003e\n\u003cli\u003eChallacombe, FL, Suchomelova, Z, Zampieri, C, et al. Preterm premature rupture of the membranes (PPROM): a study of patient experiences and support needs. J Reprod Infant Psychol. 2024; 43 (4): 926-943. doi: 10.1080/02646838.2024.2314179.\u003c/li\u003e\n\u003cli\u003eOzkan, MA, Seyhanlı, Z, Ergani, SY, et al. Prediction of Delivery Timing in Preterm Premature Rupture of Membranes: The Role of Inflammation-Related Indices. Am J Reprod Immunol. 2025; 94 (1): e70124. doi: 10.1111/aji.70124.\u003c/li\u003e\n\u003cli\u003eTsumura, K, Yamasaki, F, Nomiyama, M, et al. Relationship between fetal inflammatory response syndrome and stages of acute placental inflammation stratified by the presence or absence of preterm premature rupture of membranes. Placenta. 2025; 167 64-70. doi: 10.1016/j.placenta.2025.05.001.\u003c/li\u003e\n\u003cli\u003eGabbai, Daniel, et al. Neutrophil-To-Lymphocyte Ratio and Delivery Within 24\u0026thinsp;h in Preterm Premature Rupture of Membranes: A Retrospective Cohort Study. BJOG : an international journal of obstetrics and gynaecology vol. 132, 10 (2025): 1454-1459. doi: 10.1111/1471-0528.18208.\u003c/li\u003e\n\u003cli\u003eMegli, CJ, Carlin, SM, Giacobe, EJ, et al. Virulence and pathogenicity of group B Streptococcus: Virulence factors and their roles in perinatal infection. Virulence. 2025; 16 (1): 2451173. doi: 10.1080/21505594.2025.2451173.\u003c/li\u003e\n\u003cli\u003eSumino, M, Yoshida, T, Hirata, T, et al. New diagnostic criteria for clinical chorioamnionitis using only objective indicators: A retrospective study. J Neonatal Perinatal Med. 2025; 19345798251351002. doi: 10.1177/19345798251351002.\u003c/li\u003e\n\u003cli\u003eOzen, M, Vergara, A, Kitase, Y, et al. Chorioamnionitis Induces a Unique Time Course of Inflammatory Changes and Immune Reponses in the Brain and Spleen. Dev Neurosci. 2025; 1-15. doi: 10.1159/000546624.\u003c/li\u003e\n\u003cli\u003eMoncrieff, G, Gyte, GM, Dahlen, HG, et al. Routine vaginal examinations compared to other methods for assessing progress of labour to improve outcomes for women and babies at term. Cochrane Database Syst Rev. 2022; 3 Cochrane Database Syst Rev. doi: 10.1002/14651858.CD010088.pub3.\u003c/li\u003e\n\u003cli\u003eGluck, O, Mizrachi, Y, Ganer Herman, H, et al. The correlation between the number of vaginal examinations during active labor and febrile morbidity, a retrospective cohort study. BMC Pregnancy Childbirth. 2020; 20 (1): 246. doi: 10.1186/s12884-020-02925-9.\u003c/li\u003e\n\u003cli\u003ePresicce, P, Roland, C, Senthamaraikannan, P, et al. IL-1 and TNF mediates IL-6 signaling at the maternal-fetal interface during intrauterine inflammation. Front Immunol. 2024; 15 1416162. doi: 10.3389/fimmu.2024.1416162.\u003c/li\u003e\n\u003cli\u003eKacerovsky, M, Hornychova, H, Holeckova, M, et al. Predictive Value of the sFlt-1/PlGF Ratio and Interleukin-6 for the Presence of Placental Lesions in Spontaneous Preterm Labor with Intact Membranes with Delivery within 7 Days. FETAL DIAGN THER. 2024; 51 (6): 539-549. doi: 10.1159/000540203.\u003c/li\u003e\n\u003cli\u003eDong, X, Chen, X, Xue, M, et al. Changes in serum inflammatory factors in group B streptococcal infection and their predictive value for premature rupture of membranes complicated by chorioamnionitis. Biomark Med. 2024; 18 (7): 301-309. doi: 10.2217/bmm-2023-0588.\u003c/li\u003e\n\u003cli\u003eGalletta, MAK, Schultz, R, Sartorelli, MFGOP, et al. Clinical characteristics, complications, and predictive model of histological chorioamnionitis in women with preterm premature rupture of membranes. PLoS One. 2023; 18 PLoS One. doi: 10.1371/journal.pone.0283974.\u003c/li\u003e\n\u003cli\u003eSeravalli, V, Colucci, C, Di Cencio, C, et al. Latency to delivery and incidence of adverse obstetric and perinatal outcomes in preterm premature rupture of membranes before 32 weeks. Arch Gynecol Obstet. 2025; 311 (6): 1569-1577. doi: 10.1007/s00404-025-07970-3.\u003c/li\u003e\n\u003cli\u003eAn, H, Zheng, W, Zhu, Q, et al. Retrospective study of intrapartum fever in term pregnancies and adverse obstetric and neonatal outcomes. PeerJ. 2022; 10 e14242. doi: 10.7717/peerj.14242.\u003c/li\u003e\n\u003cli\u003eLipschuetz, M, Guedalia, J, Daud-Sabag, L, et al. Chorioamnionitis and its association with neonatal and maternal adverse outcomes in women with and without epidural analgesia administration. EUR J OBSTET GYN R B. 2022; 273 EUR J OBSTET GYN R B. doi: 10.1016/j.ejogrb.2022.04.011.\u003c/li\u003e\n\u003cli\u003eLing, L, Liu, B, Li, C, et al. Development and validation of a prediction model for intrapartum fever related to chorioamnionitis in parturients undergoing epidural analgesia. Sci Rep. 2024; 14 Sci Rep. doi: 10.1038/s41598-024-82722-y.\u003c/li\u003e\n\u003cli\u003eJia, L, Cao, H, Guo, Y, et al. Evaluation of Epidural Analgesia Use During Labor and Infection in Full-term Neonates Delivered Vaginally. JAMA Netw Open. 2021; 4 (9): e2123757. doi: 10.1001/jamanetworkopen.2021.23757.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"547\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 547px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.Univariate analysis of clinical data between two groups.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl Group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=154)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHC Group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=154)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ/\u0026chi;2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e30.00(28.00-33.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e31.00(29.00-34.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e2.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.040\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eBMI(Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e26.04(23.44-27.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e25.81(23.67-28.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.570\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e83(53.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e78(50.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e≧2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e71(46.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e76(49.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e1.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e114(74.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e103(66.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e≧1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e40(25.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e54(33.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eGW(weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e35.00(33.00-35.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e33.00(30.00-34.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e-6.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eDuration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e13.00(6.00-31.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e76.50(26.00-153.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e9.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eVE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e4.00(2.00-6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e7.00(4.00-9.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e7.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eABT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e2.00(1.00-3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e3.00(2.00-6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e4.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eRTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e15.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e94(61.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e60(38.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e60(38.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e94(61.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e28.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e94(61.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e47(30.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e60(38.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e107(69.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eLA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.422\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e114(74.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e121(78.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e=1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e40(25.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e33(21.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e37.20(37.10-37.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e37.40(37.20-37.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e6.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e8.80(7.50-10.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e12.0(9.50-15.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e7.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e2.70(1.57-5.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 138px;\"\u003e\n \u003cp\u003e7.72(2.90-20.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e6.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe quantitative data were expressed by median and percentile [M (P\u003csub\u003e25\u003c/sub\u003e-P\u003csub\u003e75\u003c/sub\u003e)], and qualitative data were expressed by n(%). \u003csup\u003e*\u003c/sup\u003e, P\u0026lt;0.05; \u003csup\u003e**\u003c/sup\u003e, P\u0026lt;0.001. HC, Histologic chorioamnionitis; BMI, Body mass index; GW, Gestational weeks; VE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; GC, glucocorticoids; LA, Labor analgesia; T, Temperature; WBC, White blood cell; CRP, C-Reactive protein.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Binary regression analysis of clinical data between two groups.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWald\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.073(0.960-1.199)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eGravidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e0.874(0.292-2.618)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eParity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e5.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.016\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e4.561(1.334-15.600)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e0.984(0.873-1.108)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eGW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e-0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e0.906(0.777-1.057)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eDuration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.002(0.998-1.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eVE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e34.816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.830(1.497-2.237)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eABT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e10.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.305(1.112-1.530)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eRTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e1.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e4.470(1.859-10.748)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e1.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.853(0.741-4.637)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eLA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e-1.494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.556\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e7.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.007\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e0.225(0.076-0.668)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.977(0.510-7.659)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e7.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.008\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.255(1.061-1.486)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e4.420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.036\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 158px;\"\u003e\n \u003cp\u003e1.058(1.004-1.114)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI, Body mass index; GW, Gestational weeks; VE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; GC, glucocorticoids; LA, Labor analgesia; T, Temperature; WBC, White blood cell; CRP, C-Reactive protein.; CI, confidence interval; \u003csup\u003e*\u003c/sup\u003e, P\u0026lt;0.05; \u003csup\u003e**\u003c/sup\u003e, P\u0026lt;0.001.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"574\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 574px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3. Calculate regression coefficients and construct prediction model\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eABT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRTP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWBC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eScore\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.60\u0026times;VE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.27\u0026times;ABT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.23\u0026times;WBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0.06\u0026times;CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003eFormula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 465px;\"\u003e\n \u003cp\u003e0.60\u0026times;VE+0.27\u0026times;ABT+1.50+0.23\u0026times;WBC+0.06\u0026times;CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eVE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; WBC, White blood cell; CRP, C-Reactive protein.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"561\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 561px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4. The predictive value of the model incorporating VE, ABT, RTP, WBC and CRP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYouden\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e7.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e0.902(0.867-0.936)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eVE, Viginal examinations; ABT, Antibiotic beginning time; RTP, Reproductive tract pathogens; WBC, White blood cell; CRP, C-Reactive protein; CI, confidence interval.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"vaginal examinations, preterm premature rupture of membrane, chorioamnionitis, predict","lastPublishedDoi":"10.21203/rs.3.rs-8063652/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8063652/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThe aim of this study is to explore the risk factors for histological chorioamnionitis(HC) in patients with preterm premature rupture of membranes(PPROM), and further establish a simple and efficient predictive model for early prediction of the occurrence of HC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis study is a retrospective case-control study that included 308 patients with PPROM divided into a case group and a control group in a 1:1 ratio. The final pathological results of the placenta in the case group showed chorioamnionitis, while the control group was negative. This study collected relevant clinical and examination data of each research subject before delivery. Univariate and multivariate analysis were used to compare the data between the two groups, explore the risk factors for HC. And then a scoring formula was established based on the OR value to predict the occurrence of HC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eUnivariate analysis showed statistical differences between the two groups in aspects age, gestational weeks(GW), time from the rupture to delivery(Duration), reproductive tract pathogens(RTP) cultivation, frequency of vaginal examinations(VE), antibiotic beginning time(ABT), glucocorticoids(GC) administering, Temperature(T), white blood cell(WBC) count and C-reactive protein(CRP). Multivariate analysis showed that VE, ABT, RTP, WBC and CRP were independent risk factors of HC. The AUC of ROC curve based on the established prediction formula reached 0.902, the sensitivity was 80.7%, the specificity was 86.2%, and the optimal cutoff value was 7.621.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e VE, ABT, RTP, WBC and CRP are independent risk factors for HC in PPROM patients. The prediction formula (0.60×VE+0.27×ABT+1.50+0.23×WBC+0.06×CRP) has good predictive value for the occurrence of HC. Individuals with a score above 7.621 have a significantly increased risk of developing HC.\u003c/p\u003e","manuscriptTitle":"Establishment of a predictive model for histological chorioamnionitis in patients with preterm premature rupture of membranes: a single center retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 06:59:06","doi":"10.21203/rs.3.rs-8063652/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":"a053019f-fce3-4f73-86a5-9901cf3d8663","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-27T19:24:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-26 06:59:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8063652","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8063652","identity":"rs-8063652","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}