Stage-Specific Pathogen and Risk Factors in Pregnancy, Parturition, and Puerperium: A Retrospective Cohort Study

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Physiological adaptations during gestation complicate early sepsis recognition, while delayed source control exacerbates risks. Stage-specific variations in pathogen and modifiable risk factors have not been adequately studied. Methods This retrospective cohort study analyzed pathogen profiles and infection systems in pregnany, perinatal, and puerperal patients undergoing pathogen testing at Gansu Provincial Maternal and Child Health Hospital from January 2020 to December 2024. Logistic regression was used to identify risk factors, with unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) reported. Results A total of 193 maternal were included, with 28 cases of sepsis and 165 non-sepsis cases. Bacterial pathogens dominate in perinatal stages, peaking at parturition. Maternal infection sites exhibited a distinct perinatal pattern: the lowest rates occurred during pregnancy (predominantly genital, respiratory, and urinary tract infections), peaked in the perinatal period (primarily genital and respiratory infections), and declined during the puerperium (with genital infections and newly emerging urinary tract and surgical site infections). Specific like Escherichia coli , Enterococcus faecalis , and Mycoplasma show stage-specific abundance changes. During perinatal, several factors were significantly associated with an increased risk of sepsis. Notably, maternal operation was strongly associated with sepsis (OR = 6.87, 95% CI: 1.76–26.74), Additionally, maternal anemia (OR = 3.83, 95% CI: 1.26–11.67) and hypoproteinemia (OR = 5.72, 95% CI: 1.68–19.54) were also significantly linked to higher odds of sepsis. Conclusion Maternal sepsis demonstrates distinct stage-specific microbial, with bacterial dominance and genital tract infections surging during perinatal. Hypoproteinemia, anemia, and surgical history are critical modifiable risk factors, underscoring the need for targeted interventions during high-risk perinatal phases. Sepsis Pregnancy Parturition Puerperium Figures Figure 1 Figure 2 Figure 3 1 Introduction Maternal sepsis, a life-threatening condition characterized by infection-induced organ dysfunction during pregnancy, childbirth, abortion, or the postpartum period (1), accounts for 11% of global maternal mortality(2, 3). Pregnant and postpartum women are particularly vulnerable to infections and subsequent sepsis, which represent major causes of intensive care unit (ICU) admissions and maternal deaths. The perinatal period involves unique immuno-physiological adaptations, including gestational immune modulation, hormonal fluctuations, and genitourinary tract changes, resulting in distinct susceptibility patterns across pregnancy, labor, and puerperium(4, 5). This evolving host microenvironment not only elevates infection risk but may also obscure clinical manifestations, leading to delayed diagnosis. These physiological alterations not only increase infection risk but may also mask typical clinical signs, potentially delaying diagnosis. Although obstetric-specific early warning tools, such as the Obstetric Modified Sequential Organ Failure Assessment (omSOFA) and maternal sepsis management guidelines(2, 6), have been developed, maternal sepsis exhibits distinct physiological characteristics during pregnancy, parturition, and the puerperium, with variations in pathogenic microbiomes and infection sites across these stages. Further stage-specific research remains imperative. To address these limitations, we performed a historical cohort study combining clinical data analysis with microbial profiling and multivariable regression. This study aims to characterize perinatal stage-dependent risk factors for maternal sepsis. 2 Methods Participants This retrospective cohort study included patients admitted between January 1, 2020, and December 31, 2024, comprising: (1) pregnant women hospitalized with suspected infections, (2) women developing infections during parturition, and (3) puerperium women readmitted with suspected infections. All enrolled patients underwent microbiological culture testing from infection-related sites, including blood, sputum, urine, and secretion cultures. Exclusion criteria: (1) No use of antibiotics or antiviral agents, (2) Acute pancreatitis, and (3) Patients without pathogen testing or microbiological cultures. All specimens were collected following standardized procedures prior to antibiotic administration and immediately transported for laboratory analysis. Venous blood was concurrently drawn for complete blood count (CBC) and procalcitonin (PCT) testing. Data collection Data were extracted from the Hospital Information System (HIS), encompassing: (1) maternal baseline characteristics (age, gestational status at admission, and gestational age), (2) clinical features (comorbidities, involved infection systems, infection sites, and causative pathogens), (3) surgical interventions including cesarean section, ureteral stent placement, and wound debridement), (4) sepsis diagnosis coded according to ICD-10, and (5) concordance of antibiotic administration pre- and post-microbiological testing. Patient consent was waived due to historical cohort study design. Obstetrics and Gynecology Intensive Care Unit, Gansu Maternal and Child Health Hospital (Gansu Provincial Center Hospital) provided approval for the study and consent forms (No. 47/2025/GSFY). Definitions and participant classifications P5articipant in the study comprising: (1) pregnant women hospitalized with suspected infections, (2) women developing infections during parturition, and (3) puerperium women readmitted with suspected infections. Anemia was defined as a hemoglobin level less than 110 g/L. Hypoproteinemia was determined when serum albumin was below 30 g/L. Gestational diabetes mellitus (GDM) was diagnosed using the 75g oral glucose tolerance test (OGTT), with criteria of fasting plasma glucose ≥ 5.1 mmol/L, 1-hour plasma glucose ≥ 10.0 mmol/L, or 2-hour plasma glucose ≥ 8.5 mmol/L. According to the Sepsis-3.0 criteria, sepsis is diagnosed when an infection is present along with a Sequential Organ Failure Assessment (SOFA) score of ≥ 2. Antibiotic consistency was categorized into two scenarios: (1) Concordant empirical therapy: initial antibiotic selection matched subsequent antimicrobial susceptibility testing results;(2) Discordant empirical therapy: discrepancies existed between the initial antibiotic regimen and antimicrobial susceptibility testing findings. Data analysis Using EmpowerStats ( http://www.empowerstats.com ) and R 4.0.2 to analyze the data. Statistical significance was defined as p < 0.05. Categorical variables are presented as counts (n) and percentages (%). Normally distributed continuous variables are expressed as mean ± standard deviation, while non-normally distributed variables are reported as median (M) with interquartile range (IQR; P25, P75). The Kruskal-Wallis rank-sum test was applied for continuous variables, and Fisher’s exact test was used for categorical variables with expected cell counts < 10. Multivariable logistic regression models were employed to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for sepsis occurrence during pregnancy, parturition, and puerperium. 3 Results Among the 242 initially screened maternal, 25 maternal with upper respiratory tract infections who did not receive antibiotic or antiviral medication, maternal with acute pancreatitis, and maternal without pathogen blood testing were excluded from analyses. Finally, 193 maternal were enrolled in the final analyses. The maternal was stratified into three groups based on perinatal stages: pregnancy group (n = 32), parturition group (n = 119), and puerperium group (n = 42), with 28 cases (14.5%) diagnosed with sepsis. Significant intergroup differences in maternal age were observed (p = 0.009), Absolute neutrophil counts showed phase-dependent variations (p = 0.009), peaking during parturition (median 10.35×10⁹/L, IQR 0.95–29.46). Pathogen cultures revealed single-pathogen infections in 126 cases (65.3%), polymicrobial infections (≥ 2 pathogens) in 29 cases (15.1%), and no microbial growth in 38 cases (19.7%). Hypoproteinemia prevalence exhibited significant temporal heterogeneity (p < 0.001), occurring in 52.94% of parturition cases versus 15.62% in pregnancy and 30.95% in puerperium groups (Table 1 ). Table 1 Demographic Characteristics of Participant in the Study Infection Time Pregnancy Parturition Puerperium P-value N 32 119 42 Age (year) 28 ± 5 30 ± 5 27 ± 6 0.009 White blood cell (x 10 9 ) 9.09 (4.30-26.67) 12.40 (1.78–39.96) 113.60 (2.92–27.38) 0.126 Hemoglobin (g) 105.40 ± 23.68 104.52 ± 22.41 100.19 ± 18.48 0.487 Lymphocyte percentage (%) 11.35 (1.50–37.60) 10.20 (1.70–41.90) 11.30 (4.00-23.90) 0.483 Neutrophil percentage (%) 80.23 ± 8.32 82.29 ± 8.22 82.86 ± 6.10 0.322 Lymphocyte absolute value 1.08 (0.35–5.20) 1.21 (0.21–10.80) 1.29 (0.46–3.66) 0.868 Neutrophil absolute value 6.57 (2.41–24.21) 10.35 (0.95–29.46) 9.77 (2.14–26.30) 0.009 Monocyte absolute value 0.42 (0.02–1.75) 0.56 (0.01–2.08) 0.61 (0.03–1.77) 0.888 C- reactive protein 63.77 (5.33-228.26) 86.99 (2.00-244.64) 84.59 (12.41–202.30) 0.119 Procalcitonin 0.36 (0.02–16.94) 0.53 (0.09–22.14) 0.49 (0.11–11.73) 0.684 Complex Infection (%) 0.615 Single microbial 25 (89.29) 75 (79.79) 24 (77.42) Two or more types of microbial 3 (10.71) 19 (20.21) 7 (22.58) Hypoproteinemia (%) < 0.001 No 27 (84.38) 56 (47.06) 29 (69.05) Yes 5 (15.62) 63 (52.94) 13 (30.95) Anemia (%) 0.798 No 17 (53.12) 58 (48.74) 19 (45.24) Yes 15 (46.88) 61 (51.26) 23 (54.76) Gestational diabetes mellitus (%) 0.015 No 30 (93.75) 101 (84.87) 42 (100.00) Yes 2 (6.25) 18 (15.13) 0 (0.00) Causes of infection (%) 0.989 Not found 7 (21.88) 24 (20.17) 9 (21.43) Bacteria 22 (68.75) 82 (68.91) 29 (69.05) Viruses 3 (9.38) 11 (9.24) 3 (7.14) Ungi or parasites 0 (0.00) 2 (1.68) 1 (2.38) Sepsis (%) 0.067 No 8 (25.00) 12 (10.08) 8 (19.05) Yes 24 (75.00) 107 (89.92) 34 (80.95) The horizontal stacked bar chart in Fig. 1 shows distinct pathogen distribution patterns across pregnancy, parturition, and puerperium phases. Bacterial pathogens demonstrated the highest prevalence, with peak concentrations observed during parturition, followed by puerperium and pregnancy phases. Viral infections showed moderate detection rates, exhibiting slightly higher incidence in pregnancy and parturition compared to puerperium. Fungal and parasitic infections displayed the lowest occurrence rates, with minimal detection across all phases. Cases without identified pathogens were categorized as "no pathogen detected." The distribution of infection sites across perinatal stages (pregnancy, parturition, puerperium) is presented in Fig. 2 , categorized into genital tract, respiratory, digestive, urinary, wound, breast, pelvic, and unknown locations. During pregnancy, overall infection rates were lowest, with predominant genital tract and respiratory infections, plus mild urinary tract involvement. A marked increase in infection rates occurred during parturition, particularly for genital tract infections which peaked at this stage, accompanied by significantly elevated respiratory infections. Although puerperium infection rates decreased from parturition levels, they remained higher than pregnancy baselines, with persistent predominance of genital tract infections and notable presence of urinary and wound infections. The stacked area chart illustrates the distribution and relative abundance changes of different microbial communities across three physiological stages: pregnancy, parturition, and puerperium. As shown in Fig. 3 , Escherichia coli exhibits the highest abundance during pregnancy, which significantly decreases postpartum. Enterococcus faecalis and Mycoplasma are present at elevated levels during pregnancy, with a marked reduction during puerperium. Conversely, microbes specific to the puerperium, such as Enterococcus faecalis and Mycoplasma , show an increased abundance during this period. Most other microbial groups, including COVID-19 virus, Influenza virus, Streptococcus pneumoniae, Haemophilus influenzae, Listeria monocytogenes, Mycobacterium tuberculosis, Staphylococcus , and Other, maintain relatively low abundance across all stages. The results from the Logistic regression model in Table 2 demonstrate the odds ratios (OR) for the occurrence of sepsis during different stages of pregnancy. During the parturition period, age, complex infections, length of hospital stay, consistency of antibiotic use, anemia, hypoproteinemia, and surgical history were all significantly associated with the risk of sepsis, with hypoproteinemia and surgical history showing the most pronounced odds ratios of 5.72 (95% CI: 1.68, 19.54) and 6.87 (95% CI: 1.76, 26.74), respectively. In contrast to the pregnancy period, the risk of sepsis during the puerperium was lower. Although age, complex infections, anemia, and hypoproteinemia indicated a certain degree of increased risk (for instance, the odds ratio for anemia was 2.03 [95% CI: 0.61, 6.74]), none reached statistical significance. Table 2 Association between Various Factors and Sepsis during Pregnancy, Parturition, and Puerperium Exposure Pregnancy Parturition (OR, 95% CI) Puerperium (OR, 95% CI) Outcome Reference 2.97 (1.10, 8.06) 1.42 (0.47, 4.30) Plus age Reference 2.71 (0.98, 7.48) 1.58 (0.51, 4.90) Plus complex infection Reference 2.66 (0.96, 7.35) 1.55 (0.50, 4.83) Plus length of hospital stay Reference 2.88 (1.02, 8.13) 1.64 (0.52, 5.20) Plus antibiotic use consistency Reference 3.76 (1.24, 11.41) 1.96 (0.60, 6.42) Plus anemia Reference 3.83 (1.26, 11.67) 2.03 (0.61, 6.74) Plus hypoproteinemia Reference 5.72 (1.68, 19.54) 2.30 (0.67, 7.83) Plus operation Reference 6.87 (1.76, 26.74) 2.80 (0.71, 11.02) 4 Discussion Our study provides insights into the stage-specific vulnerability to infections during the perinatal period and their link to sepsis risk. Procalcitonin levels, a reliable biomarker for identifying infections, showed no significant differences among the three patient groups and were comparable to non-pregnant adults, aligning with prior studies(7). Infection rates peak during parturition and remain high in the puerperium, necessitating targeted interventions during childbirth and postpartum care. Genital tract infections are common across stages, with urinary system infections rising during pregnancy and respiratory infections during parturition. The physiological changes of pregnancy, such as immunomodulation and anatomical alterations, increase infection susceptibility. Childbirth, particularly cesarean delivery, disrupts natural barriers, facilitating pathogen entry(3, 8). These patterns are influenced by physiological changes, medical interventions, and postpartum recovery challenges(9, 10). The distribution of pathogens across stages reflects the physiological and immunological changes during pregnancy and childbirth. Bacterial infections, especially from Escherichia coli and Enterococcus faecalis , are predominant, suggesting enhanced screening and prophylaxis are needed(11, 12). The rise in fungal infections during the puerperium may relate to antibiotic and immunosuppressive therapy use(13). The area chart shows Escherichia coli and Enterococcus faecalis are more abundant during pregnancy, likely due to immune and reproductive tract changes(14). Mycoplasma and Ureaplasma urealyticum peak during parturition, possibly due to childbirth stress and trauma(15). Clinicians must recognize the distinct etiologies of sepsis in peripartum and postpartum patients with suspected infection to guide timely, pathogen-specific therapy(16). An increased incidence of viral infections (e.g., influenza, SARS-CoV-2) among pregnant individuals may be linked to pregnancy-associated physiological changes that heighten susceptibility to respiratory pathogens, with the peripartum period conferring elevated risks of morbidity and disease severity(17, 18). Listeriosis , a severe foodborne infection vertically transmitted from mother to fetus, can lead to severe neonatal and maternal complications. Early diagnosis and antibiotic treatment are critical for optimizing maternal-fetal outcomes(19, 20). Other microbial groups remain at low levels, indicating they are less commonly involved in infections during these stages. Previous studies have identified that in pregnant women with suspected or confirmed infections, prior delivery history, hemorrhage, trauma, underlying medical conditions, as well as hospital-acquired or secondary infections serve as significant risk factors for severe adverse outcomes(21). Our study further revealed that inconsistent antibiotic use, anemia, hypoproteinemia, and surgical procedures constitute high-risk factors for maternal sepsis. Prolonged hospital stay increases exposure to nosocomial pathogens, highlighting the need for efficient care protocols. Identified risk factors offer valuable insights for clinical practice. Cesarean delivery, while sometimes necessary, should consider infection risks(22). Hypoproteinemia, indicating nutritional compromise, is associated with decreased immune function and increased infection susceptibility, warranting closer monitoring and intervention(23). These results underscore the importance of targeted interventions in the antenatal period to mitigate risk factors associated with adverse pregnancy outcomes (16). The physiological adaptations of pregnancy (e.g., increased heart and respiratory rates) often overlap with Systemic Inflammatory Response Syndrome (SIRS) criteria, potentially limiting quick SOFA's reliability for sepsis diagnosis in gravid patients(24, 25). We therefore utilized the full SOFA score, which incorporates multi-organ assessment, to improve sepsis identification in our study population. Group B Streptococcus (GBS), a commensal bacterium in the urogenital and gastrointestinal tracts, is a leading cause of bacterial infections contributing to adverse outcomes in pregnant individuals, neonates, and infants(26). The absence of GBS in our etiological analysis may reflect the implementation of universal prenatal screening after 34 weeks of gestation and targeted intrapartum prophylaxis at our institution. The historical cohort design limits our ability to perform detailed, real-time analyses of moderating or mediating factors(27). 5 Conclusion This research enhances our understanding of infection patterns and sepsis risk factors across pregnancy stages. By identifying stage-specific pathogen distributions and significant risk factors (e.g., surgical procedures, anemia) and demonstrating that integrating anemia and hypoproteinemia screening into prenatal care improves early identification of high-risk parturient, we can develop more effective preventive and management strategies for perinatal sepsis. Abbreviations ICU Intensive care unit omSOFA Obstetric Modified Sequential Organ Failure Assessment CBC Complete blood count PCT Procalcitonin HIS Information System GDM Gestational diabetes mellitus OGTT Oral glucose tolerance test SOFA Sequential Organ Failure Assessment IQR Interquartile range GBS Group B Streptococcus SIRS Systemic Inflammatory Response Syndrome Declarations Ethics approval and consent to participate Obstetrics and Gynecology Intensive Care Unit, Gansu Maternal and Child Health Hospital (Gansu Provincial Center Hospital) provided approval for the study and consent forms (No. 47/2025/GSFY). Patient consent was waived due to historical cohort study design. All methods were performed in accordance with the relevant guidelines and regulations. Consent for publication All authors have read and agreed to the published version of the manuscript. Availability of data and materials The datasets used and/or analyzed during the current study are available from the the corresponding author on reasonable request. Competing interests The authors declare no conflict of interest. Funding Medical Innovation and Development Project of Lanzhou University, Grant Number: lzuyxcx-2022-137 Author Contributions Wang Mei and Wang Fang led the study design and analyzed data. Wang Mei data collected data and wrote the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable Authors' information Wang Mei, Ph.D. Candidate, Department of Obstetrics and Gynecology Intensive Care Unit, Gansu Provincial Maternal and Child Health Hospital (Gansu Provincial Central Hospital). Wang Fang, Ph.D. Supervisor, Center of Reproductive Medicine, The Second Hospital of Lanzhou University, Gansu Province. References Plante LA, Pacheco LD, Louis JM. SMFM Consult Series #47: Sepsis during pregnancy and the puerperium. Am J Obstet Gynecol. 2019;220(4):B2-b10. Giouleka S, Boureka E, Tsakiridis I, Lallas K, Papazisis G, Mamopoulos A, et al. Sepsis in Pregnancy and the Puerperium: A Comparative Review of Major Guidelines. Obstet Gynecol Surv. 2023;78(4):237-48. Escobar MF, Echavarría MP, Zambrano MA, Ramos I, Kusanovic JP. Maternal sepsis. Am J Obstet Gynecol MFM. 2020;2(3):100149. Burlinson CEG, Sirounis D, Walley KR, Chau A. Sepsis in pregnancy and the puerperium. Int J Obstet Anesth. 2018;36:96-107. Soma-Pillay P, Nelson-Piercy C, Tolppanen H, Mebazaa A. Physiological changes in pregnancy. Cardiovasc J Afr. 2016;27(2):89-94. Shields AD, Plante LA, Pacheco LD, Louis JM. Society for Maternal-Fetal Medicine Consult Series #67: Maternal sepsis. Am J Obstet Gynecol. 2023;229(3):B2-b19. Prabhu M, Wilkie G, MacEachern M, LaBuda D, Purtell J, Rao K, et al. Procalcitonin levels in pregnancy: A systematic review and meta-analysis of observational studies. Int J Gynaecol Obstet. 2023;163(2):484-94. Filetici N, Van de Velde M, Roofthooft E, Devroe S. Maternal sepsis. Best Pract Res Clin Anaesthesiol. 2022;36(1):165-77. Fleischmann-Struzek C, Mikolajetz A, Schwarzkopf D, Cohen J, Hartog CS, Pletz M, et al. Challenges in assessing the burden of sepsis and understanding the inequalities of sepsis outcomes between National Health Systems: secular trends in sepsis and infection incidence and mortality in Germany. Intensive Care Med. 2018;44(11):1826-35. Executive Summary: Surviving Sepsis Campaign: International Guidelines for the Management of Sepsis and Septic Shock 2021: Erratum. Crit Care Med. 2022;50(4):e413-e4. An H, Zheng W, Zhu Q, Chai Y. A retrospective study of risk factors for early-onset neonatal sepsis with intrapartum maternal fever. PeerJ. 2022;10:e13834. Rac H, Gould AP, Eiland LS, Griffin B, McLaughlin M, Stover KR, et al. Common Bacterial and Viral Infections: Review of Management in the Pregnant Patient. Ann Pharmacother. 2019;53(6):639-51. Cottreau JM, Barr VO. A Review of Antiviral and Antifungal Use and Safety during Pregnancy. Pharmacotherapy. 2016;36(6):668-78. Sacerdoti F, Scalise ML, Burdet J, Amaral MM, Franchi AM, Ibarra C. Shiga Toxin-Producing Escherichia coli Infections during Pregnancy. Microorganisms. 2018;6(4). Jonduo ME, Vallely LM, Wand H, Sweeney EL, Egli-Gany D, Kaldor J, et al. Adverse pregnancy and birth outcomes associated with Mycoplasma hominis, Ureaplasma urealyticum and Ureaplasma parvum: a systematic review and meta-analysis. BMJ Open. 2022;12(8):e062990. Shields A, de Assis V, Halscott T. Top 10 Pearls for the Recognition, Evaluation, and Management of Maternal Sepsis. Obstet Gynecol. 2021;138(2):289-304. DeBolt CA, Bianco A, Limaye MA, Silverstein J, Penfield CA, Roman AS, et al. Pregnant women with severe or critical coronavirus disease 2019 have increased composite morbidity compared with nonpregnant matched controls. Am J Obstet Gynecol. 2021;224(5):510.e1-.e12. Lipińska-Gediga M, Goździk W, Śmiechowicz J, Adamik B. Pregnancy and COVID-19: Comparing ICU Outcomes for Pregnant and Nonpregnant Women. Viruses. 2024;17(1). Kraus V, Jr., Čižmárová B, Birková A. Listeria in Pregnancy-The Forgotten Culprit. Microorganisms. 2024;12(10). Craig AM, Dotters-Katz S, Kuller JA, Thompson JL. Listeriosis in Pregnancy: A Review. Obstet Gynecol Surv. 2019;74(6):362-8. Escobar-Vidarte MF, Fernandez PA, Galindo JS, Valencia-Orozco A, Libreros-Peña L, Peña-Zarate EE, et al. Factors associated with infection-related severe maternal outcomes in pregnant and recently pregnant women: A secondary analysis of the WHO global maternal sepsis study. Int J Gynaecol Obstet. 2025;168(1):259-68. Holanda AMC, de Amorim MMR, Bezerra SMB, Aschoff LMS, Katz L. Risk factors for death in patients with sepsis admitted to an obstetric intensive care unit: A cohort study. Medicine (Baltimore). 2020;99(50):e23566. Cunningham HM, Knochenhauer HE, Federspiel JJ, Wein LE, Denoble AE, Heine RP, et al. Associations between Anemia and Outcomes of Pregnant Patients with Pyelonephritis. Am J Perinatol. 2024;41(S 01):e2403-e9. Serafim R, Gomes JA, Salluh J, Póvoa P. A Comparison of the Quick-SOFA and Systemic Inflammatory Response Syndrome Criteria for the Diagnosis of Sepsis and Prediction of Mortality: A Systematic Review and Meta-Analysis. Chest. 2018;153(3):646-55. Coopersmith CM, Antonelli M, Bauer SR, Deutschman CS, Evans LE, Ferrer R, et al. The Surviving Sepsis Campaign: Research Priorities for Coronavirus Disease 2019 in Critical Illness. Crit Care Med. 2021;49(4):598-622. Manuel G, Twentyman J, Noble K, Eastman AJ, Aronoff DM, Seepersaud R, et al. Group B streptococcal infections in pregnancy and early life. Clin Microbiol Rev. 2025;38(1):e0015422. Klebanoff MA, Snowden JM. Historical (retrospective) cohort studies and other epidemiologic study designs in perinatal research. Am J Obstet Gynecol. 2018;219(5):447-50. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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09:55:49","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":67366,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-6829609/v1/d3ae7b1ab3bef9d0930d6117.html"},{"id":91841523,"identity":"bd46970c-0b30-46c0-9470-cb3d9321f872","added_by":"auto","created_at":"2025-09-22 09:55:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":520277,"visible":true,"origin":"","legend":"\u003cp\u003ePathogen species distribution in different phases\u003c/p\u003e","description":"","filename":"Figure1PathogenSpeciesDistributioninDifferentPhases.png","url":"https://assets-eu.researchsquare.com/files/rs-6829609/v1/8465421a3b189c49c4af543f.png"},{"id":91841504,"identity":"7fda1884-b6b2-40df-aac4-5c3160cce5dc","added_by":"auto","created_at":"2025-09-22 09:55:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":709063,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of infection sites\u003c/p\u003e","description":"","filename":"Figure2DistributionofInfectionSitesAcrossPerinatalStages.png","url":"https://assets-eu.researchsquare.com/files/rs-6829609/v1/b65140becab108d450fcdb52.png"},{"id":91841541,"identity":"0b1eee5a-ec00-4755-a349-fdbfe90a29e2","added_by":"auto","created_at":"2025-09-22 09:56:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1219958,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution and relative abundance\u003c/p\u003e","description":"","filename":"Figure3DistributionandRelativeAbundanceofDifferentMicrobialCommunities.png","url":"https://assets-eu.researchsquare.com/files/rs-6829609/v1/b7dd2eaa2b8553d1bfa833b5.png"},{"id":108804271,"identity":"35535e39-e116-4f9e-a633-ae681e906419","added_by":"auto","created_at":"2026-05-08 15:18:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2925315,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6829609/v1/c923b8e2-d5e1-43f1-86dd-2099b79031f2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stage-Specific Pathogen and Risk Factors in Pregnancy, Parturition, and Puerperium: A Retrospective Cohort Study","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eMaternal sepsis, a life-threatening condition characterized by infection-induced organ dysfunction during pregnancy, childbirth, abortion, or the postpartum period (1), accounts for 11% of global maternal mortality(2, 3). Pregnant and postpartum women are particularly vulnerable to infections and subsequent sepsis, which represent major causes of intensive care unit (ICU) admissions and maternal deaths. The perinatal period involves unique immuno-physiological adaptations, including gestational immune modulation, hormonal fluctuations, and genitourinary tract changes, resulting in distinct susceptibility patterns across pregnancy, labor, and puerperium(4, 5). This evolving host microenvironment not only elevates infection risk but may also obscure clinical manifestations, leading to delayed diagnosis. These physiological alterations not only increase infection risk but may also mask typical clinical signs, potentially delaying diagnosis.\u003c/p\u003e\u003cp\u003e Although obstetric-specific early warning tools, such as the Obstetric Modified Sequential Organ Failure Assessment (omSOFA) and maternal sepsis management guidelines(2, 6), have been developed, maternal sepsis exhibits distinct physiological characteristics during pregnancy, parturition, and the puerperium, with variations in pathogenic microbiomes and infection sites across these stages. Further stage-specific research remains imperative.\u003c/p\u003e\u003cp\u003eTo address these limitations, we performed a historical cohort study combining clinical data analysis with microbial profiling and multivariable regression. This study aims to characterize perinatal stage-dependent risk factors for maternal sepsis.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cp\u003e\u003cb\u003eParticipants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis retrospective cohort study included patients admitted between January 1, 2020, and December 31, 2024, comprising: (1) pregnant women hospitalized with suspected infections, (2) women developing infections during parturition, and (3) puerperium women readmitted with suspected infections. All enrolled patients underwent microbiological culture testing from infection-related sites, including blood, sputum, urine, and secretion cultures. Exclusion criteria: (1) No use of antibiotics or antiviral agents, (2) Acute pancreatitis, and (3) Patients without pathogen testing or microbiological cultures. All specimens were collected following standardized procedures prior to antibiotic administration and immediately transported for laboratory analysis. Venous blood was concurrently drawn for complete blood count (CBC) and procalcitonin (PCT) testing.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData were extracted from the Hospital Information System (HIS), encompassing: (1) maternal baseline characteristics (age, gestational status at admission, and gestational age), (2) clinical features (comorbidities, involved infection systems, infection sites, and causative pathogens), (3) surgical interventions including cesarean section, ureteral stent placement, and wound debridement), (4) sepsis diagnosis coded according to ICD-10, and (5) concordance of antibiotic administration pre- and post-microbiological testing. Patient consent was waived due to historical cohort study design. Obstetrics and Gynecology Intensive Care Unit, Gansu Maternal and Child Health Hospital (Gansu Provincial Center Hospital) provided approval for the study and consent forms (No. 47/2025/GSFY).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDefinitions and participant classifications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eP5articipant in the study comprising: (1) pregnant women hospitalized with suspected infections, (2) women developing infections during parturition, and (3) puerperium women readmitted with suspected infections. Anemia was defined as a hemoglobin level less than 110 g/L. Hypoproteinemia was determined when serum albumin was below 30 g/L. Gestational diabetes mellitus (GDM) was diagnosed using the 75g oral glucose tolerance test (OGTT), with criteria of fasting plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;5.1 mmol/L, 1-hour plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;10.0 mmol/L, or 2-hour plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;8.5 mmol/L. According to the Sepsis-3.0 criteria, sepsis is diagnosed when an infection is present along with a Sequential Organ Failure Assessment (SOFA) score of \u0026ge;\u0026thinsp;2. Antibiotic consistency was categorized into two scenarios: (1) Concordant empirical therapy: initial antibiotic selection matched subsequent antimicrobial susceptibility testing results;(2) Discordant empirical therapy: discrepancies existed between the initial antibiotic regimen and antimicrobial susceptibility testing findings.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUsing EmpowerStats (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.empowerstats.com\u003c/span\u003e\u003cspan address=\"http://www.empowerstats.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and R 4.0.2 to analyze the data. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Categorical variables are presented as counts (n) and percentages (%). Normally distributed continuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while non-normally distributed variables are reported as median (M) with interquartile range (IQR; P25, P75). The Kruskal-Wallis rank-sum test was applied for continuous variables, and Fisher\u0026rsquo;s exact test was used for categorical variables with expected cell counts\u0026thinsp;\u0026lt;\u0026thinsp;10. Multivariable logistic regression models were employed to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for sepsis occurrence during pregnancy, parturition, and puerperium.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003eAmong the 242 initially screened maternal, 25 maternal with upper respiratory tract infections who did not receive antibiotic or antiviral medication, maternal with acute pancreatitis, and maternal without pathogen blood testing were excluded from analyses. Finally, 193 maternal were enrolled in the final analyses. The maternal was stratified into three groups based on perinatal stages: pregnancy group (n\u0026thinsp;=\u0026thinsp;32), parturition group (n\u0026thinsp;=\u0026thinsp;119), and puerperium group (n\u0026thinsp;=\u0026thinsp;42), with 28 cases (14.5%) diagnosed with sepsis. Significant intergroup differences in maternal age were observed (p\u0026thinsp;=\u0026thinsp;0.009), Absolute neutrophil counts showed phase-dependent variations (p\u0026thinsp;=\u0026thinsp;0.009), peaking during parturition (median 10.35\u0026times;10⁹/L, IQR 0.95\u0026ndash;29.46). Pathogen cultures revealed single-pathogen infections in 126 cases (65.3%), polymicrobial infections (\u0026ge;\u0026thinsp;2 pathogens) in 29 cases (15.1%), and no microbial growth in 38 cases (19.7%). Hypoproteinemia prevalence exhibited significant temporal heterogeneity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), occurring in 52.94% of parturition cases versus 15.62% in pregnancy and 30.95% in puerperium groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic Characteristics of Participant in the Study\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfection Time\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePregnancy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eParturition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePuerperium\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite blood cell (x 10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.09 (4.30-26.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.40 (1.78\u0026ndash;39.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e113.60 (2.92\u0026ndash;27.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHemoglobin (g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e105.40\u0026thinsp;\u0026plusmn;\u0026thinsp;23.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e104.52\u0026thinsp;\u0026plusmn;\u0026thinsp;22.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100.19\u0026thinsp;\u0026plusmn;\u0026thinsp;18.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.487\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphocyte percentage (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.35 (1.50\u0026ndash;37.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.20 (1.70\u0026ndash;41.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.30 (4.00-23.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.483\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil percentage (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.23\u0026thinsp;\u0026plusmn;\u0026thinsp;8.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.29\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e82.86\u0026thinsp;\u0026plusmn;\u0026thinsp;6.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.322\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLymphocyte absolute value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.08 (0.35\u0026ndash;5.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.21 (0.21\u0026ndash;10.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.29 (0.46\u0026ndash;3.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.868\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeutrophil absolute value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.57 (2.41\u0026ndash;24.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.35 (0.95\u0026ndash;29.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.77 (2.14\u0026ndash;26.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonocyte absolute value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.42 (0.02\u0026ndash;1.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.56 (0.01\u0026ndash;2.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.61 (0.03\u0026ndash;1.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.888\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC- reactive protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.77 (5.33-228.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.99 (2.00-244.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e84.59 (12.41\u0026ndash;202.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcalcitonin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.36 (0.02\u0026ndash;16.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.53 (0.09\u0026ndash;22.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.49 (0.11\u0026ndash;11.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.684\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplex Infection (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.615\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle microbial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (89.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75 (79.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24 (77.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTwo or more types of microbial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (10.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (20.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (22.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypoproteinemia (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (84.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56 (47.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29 (69.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (15.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63 (52.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (30.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnemia (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.798\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17 (53.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (48.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (45.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (46.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61 (51.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (54.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGestational diabetes mellitus (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (93.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101 (84.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42 (100.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (6.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (15.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCauses of infection (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.989\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot found\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (21.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (20.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (21.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBacteria\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (68.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82 (68.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29 (69.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViruses\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (9.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (9.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (7.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUngi or parasites\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (2.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSepsis (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (25.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (10.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (19.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (75.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107 (89.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (80.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe horizontal stacked bar chart in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows distinct pathogen distribution patterns across pregnancy, parturition, and puerperium phases. Bacterial pathogens demonstrated the highest prevalence, with peak concentrations observed during parturition, followed by puerperium and pregnancy phases. Viral infections showed moderate detection rates, exhibiting slightly higher incidence in pregnancy and parturition compared to puerperium. Fungal and parasitic infections displayed the lowest occurrence rates, with minimal detection across all phases. Cases without identified pathogens were categorized as \"no pathogen detected.\"\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe distribution of infection sites across perinatal stages (pregnancy, parturition, puerperium) is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, categorized into genital tract, respiratory, digestive, urinary, wound, breast, pelvic, and unknown locations. During pregnancy, overall infection rates were lowest, with predominant genital tract and respiratory infections, plus mild urinary tract involvement. A marked increase in infection rates occurred during parturition, particularly for genital tract infections which peaked at this stage, accompanied by significantly elevated respiratory infections. Although puerperium infection rates decreased from parturition levels, they remained higher than pregnancy baselines, with persistent predominance of genital tract infections and notable presence of urinary and wound infections.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe stacked area chart illustrates the distribution and relative abundance changes of different microbial communities across three physiological stages: pregnancy, parturition, and puerperium. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e exhibits the highest abundance during pregnancy, which significantly decreases postpartum. \u003cem\u003eEnterococcus faecalis\u003c/em\u003e and \u003cem\u003eMycoplasma\u003c/em\u003e are present at elevated levels during pregnancy, with a marked reduction during puerperium. Conversely, microbes specific to the puerperium, such as \u003cem\u003eEnterococcus faecalis\u003c/em\u003e and \u003cem\u003eMycoplasma\u003c/em\u003e, show an increased abundance during this period. Most other microbial groups, including COVID-19 virus, Influenza virus, \u003cem\u003eStreptococcus\u003c/em\u003e pneumoniae, \u003cem\u003eHaemophilus\u003c/em\u003e influenzae, \u003cem\u003eListeria\u003c/em\u003e monocytogenes, \u003cem\u003eMycobacterium\u003c/em\u003e tuberculosis, \u003cem\u003eStaphylococcus\u003c/em\u003e, and Other, maintain relatively low abundance across all stages.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe results from the Logistic regression model in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrate the odds ratios (OR) for the occurrence of sepsis during different stages of pregnancy. During the parturition period, age, complex infections, length of hospital stay, consistency of antibiotic use, anemia, hypoproteinemia, and surgical history were all significantly associated with the risk of sepsis, with hypoproteinemia and surgical history showing the most pronounced odds ratios of 5.72 (95% CI: 1.68, 19.54) and 6.87 (95% CI: 1.76, 26.74), respectively. In contrast to the pregnancy period, the risk of sepsis during the puerperium was lower. Although age, complex infections, anemia, and hypoproteinemia indicated a certain degree of increased risk (for instance, the odds ratio for anemia was 2.03 [95% CI: 0.61, 6.74]), none reached statistical significance.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociation between Various Factors and Sepsis during Pregnancy, Parturition, and Puerperium\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExposure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePregnancy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eParturition (OR, 95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePuerperium (OR, 95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.97 (1.10, 8.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.42 (0.47, 4.30)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlus age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.71 (0.98, 7.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.58 (0.51, 4.90)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlus complex infection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.66 (0.96, 7.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.55 (0.50, 4.83)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlus length of hospital stay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.88 (1.02, 8.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.64 (0.52, 5.20)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlus antibiotic use consistency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.76 (1.24, 11.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.96 (0.60, 6.42)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlus anemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.83 (1.26, 11.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.03 (0.61, 6.74)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlus hypoproteinemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.72 (1.68, 19.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.30 (0.67, 7.83)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePlus operation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.87 (1.76, 26.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.80 (0.71, 11.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eOur study provides insights into the stage-specific vulnerability to infections during the perinatal period and their link to sepsis risk. Procalcitonin levels, a reliable biomarker for identifying infections, showed no significant differences among the three patient groups and were comparable to non-pregnant adults, aligning with prior studies(7). Infection rates peak during parturition and remain high in the puerperium, necessitating targeted interventions during childbirth and postpartum care. Genital tract infections are common across stages, with urinary system infections rising during pregnancy and respiratory infections during parturition. The physiological changes of pregnancy, such as immunomodulation and anatomical alterations, increase infection susceptibility. Childbirth, particularly cesarean delivery, disrupts natural barriers, facilitating pathogen entry(3, 8). These patterns are influenced by physiological changes, medical interventions, and postpartum recovery challenges(9, 10).\u003c/p\u003e\u003cp\u003eThe distribution of pathogens across stages reflects the physiological and immunological changes during pregnancy and childbirth. Bacterial infections, especially from \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eEnterococcus faecalis\u003c/em\u003e, are predominant, suggesting enhanced screening and prophylaxis are needed(11, 12). The rise in \u003cem\u003efungal\u003c/em\u003e infections during the puerperium may relate to antibiotic and immunosuppressive therapy use(13). The area chart shows \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eEnterococcus faecalis\u003c/em\u003e are more abundant during pregnancy, likely due to immune and reproductive tract changes(14). \u003cem\u003eMycoplasma\u003c/em\u003e and \u003cem\u003eUreaplasma urealyticum\u003c/em\u003e peak during parturition, possibly due to childbirth stress and trauma(15). Clinicians must recognize the distinct etiologies of sepsis in peripartum and postpartum patients with suspected infection to guide timely, pathogen-specific therapy(16). An increased incidence of viral infections (e.g., influenza, SARS-CoV-2) among pregnant individuals may be linked to pregnancy-associated physiological changes that heighten susceptibility to respiratory pathogens, with the peripartum period conferring elevated risks of morbidity and disease severity(17, 18). \u003cem\u003eListeriosis\u003c/em\u003e, a severe foodborne infection vertically transmitted from mother to fetus, can lead to severe neonatal and maternal complications. Early diagnosis and antibiotic treatment are critical for optimizing maternal-fetal outcomes(19, 20). Other microbial groups remain at low levels, indicating they are less commonly involved in infections during these stages.\u003c/p\u003e\u003cp\u003ePrevious studies have identified that in pregnant women with suspected or confirmed infections, prior delivery history, hemorrhage, trauma, underlying medical conditions, as well as hospital-acquired or secondary infections serve as significant risk factors for severe adverse outcomes(21). Our study further revealed that inconsistent antibiotic use, anemia, hypoproteinemia, and surgical procedures constitute high-risk factors for maternal sepsis. Prolonged hospital stay increases exposure to nosocomial pathogens, highlighting the need for efficient care protocols. Identified risk factors offer valuable insights for clinical practice. Cesarean delivery, while sometimes necessary, should consider infection risks(22). Hypoproteinemia, indicating nutritional compromise, is associated with decreased immune function and increased infection susceptibility, warranting closer monitoring and intervention(23). These results underscore the importance of targeted interventions in the antenatal period to mitigate risk factors associated with adverse pregnancy outcomes (16).\u003c/p\u003e\u003cp\u003eThe physiological adaptations of pregnancy (e.g., increased heart and respiratory rates) often overlap with Systemic Inflammatory Response Syndrome (SIRS) criteria, potentially limiting quick SOFA's reliability for sepsis diagnosis in gravid patients(24, 25). We therefore utilized the full SOFA score, which incorporates multi-organ assessment, to improve sepsis identification in our study population. \u003cem\u003eGroup B Streptococcus\u003c/em\u003e (GBS), a commensal bacterium in the urogenital and gastrointestinal tracts, is a leading cause of bacterial infections contributing to adverse outcomes in pregnant individuals, neonates, and infants(26). The absence of GBS in our etiological analysis may reflect the implementation of universal prenatal screening after 34 weeks of gestation and targeted intrapartum prophylaxis at our institution. The historical cohort design limits our ability to perform detailed, real-time analyses of moderating or mediating factors(27).\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis research enhances our understanding of infection patterns and sepsis risk factors across pregnancy stages. By identifying stage-specific pathogen distributions and significant risk factors (e.g., surgical procedures, anemia) and demonstrating that integrating anemia and hypoproteinemia screening into prenatal care improves early identification of high-risk parturient, we can develop more effective preventive and management strategies for perinatal sepsis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eICU Intensive care unit\u003c/p\u003e\n\u003cp\u003eomSOFA Obstetric Modified Sequential Organ Failure Assessment\u003c/p\u003e\n\u003cp\u003eCBC Complete blood count\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePCT Procalcitonin\u003c/p\u003e\n\u003cp\u003eHIS Information System\u003c/p\u003e\n\u003cp\u003eGDM Gestational diabetes mellitus\u003c/p\u003e\n\u003cp\u003eOGTT Oral glucose tolerance test\u003c/p\u003e\n\u003cp\u003eSOFA Sequential Organ Failure Assessment\u003c/p\u003e\n\u003cp\u003eIQR Interquartile range\u003c/p\u003e\n\u003cp\u003eGBS Group B Streptococcus\u003c/p\u003e\n\u003cp\u003eSIRS Systemic Inflammatory Response Syndrome\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObstetrics and Gynecology Intensive Care Unit, Gansu Maternal and Child Health Hospital (Gansu Provincial Center Hospital) provided approval for the study and consent forms (No. 47/2025/GSFY). Patient consent was waived due to historical cohort study design. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the\u003c/p\u003e\n\u003cp\u003ethe corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMedical Innovation and Development Project of Lanzhou University, Grant Number: lzuyxcx-2022-137\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWang Mei and Wang Fang led the study design and analyzed data. Wang Mei data collected data and wrote the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWang Mei, Ph.D. Candidate, Department of Obstetrics and Gynecology Intensive Care Unit, Gansu Provincial Maternal and Child Health Hospital (Gansu Provincial Central Hospital).\u003c/p\u003e\n\u003cp\u003eWang Fang, Ph.D. Supervisor, Center of Reproductive Medicine, The Second Hospital of Lanzhou University, Gansu Province.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePlante LA, Pacheco LD, Louis JM. SMFM Consult Series #47: Sepsis during pregnancy and the puerperium. Am J Obstet Gynecol. 2019;220(4):B2-b10.\u003c/li\u003e\n\u003cli\u003eGiouleka S, Boureka E, Tsakiridis I, Lallas K, Papazisis G, Mamopoulos A, et al. Sepsis in Pregnancy and the Puerperium: A Comparative Review of Major Guidelines. Obstet Gynecol Surv. 2023;78(4):237-48.\u003c/li\u003e\n\u003cli\u003eEscobar MF, Echavarr\u0026iacute;a MP, Zambrano MA, Ramos I, Kusanovic JP. Maternal sepsis. Am J Obstet Gynecol MFM. 2020;2(3):100149.\u003c/li\u003e\n\u003cli\u003eBurlinson CEG, Sirounis D, Walley KR, Chau A. Sepsis in pregnancy and the puerperium. Int J Obstet Anesth. 2018;36:96-107.\u003c/li\u003e\n\u003cli\u003eSoma-Pillay P, Nelson-Piercy C, Tolppanen H, Mebazaa A. Physiological changes in pregnancy. Cardiovasc J Afr. 2016;27(2):89-94.\u003c/li\u003e\n\u003cli\u003eShields AD, Plante LA, Pacheco LD, Louis JM. Society for Maternal-Fetal Medicine Consult Series #67: Maternal sepsis. Am J Obstet Gynecol. 2023;229(3):B2-b19.\u003c/li\u003e\n\u003cli\u003ePrabhu M, Wilkie G, MacEachern M, LaBuda D, Purtell J, Rao K, et al. Procalcitonin levels in pregnancy: A systematic review and meta-analysis of observational studies. Int J Gynaecol Obstet. 2023;163(2):484-94.\u003c/li\u003e\n\u003cli\u003eFiletici N, Van de Velde M, Roofthooft E, Devroe S. Maternal sepsis. Best Pract Res Clin Anaesthesiol. 2022;36(1):165-77.\u003c/li\u003e\n\u003cli\u003eFleischmann-Struzek C, Mikolajetz A, Schwarzkopf D, Cohen J, Hartog CS, Pletz M, et al. Challenges in assessing the burden of sepsis and understanding the inequalities of sepsis outcomes between National Health Systems: secular trends in sepsis and infection incidence and mortality in Germany. Intensive Care Med. 2018;44(11):1826-35.\u003c/li\u003e\n\u003cli\u003eExecutive Summary: Surviving Sepsis Campaign: International Guidelines for the Management of Sepsis and Septic Shock 2021: Erratum. Crit Care Med. 2022;50(4):e413-e4.\u003c/li\u003e\n\u003cli\u003eAn H, Zheng W, Zhu Q, Chai Y. A retrospective study of risk factors for early-onset neonatal sepsis with intrapartum maternal fever. PeerJ. 2022;10:e13834.\u003c/li\u003e\n\u003cli\u003eRac H, Gould AP, Eiland LS, Griffin B, McLaughlin M, Stover KR, et al. Common Bacterial and Viral Infections: Review of Management in the Pregnant Patient. Ann Pharmacother. 2019;53(6):639-51.\u003c/li\u003e\n\u003cli\u003eCottreau JM, Barr VO. A Review of Antiviral and Antifungal Use and Safety during Pregnancy. Pharmacotherapy. 2016;36(6):668-78.\u003c/li\u003e\n\u003cli\u003eSacerdoti F, Scalise ML, Burdet J, Amaral MM, Franchi AM, Ibarra C. Shiga Toxin-Producing Escherichia coli Infections during Pregnancy. Microorganisms. 2018;6(4).\u003c/li\u003e\n\u003cli\u003eJonduo ME, Vallely LM, Wand H, Sweeney EL, Egli-Gany D, Kaldor J, et al. Adverse pregnancy and birth outcomes associated with Mycoplasma hominis, Ureaplasma urealyticum and Ureaplasma parvum: a systematic review and meta-analysis. BMJ Open. 2022;12(8):e062990.\u003c/li\u003e\n\u003cli\u003eShields A, de Assis V, Halscott T. Top 10 Pearls for the Recognition, Evaluation, and Management of Maternal Sepsis. Obstet Gynecol. 2021;138(2):289-304.\u003c/li\u003e\n\u003cli\u003eDeBolt CA, Bianco A, Limaye MA, Silverstein J, Penfield CA, Roman AS, et al. Pregnant women with severe or critical coronavirus disease 2019 have increased composite morbidity compared with nonpregnant matched controls. Am J Obstet Gynecol. 2021;224(5):510.e1-.e12.\u003c/li\u003e\n\u003cli\u003eLipińska-Gediga M, Goździk W, Śmiechowicz J, Adamik B. Pregnancy and COVID-19: Comparing ICU Outcomes for Pregnant and Nonpregnant Women. Viruses. 2024;17(1).\u003c/li\u003e\n\u003cli\u003eKraus V, Jr., Čižm\u0026aacute;rov\u0026aacute; B, Birkov\u0026aacute; A. Listeria in Pregnancy-The Forgotten Culprit. Microorganisms. 2024;12(10).\u003c/li\u003e\n\u003cli\u003eCraig AM, Dotters-Katz S, Kuller JA, Thompson JL. Listeriosis in Pregnancy: A Review. Obstet Gynecol Surv. 2019;74(6):362-8.\u003c/li\u003e\n\u003cli\u003eEscobar-Vidarte MF, Fernandez PA, Galindo JS, Valencia-Orozco A, Libreros-Pe\u0026ntilde;a L, Pe\u0026ntilde;a-Zarate EE, et al. Factors associated with infection-related severe maternal outcomes in pregnant and recently pregnant women: A secondary analysis of the WHO global maternal sepsis study. Int J Gynaecol Obstet. 2025;168(1):259-68.\u003c/li\u003e\n\u003cli\u003eHolanda AMC, de Amorim MMR, Bezerra SMB, Aschoff LMS, Katz L. Risk factors for death in patients with sepsis admitted to an obstetric intensive care unit: A cohort study. Medicine (Baltimore). 2020;99(50):e23566.\u003c/li\u003e\n\u003cli\u003eCunningham HM, Knochenhauer HE, Federspiel JJ, Wein LE, Denoble AE, Heine RP, et al. Associations between Anemia and Outcomes of Pregnant Patients with Pyelonephritis. Am J Perinatol. 2024;41(S 01):e2403-e9.\u003c/li\u003e\n\u003cli\u003eSerafim R, Gomes JA, Salluh J, P\u0026oacute;voa P. A Comparison of the Quick-SOFA and Systemic Inflammatory Response Syndrome Criteria for the Diagnosis of Sepsis and Prediction of Mortality: A Systematic Review and Meta-Analysis. Chest. 2018;153(3):646-55.\u003c/li\u003e\n\u003cli\u003eCoopersmith CM, Antonelli M, Bauer SR, Deutschman CS, Evans LE, Ferrer R, et al. The Surviving Sepsis Campaign: Research Priorities for Coronavirus Disease 2019 in Critical Illness. Crit Care Med. 2021;49(4):598-622.\u003c/li\u003e\n\u003cli\u003eManuel G, Twentyman J, Noble K, Eastman AJ, Aronoff DM, Seepersaud R, et al. Group B streptococcal infections in pregnancy and early life. Clin Microbiol Rev. 2025;38(1):e0015422.\u003c/li\u003e\n\u003cli\u003eKlebanoff MA, Snowden JM. Historical (retrospective) cohort studies and other epidemiologic study designs in perinatal research. Am J Obstet Gynecol. 2018;219(5):447-50.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sepsis, Pregnancy, Parturition, Puerperium","lastPublishedDoi":"10.21203/rs.3.rs-6829609/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6829609/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eMaternal sepsis remains a leading cause of pregnancy-related morbidity and mortality. Physiological adaptations during gestation complicate early sepsis recognition, while delayed source control exacerbates risks. Stage-specific variations in pathogen and modifiable risk factors have not been adequately studied.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis retrospective cohort study analyzed pathogen profiles and infection systems in pregnany, perinatal, and puerperal patients undergoing pathogen testing at Gansu Provincial Maternal and Child Health Hospital from January 2020 to December 2024. Logistic regression was used to identify risk factors, with unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) reported.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 193 maternal were included, with 28 cases of sepsis and 165 non-sepsis cases. Bacterial pathogens dominate in perinatal stages, peaking at parturition. Maternal infection sites exhibited a distinct perinatal pattern: the lowest rates occurred during pregnancy (predominantly genital, respiratory, and urinary tract infections), peaked in the perinatal period (primarily genital and respiratory infections), and declined during the puerperium (with genital infections and newly emerging urinary tract and surgical site infections). Specific like \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eEnterococcus faecalis\u003c/em\u003e, and \u003cem\u003eMycoplasma\u003c/em\u003e show stage-specific abundance changes. During perinatal, several factors were significantly associated with an increased risk of sepsis. Notably, maternal operation was strongly associated with sepsis (OR\u0026thinsp;=\u0026thinsp;6.87, 95% CI: 1.76\u0026ndash;26.74), Additionally, maternal anemia (OR\u0026thinsp;=\u0026thinsp;3.83, 95% CI: 1.26\u0026ndash;11.67) and hypoproteinemia (OR\u0026thinsp;=\u0026thinsp;5.72, 95% CI: 1.68\u0026ndash;19.54) were also significantly linked to higher odds of sepsis.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eMaternal sepsis demonstrates distinct stage-specific microbial, with bacterial dominance and genital tract infections surging during perinatal. Hypoproteinemia, anemia, and surgical history are critical modifiable risk factors, underscoring the need for targeted interventions during high-risk perinatal phases.\u003c/p\u003e","manuscriptTitle":"Stage-Specific Pathogen and Risk Factors in Pregnancy, Parturition, and Puerperium: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 09:54:31","doi":"10.21203/rs.3.rs-6829609/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fe684dc3-094d-4237-a429-0ed0ca2b6d5f","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T13:27:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 09:54:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6829609","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6829609","identity":"rs-6829609","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}