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Development and validation of a predictive model for septic shock in maternal sepsis: a retrospective cohort study in a single referral center

  • Xin Lyu,
  • Siying Chen,
  • Haoting Shi,
  • Shibin Hong,
  • Meng Jiang,
  • Chang Liu,
  • Chuan Wang,
  • Ning Zhang

摘要

Objectives

Maternal sepsis carries a high risk of progression to septic shock. However, existing risk stratification tools, such as qSOFA and the Sepsis in Obstetrics Score, perform suboptimally in pregnant and postpartum populations, and no simple model specifically predicts progression from sepsis to septic shock. This study aimed to identify variables associated with septic shock in maternal sepsis, characterize infection sources and pathogens, and develop and internally validate a practical predictive model.

Methods

A retrospective cohort study was conducted on 139 pregnant and postpartum women with sepsis admitted to a single tertiary center between January 2016 and July 2025. The primary outcome was septic shock within 72 h of sepsis diagnosis, and predictors were collected at the time of diagnosis. Patients were randomly split into training (70%) and validation (30%) cohorts. Predictors were first screened using univariate robust Poisson regression, followed by LASSO regression for feature selection. The final predictive model was fitted using multivariable robust Poisson regression. Model performance was assessed using the area under the receiver-operating-characteristic curve, calibration plots, and decision curve analyses (DCA).

Results

Four independent predictors for septic shock were identified: history of surgery during pregnancy, prothrombin time (PT), procalcitonin (PCT), and arterial partial pressure of oxygen (PaO₂). The model exhibited good discrimination in the training cohort (Area-under-curve [AUC] 0.87, 95% CI: 0.80–0.94) and validation cohort (AUC 0.87, 95% CI: 0.75–0.99), with good calibration and clinical utility. Higher risk scores were significantly associated with adverse maternal and neonatal outcomes. Respiratory infections were the most common source (44.6%), followed by genitourinary (30.9%) and gastrointestinal infections (12.9%). Gram-negative bacteria (55.1%) were the main pathogens. Septic shock occurred more frequently in puerperal sepsis than in pregnancy-onset sepsis (43.3% vs. 19.0%, p = 0.003).

Conclusion

A four-variable model using readily available clinical parameters demonstrated favorable predictive performance for predicting septic shock in maternal sepsis and was associated with adverse perinatal outcomes. This tool may support early risk stratification and clinical decision-making, pending future prospective external validation.