Risk-Stratified Predictive Models of Pregnancy Loss
https://doi.org/10.31631/2073-3046-2025-24-3-83-93
Abstract
Relevance. Given the substantial prevalence of pregnancy loss (20-46 % of conceptions), there is an urgent need to establish risk-prediction models for miscarriage to facilitate targeted preventive interventions.
Aim. To identify predictors of miscarriage and to develop prognostic models of miscarriage development based on risk assessment.
Materials and methods. We conducted a case-control study involving 282 women: 152 cases of spontaneous pregnancy loss (≤21 weeks gestation) and 130 controls with term deliveries. The assessment protocol included: a standardized 77-item questionnaire, validated Russian version of the Perinatal Anxiety Screening Scale (PASS-R, 31 items). Laboratory analyses comprised: molecular biological methods: quantitative PCR analysis of vaginal microbiota, microbiological assays: oropharyngeal swabs with semi-quantitative microbial growth assessment, fecal bacteriological examination for dysbiosis. Statistical analysis was performed using R software (v4.3.1), incorporating: univariate and multivariate logistic regression, ROC curve analysis (AUC) for model performance evaluation.
Results and discussion. Multivariate analysis identified statistically significant predictors of pregnancy loss, enabling development of two predictive mathematical models with strong discriminatory capacity. Key risk factors included: socio-demographic predictors (maternal age ≥35 years (aOR = 11.1; 95 %CI:1.46–238; p = 0.043), leadership occupation (OR = 8.92; 95 %CI:2.93–31.6; p < 0.001). Protective factor: normal body mass index (18.6–25 kg/m2; OR = 0.03; 95 % CI:0.001–0.32; p = 0.008). Clinical-anamnestic factors: medically indicated abortion history (OR = 8.07; 95 % CI:1.50–55.8; p = 0.021), smoking during pregnancy (OR = 6.06; 95 % CI:1.45–33.4; p = 0.022). Microbiological markers: severe intestinal dysbiosis (OR = 9.51; 95 % CI:2.37–64.7; p = 0.005). The developed models demonstrated excellent predictive performance, with high sensitivity and specificity (AUC 0.86 and 0.79).
Conclusion. The developed pregnancy loss risk prediction models, incorporating comprehensive socio-demographic, clinical, and microbiological predictors, demonstrate high specificity for spontaneous abortion risk stratification (AUC 0.861 and 0.790). These models show potential for refinement, validation, and eventual clinical implementation.
About the Authors
O. V. Shirai
St. Elizabeth City Hospital
Russian Federation
Russian Federation
Olga V. Shirai – Head of the Department-Epidemiologist
4, Vavilov street, Saint Petersburg, 195257
+7 (931) 213-83-94
B. I. Aslanov
North West State Medical University named after I.I. Mechnikov
Russian Federation
Russian Federation
Batyrbek I. Aslanov – Dr. Sci. (Med.), Professor Head of department Epidemiology, Parasitology and Disinfectology
Saint Petersburg
S. V. Rishchuk
North West State Medical University named after I.I. Mechnikov
Russian Federation
Russian Federation
Sergey V. Rishchuk – Dr. Sci. (Med.), associate professor, professor of Department Obstetrics and Gynecology named after S.N. Davydov
Saint Petersburg
S. E. Melnikova
North West State Medical University named after I.I. Mechnikov
Russian Federation
Russian Federation
Svetlana E. Melnikova – Cand. Sci. (Med.), Associate Professor of Department Obstetrics and Gynecology named after S.N. Davydov
Saint Petersburg
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Review
For citations:
Shirai O.V., Aslanov B.I., Rishchuk S.V., Melnikova S.E. Risk-Stratified Predictive Models of Pregnancy Loss. Epidemiology and Vaccinal Prevention. 2025;24(3):83-93. (In Russ.) https://doi.org/10.31631/2073-3046-2025-24-3-83-93
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