Prediction of postpartum endometritis in women after vaginal birth

Introduction. About 5 million postpartum infectious complications are recorded annually, and about 75 thousand of them lead to maternal death.

Aim. To create predictive model founded on binary logistic regression which could help to diagnosis postpartum endometritis in women after vaginal delivery, based on analyses of links between anamnesis data, anthropometric indicators and risk of postpartum endometritis in postpartum women in modern mega policy.

Material and methods. We conducted a retrospective cohort study, analysis of the 61 medical histories or the postpartum patient admitted to the gynecological department of a state medical institution in Moscow since 2019 to 2021 year was carried out with “Postpartum endometritis” and analysis of history of 70 birth history of postpartum women after physiological labor in different maternity hospital in Moscow.

Results. Patient with postpartum endometritis statistically significant greater have overweight (р = 0,015), dental caries (р = 0,000), vaginitis (р = 0,000), first pregnancy (p = 0,025) and the next complications of pregnancy: acute respiratory viral infections (ARVI) (p = 0,010), urinary tract infections (p = 0,015), gestational diabetes (p = 0,013), inflammatory diseases of vagina and vulva (p = 0,008). They have statistically significant greater induction of labor (p = 0,000) and greater blood loss (p = 0,001).

Conclusions. Predictive model is statistically significant, has 87,1% specifity and 86,9% sensitivity. It allows to prognose postpartum endometritis after vaginal birth.

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