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BMC pregnancy and childbirth · 2025

The intersection of cervicovaginal microbiota and cervical length in predicting adverse perinatal outcomes at preterm birth risk.

СтатьяНазвание и аннотация: Перевод в очереди
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Okutucu Gulcan, Tanacan Atakan, Bayraktar Nazli, Ozdal Burcu Bozkurt, Babayigit Eda Busra, Dinc Bedia, Kara Ozgur, Sahin Dilek

Аннотация

AIM: To evaluate the cervicovaginal (CV) microbiota in pregnant women with conditions increasing the risk of preterm labor and to assess the relationship between pathogenic microorganism growth in CV cultures and composite adverse perinatal outcomes (CAPO).

METHODS: A total of 665 CV culture results from pregnant women hospitalized for threatened preterm labor (TPL), preterm premature rupture of membranes (PPROM), or cervical insufficiency (CIS) without other obstetric complications were included. Culture results were divided into three groups according to the dominant microorganism type: normal (Lactobacillus spp. dominated), candidal, and bacterial cervicovaginal flora (CVF). CAPO were defined as the presence of perinatal mortality alone or the occurrence of at least two of the following neonatal complications: neonatal sepsis, transient tachypnea of the newborn, respiratory distress syndrome, intracranial or intraventricular hemorrhage, and umbilical cord arterial pH < 7.1.

RESULTS: Of the cultures, 431 (64.8%) were normal, and 234 (35.2%) were non-normal CVFs. Indications for hospitalization were TPL (n = 387, 58.2%), CIS (n = 172, 25.9%), and PPROM (n = 106, 15.9%). Bacterial CVFs had the highest rate of preterm birth (p = 0.024) and CAPO (52.5%, p = 0.021), as well as the lowest birth weight (p = 0.011). The optimal cut-off value for cervical length (CxL) to predict CAPO in the presence of non-normal CVFs was determined 28.5 mm, with a sensitivity of 70.7% and specificity of 71.1% (AUC: 0.763, p < 0.001).

CONCLUSIONS: Monitoring CxL and determining bacterial predominance in CVF in women at risk of preterm delivery may help predict adverse perinatal outcomes and provide insight for better obstetric management and intervention.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты