作者
Kehinde S Okunade, Aloy O Ugwu, Muisi A Adenekan, Ayokunle Olumodeji, Yusuf A Oshodi, Temitope Ojo, Adebola A Adejimi, Iyabo Y Ademuyiwa, Victoria Adaramoye, Austin C Okoro, Atinuke Olowe, Olukayode O Akinmola, Sarah O John‐Olabode, Hameed Adelabu, Rodrigo Henriquez, Tom Decroo, Lutgarde Lynen
发表日期
2024/1/17
期刊
International Journal of Gynecology & Obstetrics
简介
Objectives
There is currently a limited ability to accurately identify women at risk of postpartum hemorrhage (PPH). We conducted the “Predict‐PPH” study to develop and evaluate an antepartum prediction model and its derived risk‐scoring system.
Methods
This was a prospective cohort study of healthy pregnant women who registered and gave birth in five hospitals in Lagos, Nigeria, from January to June 2023. Maternal antepartum characteristics were compared between women with and without PPH. A predictive multivariable model was estimated using binary logistic regression with a backward stepwise approach eliminating variables when P was greater than 0.10. Statistically significant associations in the final model were reported when P was less than 0.05.
Results
The prevalence of PPH in the enrolled cohort was 37.1%. Independent predictors of PPH such as maternal obesity (adjusted odds ratio …
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KS Okunade, AO Ugwu, MA Adenekan, A Olumodeji… - International Journal of Gynecology & Obstetrics, 2024