https://www.selleckchem.com/pr....oducts/ly3214996.htm
1% of these cases (odds ratio 5.3, 95% CI 4.7-6.0; high-risk versus low-risk groups). Data acquired throughout the first stage of labour can be used to predict SANO during the second stage of labour using a machine learning model. Stratifying parturients at the beginning of the second stage of labour in a 'time out' session, can direct a personalised approach to management of this challenging aspect of labour, as well as improve allocation of staff and resources. Personalised prediction score for severe adverse neonatal outcomes in la