Predicting postpartum hemorrhage (PPH) during cesarean delivery using the Leicester PPH Predict tool: a retrospective cohort study.

Objective: The aim of the present study was to develop a toolkit combining various risk factors to predict the risk of developing a postpartum hemorrhage (PPH) during a cesarean section. Study Design: A retrospective cohort study of 24,230 women who had cesarean delivery between January 2003 and December 2013 at a tertiary care teaching ho spital within the United Kingdom serving a multi-ethnic population. Data was extracted from hospital databases and risk factors for PPH were identified. Hothorn et al.s Recursive Partitioning algorithm was used to infer a conditional decision tree. For each of the identified combinations of risk factors two probabilities were calculated: the probability of a patient pro ducing 1000ml blood loss and 2000ml blood loss. Results: The Leicester PPH Predict Score was then tested on the randomly s elected remaining 25% (n=6095) of the data for internal validity. Reliability te sting showed intraclass correlation of 0.98 and mean absolute error 239.8ml with the actual outcome. Conclusion: The proposed toolkit, which is available online, enables clinicians to predict the risk of postpartum hemorrhage. As a result, preventative measures f or postpartum hemorrhage could be undertaken. Further external validation of the current toolkit is required.