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Updated: Feb 24, 2026
An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
Published on: January 27, 2010
Predicting Postpartum Hemorrhage (PPH) during Cesarean Delivery Using the Leicester PPH Predict Tool: A Retrospective
Suzanna E Dunkerton1, Yadava B Jeve1, Neil Walkinshaw2
1Department of Obstetrics and Gynecology, University Hospitals of Leicester, Leicester, United Kingdom.
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 delivery.
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 hospital within the United Kingdom serving a multiethnic population. Data were extracted from hospital databases, and risk factors for PPH were identified. Hothorn et al 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 producing ≥1,000 and ≥ 2,000 mL blood loss.
Results:
The Leicester PPH predict score was then tested on the randomly selected remaining 25% (n = 6,095) of the data for internal validity. Reliability testing showed an intraclass correlation of 0.98 and mean absolute error of 239.8 mL with the actual outcome.
Conclusion:
The proposed toolkit enables clinicians to predict the risk of postpartum hemorrhage. As a result, preventative measures for postpartum hemorrhage could be undertaken. Further external validation of the current toolkit is required.
