Charlotte Neary

and 3 more

Background: Postpartum haemorrhage (PPH) rates are increasing in developed countries. A reliable prognostic tool for PPH has potential to aid prevention efforts. Objective: To systematically identify and appraise prognostic modelling studies for prediction of PPH. Search strategy: MEDLINE, Embase, CINAHL and the Cochrane Library were searched using a combination of terms and synonyms including ‘prediction tool’, ‘risk score’ and ‘postpartum haemorrhage’. Selection criteria: Any observational or experimental study developing a prognostic model for women’s risk of PPH. English language publications. Data collection and analysis: Predesigned data extraction form to record: data source; participant criteria; outcome; candidate predictors; actual predictors; sample size; missing data; model development; model performance; model evaluation; interpretation. Main Results: Of 1723 citations screened, 10 studies were eligible for inclusion. An additional paper was published and identified following completion of the search. Studies addressed populations of women who experienced; placenta praevia; vaginal births; caesarean birth; and the general obstetric population. Primary study authors deemed four models to be confirmatory. There was a high risk of bias across all studies due to a combination of retrospective selection of women, low sample size, no internal validation, suboptimal external validation and no reporting of missing data. Conclusion: Of eleven prognostic models for PPH risk, one developed for women undergoing caesarean section is deemed suitable for external validation. Future research requires robust internal and external validation of existing tools and development of a model that can be used to predict PPH in the general obstetric population. Protocol registration number: PROSPERO 95587