Introduction

Postpartum haemorrhage (PPH) remains a leading cause of morbidity and mortality globally, and was the second highest cause of direct maternal death in the UK 2013-2015.
The incidence of PPH is problematic in developing countries but is also noted to be increasing in developed countries., While early diagnosis is essential in the management of PPH, diagnosis of PPH itself presents a challenge due to the reliance upon quantification of the volume of blood loss. For vaginal delivery, cut-offs for haemorrhage are typically over 500ml of blood loss whilst for caesarean section (CS) it is over 1000ml.
Prevention of PPH could arise through identification of women at highest risk, allowing for measures to be taken for active management of third stage of labour, presence of experienced clinicians and immediate access to resources such as oxytocin infusion and tranexamic acid. There are numerous studies identifying individual risk factors for PPH but these don’t reliably identify women at greatest risk by combining multiple risk factors. A combination of risk factors is common in practice but quantifying the associated risk without the aid of a clinical prediction model is challenging. Once a reliable and high performing prediction model is developed this could be converted into a user-friendly tool such as an online risk calculator or embedded within electronic health records.
A review by Kleinroueler et al., 2015 found over 200 prognostic models available in obstetrics, three of which related to PPH. The review found very few models in any area of obstetrics that were being applied to routine clinical practice and the majority of studies had not presented model formulas to allow researchers to conduct independent external validation of the models.
In order to progress efforts to identify women at risk of PPH as early and as accurately as possible, a systematic review of existing prognostic models was considered essential. This would enable assessment of existing models for their suitability for immediate use, or identify those which perform well internally but require external validation on an independent cohort before being considered for clinical use. This approach has potential to be more efficient than the addition of a new model to aid prevention of PPH.
Since publication of the aforementioned review several attempts at developing prognostic models for PPH have been published. This review aims to systematically identify and appraise studies which develop prognostic models that can predict the chance of PPH in pregnant women.