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.