Essential Site Maintenance: Authorea-powered sites will be updated circa 15:00-17:00 Eastern on Tuesday 5 November.
There should be no interruption to normal services, but please contact us at [email protected] in case you face any issues.

loading page

Predicting Postpartum Haemorrhage: A systematic review of prognostic models
  • +3
  • Bethany Carr,
  • Maryam Jahangirifar,
  • Ann Nicholson,
  • Ben Mol,
  • Wentao Li,
  • Sharon Licqurish
Bethany Carr
Monash University

Corresponding Author:[email protected]

Author Profile
Maryam Jahangirifar
Monash University
Author Profile
Ann Nicholson
Monash University
Author Profile
Ben Mol
Monash University Faculty of Medicine Nursing and Health Sciences
Author Profile
Wentao Li
Monash University
Author Profile
Sharon Licqurish
Monash Centre for Health Research and Implementation
Author Profile

Abstract

Background: Postpartum Haemorrhage (PPH) remains a leading cause of maternal mortality and morbidity worldwide, and the rate is increasing. Using a reliable predictive model could identify those at risk, support management and treatment, and improve maternal outcomes. Objectives: To systematically identify and appraise existing prognostic models for PPH and ascertain suitability for clinical use. Search strategy: MEDLINE, CINAHL, Embase, and the Cochrane Library were searched using combinations of terms and synonyms including ‘postpartum haemorrhage’, ‘prognostic model’, and ‘risk factors’ that were developed from a scoping review. Selection Criteria: Observational or experimental studies describing a prognostic model for risk of PPH, published in English. Data Collection and Analysis: The Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist informed data extraction and Prediction Model Risk of Bias Assessment Tool guided analysis. Main Results: 16 studies met the inclusion criteria after screening 1612 records. All studies were hospital settings from 8 different countries. Models were developed for women who experienced vaginal birth (n=7), caesarean birth(n=2), any type of birth(n=2), hypertensive disorders(n=1) and those with placental abnormalities(n=4). All studies were at high risk of bias due to use of inappropriate analysis methods or omission of important statistical considerations or suboptimal validation. Conclusions: No existing prognostic models for PPH are ready for clinical application. Future research is needed to externally validate existing models and potentially develop a new model that is reliable and applicable to clinical practice. Funding: This study received no funding. Keywords: Postpartum haemorrhage, prognostic model, prediction tool.
02 Aug 2022Published in Australian and New Zealand Journal of Obstetrics and Gynaecology. 10.1111/ajo.13599