PB1511 - Systematic review on hemostatic biomarkers predictive for postpartum hemorrhage

Tuesday, June 27, 2023

18:30 – 19:30 ET

Room: Exhibition

Presenting Author(s)

Claire de Moreuil, MD,PhD (she/her/hers)

Hospital Practioner in Internal Medicine
Internal medicine and Pneumology Department, Brest University Hospital, UMR 1304, GETBO
BREST, Bretagne, France

Co-Author(s)

Dino Mehic, MD

Resident physician
Clinical Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
Vienna, Wien, Austria
Stephan Nopp, MD

PhD Student
Clinical Division of Haematology and Haemostaseology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
Vienna, Wien, Austria
Daniel Kraemmer, MD (he/him/his)

PhD Student
Department of Medicine I, Clinical Division of Haematology and Haemostaseology; Medical University of Vienna, Vienna, Austria
Vienna, Wien, Austria
Johanna Gebhart, MD, PhD (she/her/hers)

Ap. Prof. Dr. PhD
Clinical Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
Vienna, Wien, Austria
Theresa Schramm, MSc

PhD Student
Department of Medicine I, Clinical Division of Haematology and Haemostaseology; Medical University of Vienna, Vienna, Austria
Vienna, Wien, Austria
Francis Couturaud, PhD (he/him/his)

MD, PhD
Centre Hospitalo-Universitaire de Brest, Département de Médecine Interne et Pneumologie, INSERM U1304, CIC INSERM 1412, Univ_Brest, Brest, FCRIN INNOVTE, France.
Brest, Bretagne, France
Cihan Ay, MD (he/him/his)

Professor, Head of the Thrombosis and Haemostasis Research Group
Clinical Division of Haematology and Haemostaseology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
Vienna, Wien, Austria
Ingrid Pabinger, MD

Co-Head of the Thrombosis and Haemostasis Research Group
Clinical Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
Vienna, Wien, Austria

Background: Postpartum hemorrhage (PPH) remains a leading cause of maternal morbi-mortality. Obstetric risk factors have been described, however, the impact of hemostatic biomarkers obtained predelivery are still incompletely understood.

Aims: In this systematic review, we aimed to summarize the current literature on the association between predelivery hemostatic biomarkers and PPH or severe PPH.

Methods: We searched the following electronic databases from inception to October 2022: MEDLINE, EMBASE, and CENTRAL. Two review authors (CDM, DM) independently performed title, abstract, and full-text screening. Observational studies on unselected pregnant women without known bleeding disorder, reporting on PPH and on predelivery hemostatic biomarkers, were included. A quantitative synthesis of studies reporting on the same hemostatic biomarker was conducted, calculating mean differences (MD) between women with PPH/severe PPH and controls. We fitted a random-effects model to the data, computing tests and 95% confidence intervals (95%CI) with the Knapp and Hartung method.

Results: Search of databases on 18 October 2022 yielded 76 articles fitting our inclusion criteria (Figure 1). The heterogeneity between studies was considerable. With regard to PPH in general, average MD in investigated biomarkers (platelets, fibrinogen, hemoglobin, D-Dimer, aPTT, PT) were not statistically significant. Women who developed severe PPH had a lower predelivery platelet count than controls (MD = - 26.0 G/L; 95%CI -35.8, -16.1, 4 studies), whereas difference in predelivery fibrinogen concentration (MD = -0.31 g/L; 95%CI -0.75, 0.13) or hemoglobin level (- 0.25 g/dL; 95%CI -4.36, 3.85) did not reach statistical significance (Figure 2). There was also no significant difference in mean factor XIII values between women with severe PPH and controls (MD = - 0.07 IU/dL; 95%CI -0.17, 0.04).

Conclusion(s): On average, predelivery platelet count was lower in women who developed severe PPH compared to controls, suggesting the potential usefulness of this simple biomarker in the prediction of severe PPH.