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Examining associations between social vulnerability and maternal morbidity among a multicentre cohort of pregnancies complicated by placenta accreta spectrum disorder in New York City

Authors :
Nicola Francesco Tavella
Henri Mitchell Rosenberg
Alexandra Mills
Thomas Owens
Lois Brustman
Georgios Doulaveris
Shoshana Haberman
Meghana Limaye
Teresa Janevic
Rebecca Hope Jessel
Angela Teresa Bianco
Source :
BMJ Public Health, Vol 2, Iss 2 (2024)
Publication Year :
2024
Publisher :
BMJ Publishing Group, 2024.

Abstract

Background Placenta accreta spectrum (PAS) disorder is a source of severe obstetric morbidity and mortality worldwide. The objective of this paper was to evaluate the potential relationship between social vulnerability and severe maternal morbidity in a cohort of patients delivering a pregnancy complicated by PAS.Methods A retrospective review of 323 deliveries at three academic medical institutions between January 2013 and June 2022 was included in the analyses. Patients were those with a histopathologically confirmed case of PAS. The composite morbidity outcome included such maternal complications as mechanical ventilation, injury to organs and transfusion of 4+units of red blood cells. Social vulnerability was measured by assigning subjects a value of the Childhood Opportunity Index based on their home zip code. Logistic regression models were employed and adjusted for potential confounders.Results 73% of our sample experienced composite severe maternal morbidity at the time of their delivery. There were no statistically significant associations between social vulnerability and severe surgical morbidity, either as a composite or individually, within the multivariate regression models.Conclusion Our results do not support the hypothesis that social vulnerability is associated with severe maternal morbidity in deliveries complicated by PAS. The present study suggests that the relationship between social vulnerability and obstetrical surgical morbidity is more complicated than can be assessed by the present linear regression models.

Details

Language :
English
ISSN :
27534294
Volume :
2
Issue :
2
Database :
Directory of Open Access Journals
Journal :
BMJ Public Health
Publication Type :
Academic Journal
Accession number :
edsdoj.935ecef742154c97a7a50985700f739c
Document Type :
article
Full Text :
https://doi.org/10.1136/bmjph-2024-001083