Does precision-based medicine hold the promise of a new approach to predicting and treating spontaneous preterm birth?
File(s)ijtm-04-00002-with-cover.pdf (2.72 MB)
Published version
Author(s)
Khan, Hiba
Singh, Natasha
Leyva, Luis Y
Malawana, Johann
Shah, Nishel M
Type
Journal Article
Abstract
Background: Preterm birth (PTB) is a leading cause of childhood disability, and it has become a key public health priority recognized by the World Health Organization and the United Nations. Objectives: This review will: (1) summarize current practice in the diagnosis and management of PTB, (2) outline developments in precision-based medicine for diagnostics to improve the care provided to pregnant women at risk of PTB, and (3) discuss the implications of current research in personalized medicine and the potential of future advances to influence the clinical care of women at risk of PTB. Methodology: This is a narrative literature review. Relevant journal articles were identified following searches of computerized databases. Key Results: Current and emerging technologies for the utility of personalized medicine in the context of PTB have the potential for applications in: (1) direct diagnostics to identify and target infection as one of the main known causes of PTB, (2) identifying novel maternal and fetal biomarkers, (3) the use of artificial intelligence and computational modeling, and (4) combining methods to enhance diagnosis and treatment. Conclusions: In this paper, we show how current research has moved in the direction of the targeted use of biomarkers in the context of PTB, with many novel approaches.
Date Issued
2024-03
Date Acceptance
2023-11-01
Citation
International Journal of Translational Medicine, 2024, 4 (1), pp.15-52
ISSN
2673-8937
Publisher
MDPI AG
Start Page
15
End Page
52
Journal / Book Title
International Journal of Translational Medicine
Volume
4
Issue
1
Copyright Statement
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
http://dx.doi.org/10.3390/ijtm4010002
Publication Status
Published
Date Publish Online
2024-01-05