A scoping review and modelling of predictors of an abnormal Thompson score in term neonates in low-resource settings
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Clinical risk scores, such as Thompson score, are useful alternatives to identify neonatal encephalopathy in low-resource settings where adequate training and equipment are often unavailable. An understanding of the clinical predictors of abnormally high Thompson score values would be beneficial to identify term neonates with suspected neonatal encephalopathy. A scoping review was conducted to identify a set of a priori neonatal and maternal variables associated with neonatal encephalopathy. Next, a prospective study of all term neonates admitted to Sally Mugabe Central Hospital in Zimbabwe between October 2020 and December 2022 was conducted to develop a predictive statistical model of abnormal (> 10) Thompson score. In total 45 articles were identified from searching Medline, Scopus and Web of Science and 10 articles were selected. Five studies were conducted in countries in Asia and five in Africa. Of 6,054 neonates who met the inclusion criteria, 4.06% (n = 246) had an abnormal Thompson score at admission with a case fatality rate of 589 per 1000 admissions. Among these neonates, 90.65% (n = 223) had a low Apgar score (p < 0.001). 40 candidate predictors were identified, of which 20 predictors were selected as the most important. Six risk factors were predictive of neonates at risk of abnormal Thompson score, including low neonatal heart rate (aOR = 0.97), temperature lower than 36.5 °C (aOR = 2.24), head swelling (aOR = 2.19), other maternal risk factors of sepsis excluding offensive liquor and premature rupture of membranes (aOR = 1.97), meconium-stained umbilicus (aOR = 1.79), and not crying at birth (aOR = 2.58). These identified risk factors should be prioritised before conducting a Thompson score assessment in resource-poor settings, and local clinical guidelines should incorporate these into the clinical management of at-risk neonates.
Date Issued
2025-04-10
Date Acceptance
2025-03-28
Citation
Scientific Reports, 2025, 15
ISSN
2045-2322
Publisher
Nature Portfolio
Journal / Book Title
Scientific Reports
Volume
15
Copyright Statement
© The Author(s) 2025 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
10.1038/s41598-025-96566-7
Subjects
Newborn care
Neonatal encephalopathy
Predictive modeling
LMIC
Low-resource settings
Publication Status
Published
Article Number
12217
Date Publish Online
2025-04-10