Improving early prediction for adverse dengue outcomes using data from the IDAMS prospective multicentre study

Abstract Early identification of individuals at risk of complications is important to improve dengue case-management and promote appropriate use of limited resources in high burden settings. In this prospective observational cohort, 7428 febrile outpatients were enrolled across 8 countries in Asia and Latin America and followed daily; 2230 individuals with confirmed dengue were included in the analysis, among whom 304 (14%) progressed to moderate/severe dengue and 38 (2%) to severe dengue during follow-up. We demonstrate evolving relationships between common clinical features, WHO clinical warning signs, and simple haematological parameters, with progression. Key predictors of moderate/severe dengue include low lymphocyte percentage, low total white blood cell count, low platelet count, and persistent vomiting and significant abdominal pain/tenderness. Multivariable models incorporating these variables predict the risk of moderate/severe dengue, initially with modest performance (AUC ~ 0.68), but improving subsequently as new daily data is included into the predictions (AUC ~ 0.73-0.85). We also demonstrate that using these models in combination with clinical decision-making pathways could facilitate earlier admission of high-risk patients without markedly increasing admissions of uncomplicated cases. These results should prove instrumental for updating guidelines on dengue triage and management, potentially providing major public health benefits in resource poor settings.

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Publication Details

Journal
Nature Communications
Published
2026-08-21
DOI
https://doi.org/10.1038/s41467-026-76450-2
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
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article

Improving early prediction for adverse dengue outcomes using data from the IDAMS prospective multicentre study

Patrícia Brasil, Quyen T.K. Nguyen, Ngoc Tran Van, Bruno Souza Benevides et al.
Nature Communications
Mosquito-borne diseases and control
article

Improving early prediction for adverse dengue outcomes using data from the IDAMS prospective multicentre study

Patrícia Brasil, Quyen T.K. Nguyen, Ngoc Tran Van, Bruno Souza Benevides, Varun Kumar, Kieu Nguyen Tan Thanh, Kerstin Daniela Rosenberger, Ernesto T. A. Marques, Ngoun Chanpheaktra, María Guadalupe Guzmán Tirado, Nam Nguyen Tran, Lucy Lum Chai See, Ida Safitri Laksanawati, Sarah Bethencourt, Sophie Yacoub, Andréa Caprara, Yodi Mahendradhata, Phung Khanh Lam, Gabriela Marón, Tam Dong Thi Hoai, Ronald B. Geskus, Jameela Sathar, Lucy Chai See Lum, Bridget Wills, Adriana Tami, Kính Nguyen Văn, Md Zabir Hasan, Tereza Magalhaes, Lam Phung Khanh, Quyen Nguyen Than Ha, Md Zabir Hassan, Thomas Jaenisch, Marco Netto, Firoz Ahmed, Marcel Wolbers, Cameron Simmons, Ernesto Pleités Sandoval, Viet Do Chau
article en

Abstract

Abstract Early identification of individuals at risk of complications is important to improve dengue case-management and promote appropriate use of limited resources in high burden settings. In this prospective observational cohort, 7428 febrile outpatients were enrolled across 8 countries in Asia and Latin America and followed daily; 2230 individuals with confirmed dengue were included in the analysis, among whom 304 (14%) progressed to moderate/severe dengue and 38 (2%) to severe dengue during follow-up. We demonstrate evolving relationships between common clinical features, WHO clinical warning signs, and simple haematological parameters, with progression. Key predictors of moderate/severe dengue include low lymphocyte percentage, low total white blood cell count, low platelet count, and persistent vomiting and significant abdominal pain/tenderness. Multivariable models incorporating these variables predict the risk of moderate/severe dengue, initially with modest performance (AUC ~ 0.68), but improving subsequently as new daily data is included into the predictions (AUC ~ 0.73-0.85). We also demonstrate that using these models in combination with clinical decision-making pathways could facilitate earlier admission of high-risk patients without markedly increasing admissions of uncomplicated cases. These results should prove instrumental for updating guidelines on dengue triage and management, potentially providing major public health benefits in resource poor settings.

Nature Communications
Universidade Estadual do Ceará (BR), East Tennessee State University (US), University Malaya Medical Centre (MY), University Medical Center Groningen (NL), Johns Hopkins University (US), Universitas Gadjah Mada (ID), University of Groningen (NL), University of Pittsburgh (US), International Centre for Diarrhoeal Disease Research (BD), Heidelberg University (DE), Hospital Kuala Lumpur (MY), Angkor Hospital for Children (KH), University Hospital Heidelberg (DE), Noakhali Science and Technology University (BD), University of Malaya (MY), University of Oxford (GB), Hospital Nacional de Niños Bloom (SV), Unichristus (BR), Instituto Evandro Chagas (BR), Instituto de Medicina Tropical “Pedro Kourí” (CU), Oxford University Clinical Research Unit (VN), KPJ Ampang Puteri Specialist Hospital (MY), Secretaria Municipal de Saúde (BR), Fundação Oswaldo Cruz (BR), BRAC University (BD), Universidad de Carabobo (VE)
University of Oxford
No poverty
Openalex Percentile: Top 8%
Mosquito-borne diseases and control
DOIOpen Access PDFOpenAlex
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