Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/187980
Título: Clinical characteristics, complications and outcomes of critically ill patients with Dengue in Brazil, 2012-2024
Autor: Peres, Igor Tona
Ranzani, Otavio T.
Bastos, Leonardo S.L.
Hamacher, Silvio
Edinburgh, Tom
Garcia-Gallo, Esteban
Bozza, Fernando Augusto
Palavras-chave: Clinical management
Dengue
Intensive care
Prediction
Risk factors
Microbiology (medical)
Infectious Diseases
SDG 3 - Good Health and Well-being
Data: Out-2025
Resumo: Background: Dengue outbreaks are a major public health issue, with Brazil reporting 71% of global cases in 2024. Purpose: This study aims to describe the profile of severe dengue patients admitted to Brazilian intensive care units (ICUs) (2012-2024), assess trends over time, describe new onset complications while in ICU, and determine the risk factors at admission to develop complications during ICU stay. Methods: We performed a prospective study of dengue patients from 253 ICUs across 56 hospitals. We used descriptive statistics to describe the dengue ICU population, logistic regression to identify risk factors for complications during the ICU stay, and a machine learning framework to predict the risk of evolving to complications. Visualizations were generated using ISARIC VERTEX. Results: Of 11,047 admissions, 1117 admissions (10.1%) evolved to complications, including non-invasive (437 admissions) and invasive ventilation (166), vasopressor (364), blood transfusion (353), and renal replacement therapy (103). Age ≥80 (odds ratio [OR]: 3.10, 95% confidence interval: 2.02-4.92), chronic kidney disease (OR: 2.94, 2.22-3.89), liver cirrhosis (OR: 3.65, 1.82-7.04), low platelets (<50,000 cells/mm³; OR: 2.25, 1.89-2.68), and high leukocytes (>7000 cells/mm³; OR: 2.47, 2.02-3.03) were significant risk factors for complications. A machine learning tool for predicting complications was proposed, showing accurate discrimination and calibration. Conclusion: We described a large cohort of dengue patients admitted to ICUs and identified key risk factors for severe dengue complications, such as advanced age, presence of comorbidities, higher level of leukocytes, and lower level of platelets. The proposed prediction tool can be used for early identification and targeted interventions to improve outcomes in dengue-endemic regions.
Descrição: Funding Information: This work was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (403379/2024-5, 444968/2023-7 and 312654/2023-5 to S.H; 420096/2023-0 to L.B; 309546/2025-7 to I.P); the Carlos Chagas Filho Foundation for Research Support in Rio de Janeiro State (FAPERJ) ( E-26/210.858/2024 and E-26/204.540/2024 to I.P; E-26/204.520/2024 to L.B; E-26/204.187/2024 to S.H); the Ram\u00F3n y Cajal program [RYC2023-002923-C to O.R] awarded by the Spanish Ministry of Science; the Innovation and Universities [MICIU/AEI/10.13039/501100011033 to O.R]; the Wellcome Trust (303666/Z/23/Z); UK International Development (301542-403); the Gates Foundation (INV-063472); the European Social Fund Plus (ESF+); the Coordination for the Improvement of Higher Education Personnel (CAPES); and the Pontifical Catholic University of Rio de Janeiro. Publisher Copyright: © 2025 The Authors
Peer review: yes
URI: http://hdl.handle.net/10362/187980
DOI: https://doi.org/10.1016/j.ijid.2025.108023
ISSN: 1201-9712
Aparece nas colecções:NMS: CHRC - Artigos em revista internacional com arbitragem científica

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