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Development and Validation of a Bedside Dengue Severity Score for Predicting Severe Dengue in Children

OBJECTIVE: To develop and validate a bedside dengue severity score in children less than 12 years for predicting severe dengue disease. METHODS: We carried out an analysis of data on the clinical and laboratory parameters of patients with confirmed dengue, hospitalized in October, 2019 at our center...

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Detalles Bibliográficos
Autores principales: Gayathri, Vaitheeswaran, Lakshmi, Shanmugavel Velmurugan, Murugan, Sivaraman Senthil, Poovazhagi, Varadarajan, Kalpana, Sivasambo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10185942/
https://www.ncbi.nlm.nih.gov/pubmed/36757000
http://dx.doi.org/10.1007/s13312-023-2880-7
Descripción
Sumario:OBJECTIVE: To develop and validate a bedside dengue severity score in children less than 12 years for predicting severe dengue disease. METHODS: We carried out an analysis of data on the clinical and laboratory parameters of patients with confirmed dengue, hospitalized in October, 2019 at our center. A comprehensive patient’s score was developed. Predictive models for severity were built using a forward step-wise method. This model was validated on the data of 312 children with dengue admitted during September- October, 2021. RESULTS: Severe dengue was predicted by the dengue severity score with a sensitivity of 86.75% (95% CI 77.52%–93.19%), specificity of 98.25% (95% CI 95.56–99.52%), a positive predictive value of 95.34% (95% CI 92.18%–97.26%) and a negative predictive value of 94.74% (95% CI 87.16%–97.95%). The overall predictive accuracy was 95.2% (95% CI 92.19%–97.28%). CONCLUSION: The proposed bedside dengue severity scoring system was found to have good validity. Validating the score in different settings and patient populations is suggested. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available in the online version of this article at 10.1007/s13312-023-2880-7.