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Predictive scoring system for risk of complications in pediatric dengue infection

Background: Dengue infection has been a worrisome cause of mortality and morbidity in children. Though numerous scoring systems have been developed, they are in the adult population or are too complicated for use in children. Pediatric dengue infection has a wide spectrum from a mild illness to seve...

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Autores principales: Bhaskar, Monisha, Mahalingam, Soundarya, M M, Harish, Achappa, Basavaprabhu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9263579/
https://www.ncbi.nlm.nih.gov/pubmed/35860477
http://dx.doi.org/10.12688/f1000research.111214.1
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author Bhaskar, Monisha
Mahalingam, Soundarya
M M, Harish
Achappa, Basavaprabhu
author_facet Bhaskar, Monisha
Mahalingam, Soundarya
M M, Harish
Achappa, Basavaprabhu
author_sort Bhaskar, Monisha
collection PubMed
description Background: Dengue infection has been a worrisome cause of mortality and morbidity in children. Though numerous scoring systems have been developed, they are in the adult population or are too complicated for use in children. Pediatric dengue infection has a wide spectrum from a mild illness to severe complications and an unpredictable course. Hence the need for a predictive scoring system where the possibility of complications can be identified which can contribute to reduction in mortality and morbidity of dengue by prompt referrals and anticipatory management. Methods: Prospective case cohort study of children with confirmed dengue fever. Results: 303 children were included and divided into two groups – the dengue fever group and the complicated dengue group based on the WHO clinical classification. The clinical and laboratory parameters were analysed individually, cut offs identified by ROC curves and compared for significance between the two groups. The parameters that emerged were hypotension, PCV ≥ 42%, platelet count ≤ 75000 cells/cumm, WBC ≥ 7000 cells/cumm, and ALT ≥ 70U/L.  Using the adjusted odd’s Ratio, and coefficient, individual predictive scores were tabulated ranging from 0 to 3, with a total score of 0 to 7. A cut-off score of 2 was then identified based upon the sensitivity (84.13%) and specificity (72.50%) as the ideal score to predict complicated dengue. Internal validation of the score was done where the area under the curve for predicting complicated dengue was 0.86 (95% CI 0.8-0.92) with a P value of <0.001. Conclusion: Our dengue predictive scoring system has been developed using five indicators, with a score of two and above, out of seven, suggesting increased risk of developing complications. This has been validated internally and can be used to predict complicated dengue among children.
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spelling pubmed-92635792022-07-19 Predictive scoring system for risk of complications in pediatric dengue infection Bhaskar, Monisha Mahalingam, Soundarya M M, Harish Achappa, Basavaprabhu F1000Res Research Article Background: Dengue infection has been a worrisome cause of mortality and morbidity in children. Though numerous scoring systems have been developed, they are in the adult population or are too complicated for use in children. Pediatric dengue infection has a wide spectrum from a mild illness to severe complications and an unpredictable course. Hence the need for a predictive scoring system where the possibility of complications can be identified which can contribute to reduction in mortality and morbidity of dengue by prompt referrals and anticipatory management. Methods: Prospective case cohort study of children with confirmed dengue fever. Results: 303 children were included and divided into two groups – the dengue fever group and the complicated dengue group based on the WHO clinical classification. The clinical and laboratory parameters were analysed individually, cut offs identified by ROC curves and compared for significance between the two groups. The parameters that emerged were hypotension, PCV ≥ 42%, platelet count ≤ 75000 cells/cumm, WBC ≥ 7000 cells/cumm, and ALT ≥ 70U/L.  Using the adjusted odd’s Ratio, and coefficient, individual predictive scores were tabulated ranging from 0 to 3, with a total score of 0 to 7. A cut-off score of 2 was then identified based upon the sensitivity (84.13%) and specificity (72.50%) as the ideal score to predict complicated dengue. Internal validation of the score was done where the area under the curve for predicting complicated dengue was 0.86 (95% CI 0.8-0.92) with a P value of <0.001. Conclusion: Our dengue predictive scoring system has been developed using five indicators, with a score of two and above, out of seven, suggesting increased risk of developing complications. This has been validated internally and can be used to predict complicated dengue among children. F1000 Research Limited 2022-04-21 /pmc/articles/PMC9263579/ /pubmed/35860477 http://dx.doi.org/10.12688/f1000research.111214.1 Text en Copyright: © 2022 Bhaskar M et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Bhaskar, Monisha
Mahalingam, Soundarya
M M, Harish
Achappa, Basavaprabhu
Predictive scoring system for risk of complications in pediatric dengue infection
title Predictive scoring system for risk of complications in pediatric dengue infection
title_full Predictive scoring system for risk of complications in pediatric dengue infection
title_fullStr Predictive scoring system for risk of complications in pediatric dengue infection
title_full_unstemmed Predictive scoring system for risk of complications in pediatric dengue infection
title_short Predictive scoring system for risk of complications in pediatric dengue infection
title_sort predictive scoring system for risk of complications in pediatric dengue infection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9263579/
https://www.ncbi.nlm.nih.gov/pubmed/35860477
http://dx.doi.org/10.12688/f1000research.111214.1
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