Use of structural equation models to predict dengue illness phenotype.
BACKGROUND:Early recognition of dengue, particularly patients at risk for plasma leakage, is important to clinical management. The objective of this study was to build predictive models for dengue, dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS) using structural equation modelling (S...
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ftdoajarticles:oai:doaj.org/article:701f7aee9b214f9d9431ad2f07ada77b 2023-05-15T15:10:41+02:00 Use of structural equation models to predict dengue illness phenotype. Sangshin Park Anon Srikiatkhachorn Siripen Kalayanarooj Louis Macareo Sharone Green Jennifer F Friedman Alan L Rothman 2018-10-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0006799 https://doaj.org/article/701f7aee9b214f9d9431ad2f07ada77b EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC6181434?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0006799 https://doaj.org/article/701f7aee9b214f9d9431ad2f07ada77b PLoS Neglected Tropical Diseases, Vol 12, Iss 10, p e0006799 (2018) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2018 ftdoajarticles https://doi.org/10.1371/journal.pntd.0006799 2022-12-31T15:04:34Z BACKGROUND:Early recognition of dengue, particularly patients at risk for plasma leakage, is important to clinical management. The objective of this study was to build predictive models for dengue, dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS) using structural equation modelling (SEM), a statistical method that evaluates mechanistic pathways. METHODS/FINDINGS:We performed SEM using data from 257 Thai children enrolled within 72 h of febrile illness onset, 156 with dengue and 101 with non-dengue febrile illnesses. Models for dengue, DHF, and DSS were developed based on data obtained three and one day(s) prior to fever resolution (fever days -3 and -1, respectively). Models were validated using data from 897 subjects who were not used for model development. Predictors for dengue and DSS included age, tourniquet test, aspartate aminotransferase, and white blood cell, % lymphocytes, and platelet counts. Predictors for DHF included age, aspartate aminotransferase, hematocrit, tourniquet test, and white blood cell and platelet counts. The models showed good predictive performances in the validation set, with area under the receiver operating characteristic curves (AUC) at fever day -3 of 0.84, 0.67, and 0.70 for prediction of dengue, DHF, and DSS, respectively. Predictive performance was comparable using data based on the timing relative to enrollment or illness onset, and improved closer to the critical phase (AUC 0.73 to 0.94, 0.61 to 0.93, and 0.70 to 0.96 for dengue, DHF, and DSS, respectively). CONCLUSIONS:Predictive models developed using SEM have potential use in guiding clinical management of suspected dengue prior to the critical phase of illness. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 12 10 e0006799 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Sangshin Park Anon Srikiatkhachorn Siripen Kalayanarooj Louis Macareo Sharone Green Jennifer F Friedman Alan L Rothman Use of structural equation models to predict dengue illness phenotype. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
BACKGROUND:Early recognition of dengue, particularly patients at risk for plasma leakage, is important to clinical management. The objective of this study was to build predictive models for dengue, dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS) using structural equation modelling (SEM), a statistical method that evaluates mechanistic pathways. METHODS/FINDINGS:We performed SEM using data from 257 Thai children enrolled within 72 h of febrile illness onset, 156 with dengue and 101 with non-dengue febrile illnesses. Models for dengue, DHF, and DSS were developed based on data obtained three and one day(s) prior to fever resolution (fever days -3 and -1, respectively). Models were validated using data from 897 subjects who were not used for model development. Predictors for dengue and DSS included age, tourniquet test, aspartate aminotransferase, and white blood cell, % lymphocytes, and platelet counts. Predictors for DHF included age, aspartate aminotransferase, hematocrit, tourniquet test, and white blood cell and platelet counts. The models showed good predictive performances in the validation set, with area under the receiver operating characteristic curves (AUC) at fever day -3 of 0.84, 0.67, and 0.70 for prediction of dengue, DHF, and DSS, respectively. Predictive performance was comparable using data based on the timing relative to enrollment or illness onset, and improved closer to the critical phase (AUC 0.73 to 0.94, 0.61 to 0.93, and 0.70 to 0.96 for dengue, DHF, and DSS, respectively). CONCLUSIONS:Predictive models developed using SEM have potential use in guiding clinical management of suspected dengue prior to the critical phase of illness. |
format |
Article in Journal/Newspaper |
author |
Sangshin Park Anon Srikiatkhachorn Siripen Kalayanarooj Louis Macareo Sharone Green Jennifer F Friedman Alan L Rothman |
author_facet |
Sangshin Park Anon Srikiatkhachorn Siripen Kalayanarooj Louis Macareo Sharone Green Jennifer F Friedman Alan L Rothman |
author_sort |
Sangshin Park |
title |
Use of structural equation models to predict dengue illness phenotype. |
title_short |
Use of structural equation models to predict dengue illness phenotype. |
title_full |
Use of structural equation models to predict dengue illness phenotype. |
title_fullStr |
Use of structural equation models to predict dengue illness phenotype. |
title_full_unstemmed |
Use of structural equation models to predict dengue illness phenotype. |
title_sort |
use of structural equation models to predict dengue illness phenotype. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2018 |
url |
https://doi.org/10.1371/journal.pntd.0006799 https://doaj.org/article/701f7aee9b214f9d9431ad2f07ada77b |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 12, Iss 10, p e0006799 (2018) |
op_relation |
http://europepmc.org/articles/PMC6181434?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0006799 https://doaj.org/article/701f7aee9b214f9d9431ad2f07ada77b |
op_doi |
https://doi.org/10.1371/journal.pntd.0006799 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
12 |
container_issue |
10 |
container_start_page |
e0006799 |
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1766341658721386496 |