{"title":"Prognostic Indicators of Severe Dengue Infection in Adult Patients in Thailand.","authors":"Patcharin Khamnuan, Surangrat Pongpan, Pantitcha Thanatrakolsri, Supa Vittaporn, Punnaphat Daraswang, Sirawan Samsee","doi":"10.3390/tropicalmed10080233","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Dengue infection is a spreading vector borne disease with most severe infection-related fatalities occurring in adults. This study was conducted to explore prognostic indicators of dengue infection severity.</p><p><strong>Methods: </strong>This study included patients aged over 15 years who were diagnosed with dengue viral infection. Data were collected from nine hospitals across all regions of Thailand between January 2019 and December 2022. Diagnosis of dengue infection was confirmed by a positive result for the NS-1 antigen via RT-PCR, IgM antibody, or IgG antibody tests. Data including gender, age, BMI, underlying disease, clinical characteristics and laboratory findings were collected. Multivariable logistic regression with backward elimination was used to identify a set of prognostic factors.</p><p><strong>Results: </strong>The prognostic indicators of severe dengue were age < 55 years (OR = 6.13, <i>p</i> = 0.054), severe bleeding (bleeding from the gastrointestinal tract, hematemesis, melena, menorrhagia, or hematuria) (OR = 20.75, <i>p</i> < 0.001), pleural effusion (OR = 10.23, <i>p</i> < 0.001), and platelet ≤ 100,000 (/µL) (OR = 3.62, <i>p</i> = 0.035). These predictors were able to accurately estimate the severity of dengue infection with an area under the receiver operating curve (AuROC) of 0.836.</p><p><strong>Conclusions: </strong>The proposed four prognostic factors can be applied to predict severe dengue infections. These findings may inform the development of a risk scoring system to forecast severe dengue infection, early detection, and appropriate treatment during sickness.</p>","PeriodicalId":23330,"journal":{"name":"Tropical Medicine and Infectious Disease","volume":"10 8","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12390324/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tropical Medicine and Infectious Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/tropicalmed10080233","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Dengue infection is a spreading vector borne disease with most severe infection-related fatalities occurring in adults. This study was conducted to explore prognostic indicators of dengue infection severity.
Methods: This study included patients aged over 15 years who were diagnosed with dengue viral infection. Data were collected from nine hospitals across all regions of Thailand between January 2019 and December 2022. Diagnosis of dengue infection was confirmed by a positive result for the NS-1 antigen via RT-PCR, IgM antibody, or IgG antibody tests. Data including gender, age, BMI, underlying disease, clinical characteristics and laboratory findings were collected. Multivariable logistic regression with backward elimination was used to identify a set of prognostic factors.
Results: The prognostic indicators of severe dengue were age < 55 years (OR = 6.13, p = 0.054), severe bleeding (bleeding from the gastrointestinal tract, hematemesis, melena, menorrhagia, or hematuria) (OR = 20.75, p < 0.001), pleural effusion (OR = 10.23, p < 0.001), and platelet ≤ 100,000 (/µL) (OR = 3.62, p = 0.035). These predictors were able to accurately estimate the severity of dengue infection with an area under the receiver operating curve (AuROC) of 0.836.
Conclusions: The proposed four prognostic factors can be applied to predict severe dengue infections. These findings may inform the development of a risk scoring system to forecast severe dengue infection, early detection, and appropriate treatment during sickness.