Dengue Fever Scoring System: New Strategy for the Early Detection of Acute Dengue Virus Infection in Taiwan

Chang, Ko; Lu, Po‐Liang; Ko, Wen–Chien; Tsai, Jih‐Jin; Tsai, Wu-Hsiung; Chen, Chaur-Doug; Chen, Yen-Hsu; Chen, Tun‐Chieh; Hsieh, Hsiao-Chen; Pan, Chao-Ying; Harn, Ming-Rong

doi:10.1016/s0929-6646(09)60420-4

Cited by 27 publications

(24 citation statements)

References 9 publications

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“…Previous scoring systems trying to evaluate or forecast disease severity included the Dengue Fever Scoring System based on epidemiological information and clinical signs or symptoms, which might be useful in detecting DF very early prior to laboratory results [25]. Other scoring systems were the Pediatric Logistic Organ Dysfunction (PELOD) Score and the Pediatric Risk of Mortality III (PRISM III), used to evaluate the mortality rates [26], and the Disseminate Intravascular Coagulation (DIC) Score to diagnose DIC and to discriminate DF and DHF from other febrile illnesses [27].…”

Section: Discussionmentioning

confidence: 99%

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Development of Dengue Infection Severity Score

Pongpan

Wisitwong

Tawichasri³

et al. 2013

ISRN Pediatrics

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Objectives. To develop a simple scoring system to predict dengue infection severity based on patient characteristics and routine clinical profiles. Methods. Retrospective data of children with dengue infection from 3 general hospitals in Thailand were reviewed. Dengue infection was categorized into 3 severity levels: dengue infection (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS). Coefficients of significant predictors of disease severity under ordinal regression analysis were transformed into item scores. Total scores were used to classify patients into 3 severity levels. Results. Significant clinical predictors of dengue infection severity were age >6 years, hepatomegaly, hematocrit ≥40%, systolic pressure <90 mmHg, white cell count >5000 /μL, and platelet ≤50000 /μL. The derived total scores, which ranged from 0 to 18, classified patients into 3 severity levels: DF (scores <2.5, n = 451, 58.1%), DHF (scores 2.5–11.5, n = 276, 35.5%), and DSS (scores >11.5, n = 50, 6.4%). The derived score correctly classified patients into their original severity levels in 60.7%. An under-estimation of 25.7% and an over-estimation of 13.5% were clinically acceptable. Conclusions. The derived dengue infection severity score classified patients into DF, DHF, or DSS, correctly into their original severity levels. Validation of the score should be reconfirmed before application of routine practice.

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Section: Discussionmentioning

confidence: 99%

“…Some studies included only adult patients [25, 29] which may or may not be relevant for children. In studies which included children, some studies used information on the first few days of admission in pediatric intensive care unit (PICU) [19].…”

Section: Discussionmentioning

confidence: 99%

Development of Dengue Infection Severity Score

Pongpan

Wisitwong

Tawichasri³

et al. 2013

ISRN Pediatrics

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“…Researchers have attempted to develop scoring systems to predict infectious diseases or their severity to help clinical management. Examples were a dengue fever scoring system to differentiate dengue fever from rickettsial and Q fever, which was developed in Taiwan,19 decision-tree algorithms to differentiate and prognosticate dengue hemorrhagic fever,20 and a prediction rule to evaluate the risk for community-acquired pneumonia to help admission decisions 18. These prediction rules used parameters of epidemiologic, demographic, clinical signs and symptoms, or laboratory characteristics.…”

Section: Discussionmentioning

confidence: 99%

Clinical risk-scoring algorithm to forecast scrub typhus severity

Sriwongpan

Krittigamas

Tantipong

et al. 2013

RMHP

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PurposeTo develop a simple risk-scoring system to forecast scrub typhus severity.Patients and methodsSeven years’ retrospective data of patients diagnosed with scrub typhus from two university-affiliated hospitals in the north of Thailand were analyzed. Patients were categorized into three severity groups: nonsevere, severe, and dead. Predictors for severity were analyzed under multivariable ordinal continuation ratio logistic regression. Significant coefficients were transformed into item score and summed to total scores.ResultsPredictors of scrub typhus severity were age >15 years, (odds ratio [OR] =4.09), pulse rate >100/minute (OR 3.19), crepitation (OR 2.97), serum aspartate aminotransferase >160 IU/L (OR 2.89), serum albumin ≤3.0 g/dL (OR 4.69), and serum creatinine >1.4 mg/dL (OR 8.19). The scores which ranged from 0 to 16, classified patients into three risk levels: non-severe (score ≤5, n=278, 52.8%), severe (score 6–9, n=143, 27.2%), and fatal (score ≥10, n=105, 20.0%). Exact severity classification was obtained in 68.3% of cases. Underestimations of 5.9% and overestimations of 25.8% were clinically acceptable.ConclusionThe derived scrub typhus severity score classified patients into their severity levels with high levels of prediction, with clinically acceptable under- and overestimations. This classification may assist clinicians in patient prognostication, investigation, and management. The scoring algorithm should be validated by independent data before adoption into routine clinical practice.

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“…The search for the molecular events involved in DHF development and for host genes related to the protection/infection of the DENV has instigated several high-throughput studies that have elucidated the role of various molecules and pathways during a DENV infection event (Fink et al 2007, de Kruif et al 2008, Higa et al 2008, Chang et al 2009, Long et al 2009, Nascimento et al 2009a, b). Despite controversial and inconclusive results, there is a consensus that the innate immune and apoptotic processes trigger haemorrhagic symptoms depending on the magnitude of the response/expression (Espina et al 2003, Ubol et al 2008, Brown et al 2009, Cheng et al 2009, Gil et al 2009, Jaiyen et al 2009, Nasirudeen & Liu 2009, Nascimento et al 2009a, Conceição et al 2010).…”

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confidence: 99%

Potential biomarkers for the clinical prognosis of severe dengue

Silva

Gil

Marques

et al. 2013

Mem. Inst. Oswaldo Cruz

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Currently, several assays can confirm acute dengue infection at the point-of-care. However, none of these assays can predict the severity of the disease symptoms. A prognosis test that predicts the likelihood of a dengue patient to develop a severe form of the disease could permit more efficient patient triage and treatment. We hypothesise that mRNA expression of apoptosis and innate immune response-related genes will be differentially regulated during the early stages of dengue and might predict the clinical outcome. Aiming to identify biomarkers for dengue prognosis, we extracted mRNA from the peripheral blood mononuclear cells of mild and severe dengue patients during the febrile stage of the disease to measure the expression levels of selected genes by quantitative polymerase chain reaction. The selected candidate biomarkers were previously identified by our group as differentially expressed in microarray studies. We verified that the mRNA coding for CFD, MAGED1, PSMB9, PRDX4 and FCGR3B were differentially expressed between patients who developed clinical symptoms associated with the mild type of dengue and patients who showed clinical symptoms associated with severe dengue. We suggest that this gene expression panel could putatively serve as biomarkers for the clinical prognosis of dengue haemorrhagic fever.

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Dengue Fever Scoring System: New Strategy for the Early Detection of Acute Dengue Virus Infection in Taiwan

Abstract: The dengue scoring system had a high NPV that might be helpful in the early diagnosis of dengue fever in adults before laboratory data are available.

Cited by 27 publications

References 9 publications

Development of Dengue Infection Severity Score

Development of Dengue Infection Severity Score

Clinical risk-scoring algorithm to forecast scrub typhus severity

Potential biomarkers for the clinical prognosis of severe dengue

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