Validation of probability equation and decision tree in predicting subsequent dengue hemorrhagic fever in adult dengue inpatients in Singapore.

We developed a probability equation and a decision tree from 1,973 predominantly dengue serotype 1 hospitalized adult dengue patients in 2004 to predict progression to dengue hemorrhagic fever (DHF), applied in our clinic since March 2007. The parameters predicting DHF were clinical bleeding, high serum urea, low serum protein, and low lymphocyte proportion. This study validated these in a predominantly dengue serotype 2 cohort in 2007. The 1,017 adult dengue patients admitted to Tan Tock Seng Hospital, Singapore had a median age of 35 years. Of 933 patients without DHF on admission, 131 progressed to DHF. The probability equation predicted DHF with a sensitivity (Sn) of 94%, specificity (Sp) 17%, positive predictive value (PPV) 16%, and negative predictive value (NPV) 94%. The decision tree predicted DHF with a Sn of 99%, Sp 12%, PPV 16%, and NPV 99%. Both tools performed well despite a switch in predominant dengue serotypes.

Consecuencias del dengue hemorrágico en niños / Impact of dengue hemorrhagic fever in children

En los niños, el dengue se presenta con una variabilidad sintomática caracterizado por manifestaciones de extravasación vascular que pueden conllevar a consecuencias severas en términos de mortalidad y de costos. Estudio prospectivo y descriptivo realizado en Pediatría Médica Infecciosa (PMI) del hospital Universitario de Caracas (HUC), en niños de un mes a 12 años, con criterios de dengue hemorrágico (DH) y evidencia por laboratorio de infección aguda o reciente, que ingresaron entre enero 2000 y junio 2008, con el objetivo de evaluar las consecuencias en términos de mortalidad y costos por hospitalización. De 4 386/930 hospitalizados que ingresaron con diagnóstico de dengue, 453 cumplieron con los criterios de inclusión representando el 10 por ciento de las hospitalizaciones en PMI. El DH se presentó con mayor frecuencia entre los 5 y 9 años de edad y en el segundo semestre de cada año. El promedio de hospitalización fue de 6 días. Las consecuencias se evaluaron en términos de pérdidas de vidas (3 niños), con una tasa de letalidad 0,6 por ciento y egresos monetarios por concepto de hospitalización (exceptuando de la definición, costos/medicamentos y pruebas de laboratorio). Los gastos/hospitalización/día oscilaron entre 100 y 350$. Un 15 por ciento de los pacientes recibieron antibióticos por diagnósticos diferenciales. Ha habido un incremento progresivo de hospitalizaciones por DH en PMI, desde el 2000, predominando en la época de lluvia, con registros de casos fatales. Se generaron costos hospitalarios elevados por hospitalización que pudieran ser derivados a campañas de prevención.

Decision tree algorithms predict the diagnosis and outcome of dengue fever in the early phase of illness.

BACKGROUND: Dengue is re-emerging throughout the tropical world, causing frequent recurrent epidemics. The initial clinical manifestation of dengue often is confused with other febrile states confounding both clinical management and disease surveillance. Evidence-based triage strategies that identify individuals likely to be in the early stages of dengue illness can direct patient stratification for clinical investigations, management, and virological surveillance. Here we report the identification of algorithms that differentiate dengue from other febrile illnesses in the primary care setting and predict severe disease in adults. METHODS AND FINDINGS: A total of 1,200 patients presenting in the first 72 hours of acute febrile illness were recruited and followed up for up to a 4-week period prospectively; 1,012 of these were recruited from Singapore and 188 from Vietnam. Of these, 364 were dengue RT-PCR positive; 173 had dengue fever, 171 had dengue hemorrhagic fever, and 20 had dengue shock syndrome as final diagnosis. Using a C4.5 decision tree classifier for analysis of all clinical, haematological, and virological data, we obtained a diagnostic algorithm that differentiates dengue from non-dengue febrile illness with an accuracy of 84.7%. The algorithm can be used differently in different disease prevalence to yield clinically useful positive and negative predictive values. Furthermore, an algorithm using platelet count, crossover threshold value of a real-time RT-PCR for dengue viral RNA, and presence of pre-existing anti-dengue IgG antibodies in sequential order identified cases with sensitivity and specificity of 78.2% and 80.2%, respectively, that eventually developed thrombocytopenia of 50,000 platelet/mm(3) or less, a level previously shown to be associated with haemorrhage and shock in adults with dengue fever. CONCLUSION: This study shows a proof-of-concept that decision algorithms using simple clinical and haematological parameters can predict diagnosis and prognosis of dengue disease, a finding that could prove useful in disease management and surveillance.

Short report: assessment of the World Health Organization scheme for classification of dengue severity in Nicaragua.

The World Health Organization (WHO) scheme for classification of dengue severity was evaluated in a three-year study of 1,671 confirmed dengue cases in three Nicaraguan hospitals. The WHO classification of dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS) was compared with the presence of hemorrhagic manifestations, signs of vascular permeability, marked thrombocytopenia, and shock in 114 infants, 1,211 children, and 346 adults. We found that strict application of the WHO criteria fails to detect a significant number of patients with severe manifestations of dengue, especially in adults.