Dataset Information

A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses.

ABSTRACT: Kawasaki disease is an acute vasculitis of infants and young children that is recognized through a constellation of clinical signs that can mimic other benign conditions of childhood. The etiology remains unknown and there is no specific laboratory-based test to identify patients with Kawasaki disease. Treatment to prevent the complication of coronary artery aneurysms is most effective if administered early in the course of the illness. We sought to develop a diagnostic algorithm to help clinicians distinguish Kawasaki disease patients from febrile controls to allow timely initiation of treatment.Urine peptidome profiling and whole blood cell type-specific gene expression analyses were integrated with clinical multivariate analysis to improve differentiation of Kawasaki disease subjects from febrile controls.Comparative analyses of multidimensional protein identification using 23 pooled Kawasaki disease and 23 pooled febrile control urine peptide samples revealed 139 candidate markers, of which 13 were confirmed (area under the receiver operating characteristic curve (ROC AUC 0.919)) in an independent cohort of 30 Kawasaki disease and 30 febrile control urine peptidomes. Cell type-specific analysis of microarrays (csSAM) on 26 Kawasaki disease and 13 febrile control whole blood samples revealed a 32-lymphocyte-specific-gene panel (ROC AUC 0.969). The integration of the urine/blood based biomarker panels and a multivariate analysis of 7 clinical parameters (ROC AUC 0.803) effectively stratified 441 Kawasaki disease and 342 febrile control subjects to diagnose Kawasaki disease.A hybrid approach using a multi-step diagnostic algorithm integrating both clinical and molecular findings was successful in differentiating children with acute Kawasaki disease from febrile controls.

SUBMITTER: Ling XB

PROVIDER: S-EPMC3251532 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses.

Ling Xuefeng B XB Lau Kenneth K Kanegaye John T JT Pan Zheng Z Peng Sihua S Ji Jun J Liu Gigi G Sato Yuichiro Y Yu Tom T S TT Whitin John C JC Schilling James J Burns Jane C JC Cohen Harvey J HJ

BMC medicine 20111206

<h4>Background</h4>Kawasaki disease is an acute vasculitis of infants and young children that is recognized through a constellation of clinical signs that can mimic other benign conditions of childhood. The etiology remains unknown and there is no specific laboratory-based test to identify patients with Kawasaki disease. Treatment to prevent the complication of coronary artery aneurysms is most effective if administered early in the course of the illness. We sought to develop a diagnostic algori ...[more]

PMID: 22145762

Similar Datasets

Project description:BackgroundControl efforts towards malaria due to Plasmodium falciparum significantly decreased the incidence of the disease in many endemic countries including Senegal. Surprisingly, in Kedougou (southeastern Senegal) P. falciparum malaria remains highly prevalent and the relative contribution of other Plasmodium species to the global malaria burden is very poorly documented, partly due to the low sensitivity of routine diagnostic tools. Molecular methods offer better estimate of circulating Plasmodium species in a given area. A molecular survey was carried out to document circulating malaria parasites in Kedougou region.MethodsA total of 263 long-term stored sera obtained from patients presenting with acute febrile illness in Kedougou between July 2009 and July 2013 were used for malaria parasite determination. Sera were withdrawn from a collection established as part of a surveillance programme of arboviruses infections in the region. Plasmodium species were characterized by a nested PCR-based approach targeting the 18S small sub-unit ribosomal RNA genes of Plasmodium spp.ResultsOf the 263 sera screened in this study, Plasmodium genomic DNA was amplifiable by nested PCR from 62.35% (164/263) of samples. P. falciparum accounted for the majority of infections either as single in 85.97% (141/164) of Plasmodium-positive samples or mixed with Plasmodium ovale (11.58%, 19/164) or Plasmodium vivax (1.21%, 2/164). All 19 (11.58%) P. ovale-infected patients were mixed with P. falciparum, while no Plasmodium malariae was detected in this survey. Four patients (2.43%) were found to be infected by P. vivax, two of whom were mixed with P. falciparum. P. vivax infections originated from Bandafassi and Ninefesha villages and concerned patients aged 4, 9, 10, and 15 years old, respectively. DNA sequences alignment and phylogenetic analysis demonstrated that sequences from Kedougou corresponded to P. vivax, therefore confirming the presence of P. vivax infections in Senegal.ConclusionThe results confirm the high prevalence of P. falciparum in Kedougou and provide the first molecular evidence of P. vivax infections in Senegal. These findings pave the ways for further investigations of P. vivax infections in Senegal and its contribution to the global burden of malaria disease before targeted strategies can be deployed.

Dataset Information

A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses.

Publications

A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets