About: Discriminating Active from Latent Tuberculosis in Patients Presenting to Community Clinics

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Discriminating Active from Latent Tuberculosis in Patients Presenting to Community Clinics
Creator	Athanasakis, Dimitrios Battaglia, Francesca Fernandez-Reyes, Delmiro Montoya, Rosario Sandhu, Gurjinder Valencia, Teresa Agranoff, Daniel Ely, Barry Evans, Carlton Friedland, Jon Gilman, Robert
topic	covid:906902ba01987282a83ec42c2776de9c9bde3834#this
source	PMC
abstract	BACKGROUND: Because of the high global prevalence of latent TB infection (LTBI), a key challenge in endemic settings is distinguishing patients with active TB from patients with overlapping clinical symptoms without active TB but with co-existing LTBI. Current methods are insufficiently accurate. Plasma proteomic fingerprinting can resolve this difficulty by providing a molecular snapshot defining disease state that can be used to develop point-of-care diagnostics. METHODS: Plasma and clinical data were obtained prospectively from patients attending community TB clinics in Peru and from household contacts. Plasma was subjected to high-throughput proteomic profiling by mass spectrometry. Statistical pattern recognition methods were used to define mass spectral patterns that distinguished patients with active TB from symptomatic controls with or without LTBI. RESULTS: 156 patients with active TB and 110 symptomatic controls (patients with respiratory symptoms without active TB) were investigated. Active TB patients were distinguishable from undifferentiated symptomatic controls with accuracy of 87% (sensitivity 84%, specificity 90%), from symptomatic controls with LTBI (accuracy of 87%, sensitivity 89%, specificity 82%) and from symptomatic controls without LTBI (accuracy 90%, sensitivity 90%, specificity 92%). CONCLUSIONS: We show that active TB can be distinguished accurately from LTBI in symptomatic clinic attenders using a plasma proteomic fingerprint. Translation of biomarkers derived from this study into a robust and affordable point-of-care format will have significant implications for recognition and control of active TB in high prevalence settings.
has issue date	2012-05-30(xsd:dateTime)
bibo:doi	10.1371/journal.pone.0038080
bibo:pmid	22666453
has license	cc-by
sha1sum (hex)	906902ba01987282a83ec42c2776de9c9bde3834
schema:url	https://doi.org/10.1371/journal.pone.0038080
resource representing a document's title	Discriminating Active from Latent Tuberculosis in Patients Presenting to Community Clinics
has PubMed Central identifier	PMC3364185
has PubMed identifier	22666453
schema:publication	PLoS One
resource representing a document's body	covid:906902ba01987282a83ec42c2776de9c9bde3834#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/906902ba01987282a83ec42c2776de9c9bde3834
is schema:about of	named entity 'USED' named entity 'DISEASE STATE' named entity 'ACCURATE' named entity 'ACTIVE' named entity 'RESOLVE' named entity 'PREVALENCE' named entity 'INFECTION' named entity 'DIAGNOSTICS' named entity 'PROTEOMIC' named entity 'BUT' named entity 'patients' named entity 'settings' named entity 'Patients' named entity 'KEY' named entity 'DIFFICULTY' named entity 'MOLECULAR' named entity 'FINGERPRINTING' named entity 'CURRENT' named entity 'DISTINGUISHING' named entity 'CLINICAL SYMPTOMS' named entity 'CLINICS' named entity 'COMMUNITY' named entity 'PRESENTING' named entity 'ACTIVE' named entity 'LATENT TUBERCULOSIS' named entity 'PATIENTS' named entity 'DEFINING' named entity 'ENDEMIC' named entity 'HIGH' named entity 'LTBI' named entity 'POINT-OF-CARE' named entity 'SNAPSHOT' named entity 'GLOBAL' named entity 'METHODS' named entity 'PROVIDING' named entity 'PATIENTS' named entity 'OVERLAPPING' named entity 'LATENT' named entity 'SETTINGS' named entity 'PLASMA' named entity 'CHALLENGE' named entity 'BACKGROUND' covid:arg/906902ba01987282a83ec42c2776de9c9bde3834 named entity 'resolve' named entity 'high' named entity 'Plasma' named entity 'active' named entity 'Clinics' named entity 'latent TB' named entity 'infection' named entity 'prevalence' named entity 'point-of-care' named entity 'plasma' named entity 'area under the curve' named entity 'latent infection' named entity 'infection' named entity 'confounding' named entity 'kDa' named entity 'Lima, Peru' named entity 'HIV' named entity 'fractionated plasma' named entity 'PCA' named entity 'pathophysiological' named entity '85%' named entity 'toxicity' named entity 'peptides' named entity 'clinical symptoms' named entity 'endemic areas' named entity 'proteomic'

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