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Pediatr Infect Dis J. 2012 Apr;31(4):347-52. doi: 10.1097/INF.0b013e318243e27b.

A proposed comprehensive classification of tuberculosis disease severity in children.

Author information

1
Desmond Tutu TB Centre, Department of Pediatrics and Child Health, Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa. dommisse@sun.ac.za

Abstract

BACKGROUND:

Tuberculosis (TB) in children has conventionally been classified as pulmonary TB (PTB) and extrapulmonary TB (EPTB) disease, including disseminated TB (TB meningitis and miliary disease). There is no existing approach that comprehensively characterizes the spectrum and severity of pediatric TB. This limits accurate classification of patients and comparison across cohorts.

AIMS:

To develop a classification of pediatric TB that reflects the spectrum and severity of clinical disease better than currently available approaches.

METHODS:

We propose a framework for the standard classification of TB disease severity in children. From a literature search, the following sources of information were used: clinical data, bacteriologic, histopathologic, and imaging data (including information from chest radiography, computerized tomography, and bronchoscopy). Each individual disease entity was systematically considered. Based on the extent and the presence of complications, each entity was then classified as "severe" or "nonsevere." As an initial application, we compared the proposed classification with the convention (PTB, EPTB) in a cohort of HIV-infected and -uninfected infants with culture-confirmed TB. Agreement between the 2 systems was poor.

CONCLUSIONS:

The proposed comprehensive disease classification system may more accurately reflect the clinical TB disease spectrum in children, is relevant to clinical management, and may be valuable to inform research on diagnostic tools and TB treatment strategies in children. Prospective studies are required to evaluate this approach in representative pediatric populations, correlating TB disease severity with diagnostic yield, treatment response, and application in existing and novel treatment strategies.

PMID:
22315002
DOI:
10.1097/INF.0b013e318243e27b
[Indexed for MEDLINE]

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