The prevalence of symptoms associated with pulmonary tuberculosis in randomly selected children from a high burden

B J Marais1, C C Obihara, R P Gie

  • 1Department of Paediatrics and Child Health, Centre for TB Research and Education (CENTRE), Faculty of Health Sciences, Stellenbosch University, Cape Town, South Africa. bjmarais@sun.ac.za

Insights

Diagnosing childhood tuberculosis is challenging. Common symptoms like cough were not reliable indicators for identifying tuberculosis in children in a high-burden community, with many diagnosed children showing no symptoms.

Area of Science:

  • Pediatrics
  • Infectious Diseases
  • Public Health

Background:

  • Childhood tuberculosis diagnosis is difficult, especially in high-burden areas.
  • Symptom-based approaches are common but their effectiveness is debated.
  • This study investigated symptom prevalence and diagnostic utility in a high-burden community.

Purpose of the Study:

  • To determine the frequency of tuberculosis-associated symptoms in children in a high-burden setting.
  • To compare symptom prevalence between children with and without tuberculosis.
  • To assess the diagnostic value of symptoms for childhood tuberculosis.

Main Methods:

  • A cross-sectional, community-based survey involving a random sample of households.
  • Symptom questionnaires and tuberculin skin tests (TST) were administered to all children.
  • Chest radiographs were obtained based on national guidelines.

Main Results:

  • Out of 1415 children, 18 (1.3%) were diagnosed with tuberculosis; 451 (31.9%) were TST positive.
  • Weight loss (OR=4.5) and the combination of cough and weight loss (OR=5.4) were significant indicators.
  • 50% of children with newly diagnosed tuberculosis reported no symptoms.

Conclusions:

  • Symptoms commonly reported by children in this high-burden community had limited ability to distinguish tuberculosis cases.
  • Relying solely on symptoms can be misleading for diagnosing childhood tuberculosis.
  • Enhanced case definitions and symptom characterization are crucial for improving diagnostic accuracy.
Abstract

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