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A clinical prediction rule for pulmonary tuberculosis in emergency departments

  • L. Solari
  • , C. Acuna-Villaorduna
  • , A. Soto
  • , J. Agapito
  • , F. Perez
  • , F. Samalvides
  • , J. Zegarra
  • , J. Diaz
  • , E. Gotuzzo
  • , P. Van Der Stuyft
  • Hospital Nacional Hipolito Unanue
  • Washington Hospital Center
  • Universidad Peruana Cayetano Heredia
  • Hospital Nacional Cayetano Heredia
  • Institute of Tropical Medicine

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

SETTING: University-affiliated hospital located in an area with a high incidence of pulmonary tuberculosis (PTB). OBJECTIVE: To develop a clinical prediction rule (CPR) based on information obtainable on admission, to permit rapid identification of patients with PTB. DESIGN: Information from patients with respiratory symptoms who attended the emergency department of Cayetano Heredia Hospital, Lima, Peru, was collected prospectively. Clinical symptoms, past medical history, demographic data and results of chest X-rays (CXRs), sputum smear and culture in Löwenstein-Jensen media were obtained. Based on logistic regression, we constructed a scoring system to predict PTB. RESULTS: A total of 345 patients were enrolled in the study, including 109 (31%) culture-proven PTB cases. In logistic regression analysis, we found age, previous history of PTB, weight loss, presence of cavities, upper lobe infiltrate and miliary pattern on CXR as independent predictors of PTB. We designed a scoring system with these variables, taking into account their statistical weight. The score attained 93% sensitivity and 42% specificity. CONCLUSION: The CPR that was developed performed well in our population. It merits further validation in other settings. It should not, however, replace, but should complement sputum microscopy when deciding on isolation, and it does not preclude microbiology in making a definitive diagnosis.

Original languageEnglish
Pages (from-to)619-624
Number of pages6
JournalInternational Journal of Tuberculosis and Lung Disease
Volume12
Issue number6
StatePublished - Jun 2008
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Clinical prediction rule
  • Emergency department
  • Isolation
  • Pulmonary tuberculosis
  • Score

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