Development of a clinical prediction rule for the diagnosis of pleural tuberculosis in Peru

Lely Solari, Alonso Soto, Patrick Van der Stuyft

    Research output: Contribution to journalA1: Web of Science-articlepeer-review

    3 Downloads (Pure)


    Objectives: To develop a clinical prediction rule (CPR) for the diagnosis of pleural tuberculosis (PT) in patients with pleural exudates in Peru.

    Methods: Clinical and laboratory information was collected from patients with exudative pleural effusion attending two reference hospitals in Lima, Peru. Predictive findings associated with PT in a multiple logistic regression model were used to develop the CPR. A definite diagnosis of PT was based on a composite reference standard including bacteriological and/or histological analysis of pleural fluid and pleural biopsy specimens.

    Results: A total of 238 patients were included in the analysis, of whom 176 had PT. Age, sex, previous contact with a TB patient, presence of lymphadenopathy, and pleural adenosine deaminase (ADA) levels were found to be independently associated with PT. These predictive findings were used to construct a CPR, for which the area under the receiver operating characteristics curve (AUC) was 0.92. The single best cut-off point was a score of >= 60 points, which had a sensitivity of 88%, specificity of 92%, a positive likelihood ratio of 10.9, and a negative likelihood ratio of 0.13.

    Conclusions: The CPR is accurate for the diagnosis of PT and could be useful for treatment initiation while avoiding pleural biopsy. A prospective evaluation is needed before its implementation in different settings. (C) 2018 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.

    Original languageEnglish
    JournalInternational Journal of Infectious Diseases
    Pages (from-to)103-107
    Number of pages5
    Publication statusPublished - 2018


    • Tuberculosis
    • Clinical prediction rules
    • Aadenosine deaminase
    • Pleural effusion
    • Peru
    • CANCER
    • NEEDLE
    • BIOPSY

    Cite this