Background: Knowledge on predicting pulmonary tuberculosis (PTB) contagiosity in the hospital admission setting is limited. The objective was to assess clinical and radiological criteria to predict PTB contagiosity.

Methods: Retrospective analysis of 7 clinical, 4 chest X-ray (CXR) and 5 computed tomography (CT) signs in 299 PTB patients admitted to an urban tertiary hospital from 2008 to 2016. If the acid fact bacilli stain was positive (AFB+) on admission, the case was considered high contagiosity.

Results: Best predictors for high PTB contagiosity (AFB+) were haemoptysis (OR 4.33), cough (3.00), weight loss (2.96), cavitation in CT (2.75), cavitation in CXR (2.55), tree-in-bud-sign in CT (2.12), German residency of the patient (1.89), and abnormal auscultation findings (1.83). A previous TB infection reduced the risk of contagiosity statistically (0.40). Radiographic infiltrates, miliary picture, and pleural effusion were not helpful in predicting high or low contagiosity. 34% of all patients were clinically asymptomatic (20% of the highly contagious group, 50% of the low contagious group).

Conclusion: Haemoptysis, cough and weight loss as well as cavitation and tree-in-bud sign in CXR/CT can be helpful to predict PTB contagiosity and to improve PTB management.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10481505PMC
http://dx.doi.org/10.1186/s12890-023-02617-yDOI Listing

Publication Analysis

Top Keywords

ptb contagiosity
12
pulmonary tuberculosis
8
predict ptb
8
weight loss
8
ptb
6
contagiosity
5
clinical imaging
4
imaging factors
4
factors predict
4
predict contagiousness
4

Similar Publications

Background: Knowledge on predicting pulmonary tuberculosis (PTB) contagiosity in the hospital admission setting is limited. The objective was to assess clinical and radiological criteria to predict PTB contagiosity.

Methods: Retrospective analysis of 7 clinical, 4 chest X-ray (CXR) and 5 computed tomography (CT) signs in 299 PTB patients admitted to an urban tertiary hospital from 2008 to 2016.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!