The objective of the research under consideration was to augment early screening processes for hospitalised patients diagnosed with highly contagious tuberculosis (TB), thereby enabling effective isolation measures and curtailing the risk of TB spread. The study’s data set comprised 9458 TB patients who were newly diagnosed between 1 January 2015 and 31 December 2023 at a hospital dedicated to treating TB in Tianjin.
Patients were grouped into two categories, highly contagious and less contagious, based on their identity and comparative scale of infectiousness. Essential patient data, inclusive of clinical characteristics, as well as results of computerised tomography (CT) examinations, were compiled from hospital records, after which high-resolution chest CT examinations were conducted adhering to standardised protocols. A Receiver Operating Characteristic (ROC) curve analysis was conducted to determine the predictive value of the model.
Significant variances were discerned in sex, age (≥ 60), patient delay, and CT findings (cavitation, consolidation, tree-in-bud sign, bronchial lesions, pleural effusion, lymphadenopathy, and pericardial effusion) among the two patient groups. Multivariate logistic regression duly identified age ≥ 60 (odds ratio (OR) = 1.382), patient delay (OR = 1.830), cavitation (OR = 3.146), consolidation (OR = 2.077), tree-in-bud sign (OR = 2.764), and bronchial lesions (OR = 1.213) as independent risk factors for elevated infectiousness among TB patients. The ensuing ROC curve analysis displayed strong discriminative ability.
These findings highlight that factors such as age ≥ 60, patient delay, cavitation, consolidation, tree-in-bud sign, and bronchial lesions can effectively predict TB infectiousness among patients. These insights will aid early screening efforts and confinement measures, thus minimising the risk of TB dissemination within hospitals. Moreover, the study found that TB continues to pose a significant threat to public health, especially in high-burden countries. Hence, strategies including effective zoning measures for high and low infectious patients, are necessary to avert TB spread in hospitals.
The rigorous analysis of these comprehensive data streams is of high undoubted significance, providing essential insights with practical applications for the prevention of TB transmission within a hospital setting.
Source: https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-025-11763-z