Disseminated tuberculosis and diagnosis delay during the COVID-19 era in a Western European country: a case series analysis

Augmenting Radiological Diagnostics with AI for Tuberculosis and COVID-19 Disease Detection: Deep Learning Detection of Chest Radiographs

In this research, we introduce a network that can identify pneumonia, COVID-19, and tuberculosis using X-ray images of patients' chests. The study emphasizes tuberculosis, COVID-19, and healthy lung conditions, discussing how advanced neural networks, like VGG16 and ResNet50, can improve the detection of lung issues from images. To prepare the images for the model's input requirements, we enhanced them through data augmentation techniques for training purposes. We evaluated the model's performance by analyzing the precision, recall, and F1 scores across training, validation, and testing datasets. The results show that the ResNet50 model outperformed VGG16 with accuracy and resilience. It displayed superior ROC AUC values in both validation and test scenarios. Particularly impressive were ResNet50's precision and recall rates, nearing 0.99 for all conditions in the test set. On the hand, VGG16 also performed well during testing-detecting tuberculosis with a precision of 0.99 and a recall of 0.93. Our study highlights the performance of our deep learning method by showcasing the effectiveness of ResNet50 over traditional approaches like VGG16. This progress utilizes methods to enhance classification accuracy by augmenting data and balancing them. This positions our approach as an advancement in using state-of-the-art deep learning applications in imaging. By enhancing the accuracy and reliability of diagnosing ailments such as COVID-19 and tuberculosis, our models have the potential to transform care and treatment strategies, highlighting their role in clinical diagnostics.

Disseminated tuberculosis in a migrant child

Tuberculosis (TB) poses a major global health threat, substantially affecting children, who contribute notably to new cases and deaths. Diagnosing TB in kids is challenging due to collection issues and the paucibacillary nature of the disease. Disseminated TB, uncommon in children in low TB incidence countries, remains a significant cause of morbidity in migrant populations. We illustrate a rare case of disseminated TB in a middle-childhood boy who migrated from Angola to France, displaying chronic cough, fatigue, weight loss and persistent fever. Investigations revealed widespread TB affecting several organs (lungs, heart, bones and lymph nodes). Prompt diagnosis led to a treatment regimen of four antibiotics (isoniazid, rifampin, pyrazinamide, ethambutol) and corticosteroids, resulting in substantial improvement after 2 months. Subsequent treatment involved two antibiotics (isoniazid and rifampin) for 10 more months. This case underscores the criticality of early identification and comprehensive treatment for disseminated TB, ensuring improved outcomes and reduced risks.

Successful Management, in a Low-Resource Setting, of Disseminated Tuberculosis in a 3-Year Old Boy: A Case Report

Disseminated or military tuberculosis (TB) is defined as the presence of at least two non-contiguous sites of Mycobacterium tuberculosis, occurring as a result of progressive primary infection, reactivation and spread of a latent focus or due to iatrogenic origin. Disseminated TB represents a life-threatening condition, especially in at-risk children and when diagnosis and treatment are delayed. We report on a case of a 3-year old boy who presented with long-lasting unrecognised disseminated TB that was successfully managed in a low-resource setting.