Indian Journal of Tuberculosis最新文献

{"title":"Diagnostic accuracy of urine lipoarabinomannan in presumptive TB patients in South India – A cross-sectional study","authors":"Karthik Balasoupramaniane ,&nbsp;Dharm Prakash Dwivedi ,&nbsp;Vishnukanth Govindaraj ,&nbsp;Noyal Mariya Joseph ,&nbsp;Deepak Barathi ,&nbsp;Zeenath Alam Nadaf","doi":"10.1016/j.ijtb.2025.05.006","DOIUrl":"10.1016/j.ijtb.2025.05.006","url":null,"abstract":"<div><h3>Background</h3><div><span>Tuberculosis (TB) remains a major global health challenge, particularly in developing countries. Non-sputum diagnostic tools are the need of the hour for effective TB diagnosis, especially in paucibacillary and extrapulmonary cases. This study evaluated the diagnostic accuracy of urine </span>lipoarabinomannan (LAM) in presumptive TB patients in South India.</div></div><div><h3>Materials and methods</h3><div><span>The cross-sectional study, with a sample size of 94, was conducted between May 2022 and November 2023 in a tertiary teaching institute. Urine LAM was detected using ELISA<span>, and results were compared with MGIT liquid culture, GeneXpert, and </span></span>AFB smear. Chest X-ray scores were assessed using the Timika system. Diagnostic accuracy (sensitivity, specificity, PPV, NPV) and associations with disease severity (AFB smear grades, CXR scores) were analyzed.</div></div><div><h3>Results</h3><div><span>Urine LAM showed a sensitivity of 97.7 % and specificity of 38 % compared to MGIT<span> liquid culture. In confirmed TB cases (microbiologically and clinically diagnosed), sensitivity and specificity were 94.5 % and 80 %, respectively. Urine LAM outperformed AFB smear (61.36 % sensitivity) and GeneXpert (88.6 % sensitivity). In </span></span>extrapulmonary TB, urine LAM demonstrated 100 % sensitivity and NPV. Higher urine LAM levels correlated significantly with higher AFB smear grades (p &lt; 0.05).</div></div><div><h3>Conclusion</h3><div>Urine LAM ELISA demonstrated high sensitivity and NPV, making it a valuable screening test for TB, particularly in paucibacillary and extrapulmonary cases. Its association with higher AFB smear grades and chest X-ray scores suggests potential for assessing disease severity and treatment response. Further research using next-generation assays is needed to validate its diagnostic performance and suitability for point-of-care use.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 ","pages":"Pages S96-S101"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145692924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic performance of two commercial MPT64 assays for the identification of Mycobacterium tuberculosis complex from liquid culture","authors":"Koovakkat Rajendran Malavika,&nbsp;Kalaiarasan Ellappan,&nbsp;Noyal Mariya Joseph","doi":"10.1016/j.ijtb.2023.12.007","DOIUrl":"10.1016/j.ijtb.2023.12.007","url":null,"abstract":"<div><h3>Background</h3><div>Tuberculosis (TB) is a chronic infectious disease caused by bacteria of the <span><em>Mycobacterium</em><em> tuberculosis</em></span><span><span> complex (MTBC). Early diagnosis of TB is the most essential component to control TB. In this study, we evaluated the diagnostic performance of SD Bioline TB Ag MPT64 (SD Bioline) and BD </span>MGIT<span> TBc Identification (BD TBc ID) kits for the detection of MTBC from MGIT (Mycobacteria Growth Indicator Tube) 960 culture tube, positive for acid-fast bacilli (AFB).</span></span></div></div><div><h3>Methods</h3><div><span><span>A total of 198 AFB positive MGIT cultures [MTBC, 150 and non-tuberculous mycobacteria (NTM), 48] were collected during the study period (April 2021 to March 2023) and subjected to SD Bioline and BD TBc ID assays, respectively. All the 150 MTBC positive cultures were confirmed by </span>multiplex PCR targeting MPB64, protein B and IS6110 genes, and the 48 </span>NTM cultures were speciated by using line probe assays technique- Genotype Mycobacterium CM assay.</div></div><div><h3>Results</h3><div><span>SD Bioline and BD TBc ID kits detected all 150 MTBC strains correctly from MGIT positive cultures and no false negative was observed. However, there was one false positive for </span><em>M. abscessus</em> by SD Bioline and two false positive results for <em>M. abscessus</em> and <em>M. intracellulare</em> each by BD TBc ID. Overall, the sensitivity of both SD Bioline and BD TBc ID tests was 100 % and specificity was 97.9 % and 95.8 %, respectively.</div></div><div><h3>Conclusion</h3><div>Our results highlighted that SD Bioline and BD TBc ID assays played a promising role in the earlier identification of MTBC present in liquid culture and may act as a potential alternative to biochemical and expensive molecular techniques.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 ","pages":"Pages S18-S21"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145693487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence based modulation in diagnosis and management of tuberculosis","authors":"V.K. Arora (Chairman) ,&nbsp;Sanjay Rajpal (Director) ,&nbsp;Ankita Anand (Bacteriologist)","doi":"10.1016/j.ijtb.2025.11.022","DOIUrl":"10.1016/j.ijtb.2025.11.022","url":null,"abstract":"","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 ","pages":"Pages S1-S2"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing automated tuberculosis detection in chest radiographs through stable policy optimization with clipped objectives","authors":"Anup Gade ,&nbsp;Amol Bhoite ,&nbsp;Bharati P. Vasgi ,&nbsp;Anantha Reddy Dasari ,&nbsp;Maksadbek Babajanov ,&nbsp;Zamira Atamuratova","doi":"10.1016/j.ijtb.2025.11.009","DOIUrl":"10.1016/j.ijtb.2025.11.009","url":null,"abstract":"<div><div>Automated tuberculosis detection from chest radiographs is a fundamentally hard problem that arises from the imbalanced nature of data and weight of clinical misclassifications. In this work, we propose a novel optimization method named clipped Proximal Policy Optimization (PPO) for cost-sensitive sequential decision processing to enhance the computer-aided TB screening on chest X-rays. We first pretrain deep convolutional neural networks (DenseNet201 or ChexNet) via transfer learning on Z-score normalized 224 × 224 images and evaluate this model on binary TB classification. This is achieved in two steps: first, transforming the baseline classifier into a reinforcement learning (RL) agent for which actions correspond to decisions made by the diagnostician and for which the reward function explicitly penalizes false negatives and referrals that were not necessary. Comparative performance reveals the PPO-clipping improves over standard supervised learning as demonstrated by increased accuracy, F1-score, area under the ROC curve and reduced cumulative misclassification costs across held-out test images. Results of ablation experiments confirm that policy optimization results in more resource-efficient and robust diagnostics, particularly for high-stakes or imbalanced scenarios. Our results provide support for embedding clipped-objective RL as a component of deep radiographic classification pipelines to improve safety and clinical viability of TB triage.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 ","pages":"Pages S77-S83"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing semi-supervised graph-based learning to advance automated bacilli detection in digital tuberculosis microscopy with limited expert annotations","authors":"Pragati Pandit ,&nbsp;Sanjay Thorat ,&nbsp;Shilpy singh ,&nbsp;Sejal D'mello ,&nbsp;Geeta Padole Gaikwad ,&nbsp;Raykhan Razakova ,&nbsp;Yunus Jumaniyozov","doi":"10.1016/j.ijtb.2025.11.017","DOIUrl":"10.1016/j.ijtb.2025.11.017","url":null,"abstract":"<div><div>Automated acid-fast bacilli (AFB) detection with digital microscopy is important for the improvement of tuberculosis diagnosis in communities or populations where expert annotations are not available. In this paper, we propose a semi-supervised graph-based learning approach with label spreading and effectively make use of both the small number of labeled images and the huge collection of unlabeled high-resolution smear microscopy images. The approaches diffuse label evidence over graph-derived representations of the images and use smooth diffusion-over-graph algorithms with soft constraints to alleviate error propagated by standard methods. The experimental results show that this framework can robustly and precisely localize bacilli, which is highly competitive overall accuracy and F1-score even with limited expert annotation. These findings demonstrate that the method is applicable to rapid, scalable AI-powered tuberculosis diagnosis in low-resource settings and suggest a role for semi-supervised learning in reducing manual annotation requirements while enabling digital pathology workflows.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 ","pages":"Pages S151-S158"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145750375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based early detection of tuberculosis in asymptomatic high-risk populations","authors":"Hrushikesh Jaiwant Joshi ,&nbsp;Minal Barhate ,&nbsp;Kiran Prabhakar More ,&nbsp;Deepa Abin ,&nbsp;Ravindra Murumkar ,&nbsp;Viomesh Kumar Singh","doi":"10.1016/j.ijtb.2025.10.005","DOIUrl":"10.1016/j.ijtb.2025.10.005","url":null,"abstract":"<div><div>Tuberculosis (TB) remains a major global health challenge and continues to affect millions worldwide despite decades of control efforts. The disease can remain dormant and symptom-free for long periods, especially in high-risk populations such as household contacts, immunocompromised individuals and people living in crowded environments. Delayed detection of these silent cases fuels ongoing transmission. Chest X-ray imaging is widely used for screening, yet radiographic signs in early TB are subtle and easily confused with other lung conditions. Shortage of trained radiologists, subjective interpretation and limited data further complicate diagnosis. Recent advances in deep learning have enabled automated detection, but conventional convolutional neural networks often require large labelled datasets and struggle to capture global context in images. This paper proposes a machine-learning framework that combines contrastive pretraining with a fine-tuned vision transformer (CPT-TB) for early detection of TB in asymptomatic, high-risk populations. We utilize the publicly available chest X-ray dataset which contains 4200 images, including 3500 normal X-rays and 700 images from TB patients. Contrastive pretraining leverages unlabeled images by creating multiple augmented views and learning representations that bring similar views closer while pushing dissimilar examples apart. A transformer architecture with self-attention is then fine-tuned on the labelled portion of the dataset. The attention mechanism aggregates information across the entire lung field, capturing subtle pathological patterns that are difficult for CNNs to learn. Our method demonstrates significant improvements over standard models. In five-fold cross-validation, CPT-TB achieves an area under the receiver operating characteristic curve (AUC) of 98.2 %, accuracy of 95.5 %, sensitivity of 94.9 % and specificity of 96.0 %. These results represent a 4.0 % increase in accuracy compared to a supervised ResNet-50 baseline and a 2.3 % improvement over a supervised vision transformer. Beyond these quantitative gains, attention maps offer interpretable visual cues for clinicians. The proposed CPT-TB framework shows promise for scalable, non-invasive screening and could facilitate active case finding in resource-constrained settings where radiological expertise is scarce.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 ","pages":"Pages S3-S10"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From data to decisions: Statistical tools and Artificial Intelligence in tuberculosis Operational Research","authors":"V.K. Arora ,&nbsp;Nishi Aggarwal ,&nbsp;Sanjay Rajpal","doi":"10.1016/j.ijtb.2025.09.001","DOIUrl":"10.1016/j.ijtb.2025.09.001","url":null,"abstract":"<div><h3>Background</h3><div>Tuberculosis (TB) remains a major public health challenge, especially in low- and middle-income countries. Operational Research (OR), supported by robust statistical methods, plays a critical role in optimizing TB control strategies.</div></div><div><h3>Objective</h3><div>This review highlights the statistical tools applied in TB Operational Research, their applications, and the emerging role of Artificial Intelligence (AI) in strengthening data-driven decision-making.</div></div><div><h3>Methods</h3><div>We examine classical statistical approaches alongside predictive modeling, cost-effectiveness analysis, and AI-based frameworks. Case examples from diverse settings illustrate their practical impact.</div></div><div><h3>Findings</h3><div>Statistical methods underpin surveillance, diagnosis, treatment evaluation, and policy modeling in TB programs. AI-driven techniques, such as machine learning and deep learning, are expanding the analytical landscape by enhancing prediction, identifying high-risk populations, and enabling real-time program monitoring.</div></div><div><h3>Conclusion</h3><div>Statistical tools from traditional inference to AI-modeling are essential for advancing TB control. Strengthening methodological rigor, reporting standards and interdisciplinary collaboration will be pivotal in harnessing data for effective TB elimination strategies.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 4","pages":"Pages 455-459"},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145103102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Macrophage profiles in drug-resistant tuberculosis patients and their close contacts: A pilot study","authors":"Diah Handayani ,&nbsp;Muhammad Faris Indratmo ,&nbsp;Ardiana Kusumaningrum ,&nbsp;Ahmad Fadhil Ilham ,&nbsp;Febriana Catur Iswanti ,&nbsp;Mohamad Sadikin","doi":"10.1016/j.ijtb.2025.07.004","DOIUrl":"10.1016/j.ijtb.2025.07.004","url":null,"abstract":"<div><div><span>Macrophages play a key role in controlling tuberculosis infection<span>. This pilot study aimed to analyze the macrophage profile in drug-resistant tuberculosis patients compared to a group of close contacts diagnosed with latent infection and a group of healthy. The Interferon Gamma Release Assay (IGRA) was tested on the close contact group to determine their infection status. PBMCs were cultured using RPMI 1640 medium with M-CSF and autologous serum, incubated for 7 days at 37</span></span>^oC with 5 % CO₂<span> Incubator. Macrophage profiles were analyzed using the flow cytometry technique with CD68</span>⁺<span>, CD80</span>⁺, CD206⁺<span> markers, and the cytokine profiles were analyzed using multiplex immunoassay. The results of the IGRA showed that of the 18 close contact subjects, 8 subjects (44.4 %) were declared latent infected (LTBI) and 10 subjects (55.6 %) were declared healthy. The results showed that the macrophage population exhibit CD206</span>⁺<span> expression in each group, which showed a tendency for macrophages toward the M2 type (Kruskal-Wallis, p &gt; 0.05). Cytokine examination showed high IL-10 levels in each group (Kruskal-Wallis, p &gt; 0.05). This research is expected to provide information regarding the characteristics of macrophages as components of innate immune cells which have an important role in tuberculosis infection.</span></div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 4","pages":"Pages 540-546"},"PeriodicalIF":0.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145103134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A synthesis of qualitative evidences regarding the barriers, challenges, and facilitators of self-care management among individuals with tuberculosis: A narrative review","authors":"Pushpa Choudhary ,&nbsp;Uma Phalswal ,&nbsp;Mamta","doi":"10.1016/j.ijtb.2024.12.003","DOIUrl":"10.1016/j.ijtb.2024.12.003","url":null,"abstract":"<div><div>Many people identify tuberculosis as a complex disease that requires a wide range of restrictions, lifestyle changes, and behavioral changes. Well-managed tuberculosis necessitates specific self-care management behaviors to not only control the disease but also prevent drug resistance and future complications. This narrative review summarizes barriers, challenges, and facilitators related to self-care management among individuals with tuberculosis. We conducted a literature search using keywords and MeSH terminologies from the databases PubMed, Scopus, and CINAHL. We also performed a manual search of the references listed in the articles selected for review. Several barriers, challenges, and facilitators surround the self-care management of tuberculosis (TB). Barriers such as psychological factors (social isolation, shame, discrimination), treatment-related factors, healthcare system limitations, economic confrontation, and a knowledge-awareness gap hinder self-care management among TB patients. However, there are few facilitators to assist the individual in adhering to self-care management of tuberculosis, such as patient-Centred support, community and family engagement, technological and logistical innovations, enhanced knowledge and advocacy, and government and policy interventions. The efforts to remove obstacles are excellent, aiding individuals in improving their quality of life and achieving positive outcomes.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 3","pages":"Pages 418-423"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structure and mechanism basis of β-lactam activity against Mycobacterium tuberculosis: A review of literature","authors":"Nazia Ahmad ,&nbsp;Zeyaul Islam ,&nbsp;Sohan Dhar ,&nbsp;Pankaj Kumar ,&nbsp;Rana Zaidi","doi":"10.1016/j.ijtb.2025.01.001","DOIUrl":"10.1016/j.ijtb.2025.01.001","url":null,"abstract":"<div><div>Tuberculosis (TB), caused by the infectious agent <em>Mycobacterium tuberculosis</em> (<em>Mtb</em>), has resulted in the highest mortality rates, even surpassing HIV/AIDS. The rise of Drug-resistant TB has worsened the health crisis and urgently requires new treatment approaches. The WHO has approved the repurposing of β-lactam in combination with β-lactamase (BlaC) inhibitor for treating MDR/XDR-TB. Numerous targets of β lactams present in the Mtb's cell wall are involved in its structural cytoskeleton, peptidoglycan (PG) biosynthesis. Delving into the mechanistic basis of β-lactam activity against <em>Mtb</em> has become a holistic approach towards developing new kinds of β-lactams and ß-lactamase-inhibitors against <em>Mtb</em>. This work comprehensively reviews the literature-landscape of the structure and mechanism of β-lactams binding to different PG enzymes and the β-lactamase inhibitors that can inhibit BlaC in <em>Mtb</em>.</div></div>","PeriodicalId":39346,"journal":{"name":"Indian Journal of Tuberculosis","volume":"72 3","pages":"Pages 424-437"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}