Tuberculosis (TB) remains a leading cause of morbidity and mortality worldwide, with children representing a particularly vulnerable population in whom diagnosis is often challenging. Pediatric TB is typically paucibacillary and presents with non-specific clinical manifestations, limiting the sensitivity of microbiological confirmation and increasing reliance on immunological tests. The Tuberculin Skin Test (TST) and Interferon-Gamma Release Assays (IGRAs) are the most widely used tools for detecting Mycobacterium tuberculosis infection, yet both have important limitations, especially in young children and in Bacillus Calmette–Guérin (BCG)-vaccinated populations. TST lacks specificity due to cross-reactivity with BCG and environmental mycobacteria, while IGRAs, although more specific, require laboratory infrastructure and may have reduced sensitivity in early childhood. The Tuberculosis Skin Test (TBST), based on M. tuberculosis-specific antigens such as ESAT-6 and CFP-10, has emerged as a promising alternative that combines the operational simplicity of TST with the antigenic specificity of IGRA. This paper reviews the immunological principles, diagnostic performance, and practical considerations of TBST in pediatric populations, with direct comparison to TST and IGRA. Evidence from recent studies suggests that TBST may offer improved specificity over TST, with broadly comparable diagnostic accuracy to IGRA in some settings, although findings are not fully consistent across studies. Particular attention is given to its performance in BCG-vaccinated children and, based on emerging evidence, in those under five years of age. The potential role of TBST in clinical algorithms and public health strategies is discussed, along with current evidence gaps and future research priorities.

Background: Pediatric pleural empyema is a major complication of community-acquired pneumonia and remains associated with substantial morbidity despite advances in vaccination, antimicrobial therapy, and supportive care. Intrapleural fibrinolytic therapy has become an important minimally invasive treatment for complicated parapneumonic effusions and empyema, but uncertainty persists regarding the optimal fibrinolytic agent, treatment protocols, patient selection, and indications for surgical intervention. Methods: A narrative review of the literature was conducted to summarize current evidence on the use of intrapleural fibrinolytic therapy in pediatric pleural empyema. Experimental studies, randomized controlled trials, observational studies, systematic reviews, meta-analyses, and international clinical practice guidelines were critically reviewed. Particular attention was paid to the biological rationale for fibrinolysis, pharmacological characteristics of available agents, comparative effectiveness with video-assisted thoracoscopic surgery (VATS), practical treatment protocols, safety, and future research priorities. Results: Intrapleural fibrinolysis effectively improves pleural drainage by lysing fibrin septations during the fibrinopurulent stage of empyema and is associated with shorter hospitalization compared with chest-tube drainage alone. Urokinase remains the fibrinolytic agent supported by the highest-quality pediatric randomized evidence, whereas alteplase has demonstrated favorable outcomes in observational studies and randomized comparisons with VATS. Current evidence indicates comparable clinical outcomes between fibrinolysis and primary VATS in appropriately selected children, although fibrinolysis is generally associated with lower treatment costs and avoidance of surgery in most patients. Conventional-dose fibrinolytic therapy has an acceptable safety profile, with clinically significant bleeding reported only rarely. Current pediatric evidence does not support the routine addition of DNase to tissue plasminogen activator. Conclusions: Intrapleural fibrinolytic therapy represents a safe, effective, and minimally invasive first-line treatment for most children with complicated parapneumonic effusions and pleural empyema requiring drainage. Management should be individualized within a multidisciplinary framework, integrating timely diagnosis, image-guided pleural drainage, appropriate antimicrobial therapy, and selective surgical intervention. Future multicenter studies are needed to optimize fibrinolytic protocols, validate predictive biomarkers, and further standardize clinical management.

Background: Pediatric pleural empyema is a major complication of community-acquired pneumonia and remains associated with substantial morbidity despite advances in vaccination, antimicrobial therapy, and supportive care. Intrapleural fibrinolytic therapy has become an important minimally invasive treatment for complicated parapneumonic effusions and empyema, but uncertainty persists regarding the optimal fibrinolytic agent, treatment protocols, patient selection, and indications for surgical intervention. Methods: A narrative review of the literature was conducted to summarize current evidence on the use of intrapleural fibrinolytic therapy in pediatric pleural empyema. Experimental studies, randomized controlled trials, observational studies, systematic reviews, meta-analyses, and international clinical practice guidelines were critically reviewed. Particular attention was paid to the biological rationale for fibrinolysis, pharmacological characteristics of available agents, comparative effectiveness with video-assisted thoracoscopic surgery (VATS), practical treatment protocols, safety, and future research priorities. Results: Intrapleural fibrinolysis effectively improves pleural drainage by lysing fibrin septations during the fibrinopurulent stage of empyema and is associated with shorter hospitalization compared with chest-tube drainage alone. Urokinase remains the fibrinolytic agent supported by the highest-quality pediatric randomized evidence, whereas alteplase has demonstrated favorable outcomes in observational studies and randomized comparisons with VATS. Current evidence indicates comparable clinical outcomes between fibrinolysis and primary VATS in appropriately selected children, although fibrinolysis is generally associated with lower treatment costs and avoidance of surgery in most patients. Conventional-dose fibrinolytic therapy has an acceptable safety profile, with clinically significant bleeding reported only rarely. Current pediatric evidence does not support the routine addition of DNase to tissue plasminogen activator. Conclusion: Intrapleural fibrinolytic therapy represents a safe, effective, and minimally invasive first-line treatment for most children with complicated parapneumonic effusions and pleural empyema requiring drainage. Management should be individualized within a multidisciplinary framework, integrating timely diagnosis, image-guided pleural drainage, appropriate antimicrobial therapy, and selective surgical intervention. Future multicenter studies are needed to optimize fibrinolytic protocols, validate predictive biomarkers, and further standardize clinical management.

Background: Antimicrobial resistance (AMR) is a major global health threat, while conventional diagnostic, stewardship, dosing, and drug-development strategies remain limited by diagnostic delays, population-level decision-making, and a shrinking antibiotic pipeline. Artificial intelligence (AI) may help address these gaps by integrating complex clinical, microbiological, genomic, pharmacological, and chemical data. Methods: We conducted a narrative review of English-language publications issued between January 2010 and March 2026. PubMed/MEDLINE, Scopus, and Web of Science were searched using terms related to AI, machine learning, AMR, antimicrobial stewardship, diagnosis, susceptibility prediction, antibiotic dosing, pharmacokinetics, pharmacodynamics, and antibiotic discovery. ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform, and ISRCTN were additionally searched on 27 August 2026 for prospective interventional studies registered or publicly available by 31 March 2026. Results: AI-based systems demonstrated promising performance in differentiating bacterial from viral infections, predicting bacteremia and sepsis, enhancing matrix-assisted laser desorption/ionization time-of-flight interpretation, estimating antimicrobial susceptibility, supporting individualized empirical therapy, optimizing antibiotic dosing, and accelerating compound discovery. However, external and temporal validation frequently produced substantially poorer performance than internal validation. In representative resistance-prediction studies, AUROC declined from 0.94 internally to 0.55 during temporally independent external validation and by 0.10–0.25 over 18 months. Moreover, only six eligible prospective interventional studies were identified across the four domains examined: two concerning AI-assisted diagnosis or antibiotic-use decisions, three concerning resistance prediction or stewardship, one concerning model-informed precision dosing, and none concerning AI-assisted antibiotic discovery. Conclusions: Current evidence demonstrates that AI can generate technically promising predictions, but it does not yet establish consistent clinical or economic benefit. Discrimination alone is insufficient to demonstrate clinical usefulness. Prospective multicenter trials, clinically meaningful outcome measures, external validation, continuous monitoring for model drift, and formal implementation and cost-effectiveness evaluations are required before widespread adoption.

Background: Antimicrobial resistance (AMR) is a major global health threat, while conventional diagnostic, stewardship, dosing, and drug-development strategies remain limited by diagnostic delays, population-level decision-making, and a shrinking antibiotic pipeline. Artificial intelligence (AI) may help address these gaps by integrating complex clinical, microbiological, genomic, pharmacological, and chemical data. Methods: We conducted a narrative review of English-language publications issued between 1 January 2010 and 27 August 2026. PubMed/MEDLINE, Scopus, and Web of Science were searched using a prespecified combination of terms related to AI, machine learning, AMR, diagnosis, susceptibility prediction, antimicrobial stewardship, precision dosing, pharmacokinetics, pharmacodynamics, and antibiotic discovery. A separate structured search of ClinicalTrials.gov, the World Health Organization International Clinical Trials Registry Platform, and ISRCTN was performed on 27 August 2026 to identify prospective interventional studies. Results: AI-based systems demonstrated promising performance in differentiating bacterial from viral infections, predicting bacteremia and sepsis, enhancing matrix-assisted laser desorption/ionization time-of-flight interpretation, estimating antimicrobial susceptibility, supporting individualized empirical therapy, optimizing antibiotic dosing, and accelerating compound discovery. However, external and temporal validation frequently produced substantially poorer performance than internal validation. In representative resistance-prediction studies, AUROC declined from 0.94 internally to 0.55 during temporally independent external validation and by 0.10–0.25 over 18 months. Moreover, the structured registry search identified five prospective interventional studies of AI-based applications and one additional randomized study of conventional model-informed precision dosing. Conclusions: Current evidence demonstrates that AI can generate technically promising predictions, but it does not yet establish consistent clinical or economic benefit. Discrimination alone is insufficient to demonstrate clinical usefulness. Prospective multicenter trials, clinically meaningful outcome measures, external validation, continuous monitoring for model drift, and formal implementation and cost-effectiveness evaluations are required before widespread adoption.

Background: Pediatric tuberculosis (TB) remains a major global health concern, accounting for a substantial proportion of TB-related morbidity and mortality worldwide. Treatment in children is particularly challenging due to age-specific pharmacokinetics, difficulties in drug administration, poor palatability, and reliance on caregivers for adherence. Objectives: This narrative review aims to evaluate the advantages and limitations of fixed-dose combinations (FDCs) in the treatment of pediatric TB, with a focus on adherence, pharmacological considerations, clinical outcomes, and implementation challenges. Methods: A narrative review of the literature was conducted, including clinical studies, pharmacokinetic analyses, programmatic data, and international guidelines related to the use of FDCs in pediatric TB management. Results: Evidence indicates that pediatric FDCs significantly improve treatment adherence by reducing pill burden and simplifying dosing regimens. They also decrease the risk of medication errors and inadvertent monotherapy, thereby contributing to the prevention of drug resistance. The availability of dispersible, child-friendly formulations has enhanced acceptability and ease of administration. However, limitations persist, including reduced flexibility in dose individualization, challenges in identifying the causative agent in adverse drug reactions, and variable access across settings. Pharmacokinetic concerns, particularly regarding rifampicin exposure, have been addressed in newer WHO-recommended formulations. Conclusions: FDCs represent a critical advancement in pediatric TB management and are strongly supported by international guidelines. Further research is needed to optimize formulations, ensure equitable access, and evaluate long-term clinical outcomes in diverse pediatric populations.