Background: Early oral switch (EOS) has been proposed as an alternative to prolonged intravenous (IV) therapy for Enterobacterales bacteremia; however, its safety and effectiveness have not been clearly established. This systematic review and meta-analysis evaluated whether EOS reduces treatment failure in uncomplicated Enterobacterales bacteremia and examined how the timing of switching affects outcomes. Methods: We conducted a systematic review and random-effects meta-analysis of randomized controlled trials and observational studies that compared EOS with continued IV therapy in adults with uncomplicated Enterobacterales bacteremia. Pooled risk ratios (RRs) with 95% confidence intervals (CIs) were calculated using random-effects models. The primary outcome was treatment failure by ≤90 days. Prespecified analyses evaluated the timing of the switch. Results: Across 10 studies that met the inclusion criteria, EOS was associated with lower treatment failure than continued IV therapy (RR, 0.72; 95% CI, 0.58–0.89; I²=26%). Switching within 4 days reduced the failure (RR, 0.58; 95% CI, 0.44–0.76; I²=0%), whereas switching after 4 days showed no clear advantage (RR, 0.87; 95% CI, 0.71–1.06; I²=0%). No evidence of small study effects was observed. Conclusion EOS was associated with a lower risk of treatment failure than prolonged IV therapy, with the greatest benefit observed when the switch occurred within 4 days. These findings should be interpreted with clinical caution given that most of the evidence is observational.

The coronavirus disease 2019 pandemic has underscored the limitations of traditional diagnostic methods, particularly in ensuring the safety of healthcare workers and patients during infectious outbreaks. Smartphone-based digital stethoscopes enhanced with artificial intelligence (AI) have emerged as potential tools for addressing these challenges by enabling remote, efficient, and accessible auscultation. Despite advancements, most existing systems depend on additional hardware and external processing, increasing costs and complicating deployment. This review examines the feasibility and limitations of smartphone-based digital stethoscopes powered by AI, focusing on their ability to perform real-time analyses of audible and inaudible sound frequencies. We also explore the regulatory barriers, data storage challenges, and diagnostic accuracy issues that must be addressed to facilitate broader adoption. The implementation of these devices in veterinary medicine is discussed as a practical step toward refining their applications. With targeted improvements and careful consideration of existing limitations, smartphone-based AI stethoscopes could enhance diagnostic capabilities in human and animal healthcare settings.

The coronavirus disease 2019 pandemic has underscored the limitations of traditional diagnostic methods, particularly in ensuring the safety of healthcare workers and patients during infectious outbreaks. Smartphone-based digital stethoscopes enhanced with artificial intelligence (AI) have emerged as potential tools for addressing these challenges by enabling remote, efficient, and accessible auscultation. Despite advancements, most existing systems depend on additional hardware and external processing, increasing costs and complicating deployment. This review examines the feasibility and limitations of smartphone-based digital stethoscopes powered by AI, focusing on their ability to perform real-time analyses of audible and inaudible sound frequencies. We also explore the regulatory barriers, data storage challenges, and diagnostic accuracy issues that must be addressed to facilitate broader adoption. The implementation of these devices in veterinary medicine is discussed as a practical step toward refining their applications. With targeted improvements and careful consideration of existing limitations, smartphone-based AI stethoscopes could enhance diagnostic capabilities in human and animal healthcare settings.

The coronavirus disease 2019 pandemic has underscored the limitations of traditional diagnostic methods, particularly in ensuring the safety of healthcare workers and patients during infectious outbreaks. Smartphone-based digital stethoscopes enhanced with artificial intelligence (AI) have emerged as potential tools for addressing these challenges by enabling remote, efficient, and accessible auscultation. Despite advancements, most existing systems depend on additional hardware and external processing, increasing costs and complicating deployment. This review examines the feasibility and limitations of smartphone-based digital stethoscopes powered by AI, focusing on their ability to perform real-time analyses of audible and inaudible sound frequencies. We also explore the regulatory barriers, data storage challenges, and diagnostic accuracy issues that must be addressed to facilitate broader adoption. The implementation of these devices in veterinary medicine is discussed as a practical step toward refining their applications. With targeted improvements and careful consideration of existing limitations, smartphone-based AI stethoscopes could enhance diagnostic capabilities in human and animal healthcare settings.

The coronavirus disease 2019 pandemic has underscored the limitations of traditional diagnostic methods, particularly in ensuring the safety of healthcare workers and patients during infectious outbreaks. Smartphone-based digital stethoscopes enhanced with artificial intelligence (AI) have emerged as potential tools for addressing these challenges by enabling remote, efficient, and accessible auscultation. Despite advancements, most existing systems depend on additional hardware and external processing, increasing costs and complicating deployment. This review examines the feasibility and limitations of smartphone-based digital stethoscopes powered by AI, focusing on their ability to perform real-time analyses of audible and inaudible sound frequencies. We also explore the regulatory barriers, data storage challenges, and diagnostic accuracy issues that must be addressed to facilitate broader adoption. The implementation of these devices in veterinary medicine is discussed as a practical step toward refining their applications. With targeted improvements and careful consideration of existing limitations, smartphone-based AI stethoscopes could enhance diagnostic capabilities in human and animal healthcare settings.

Vaccination has played a central role in the historical and modern fight against infectious diseases. This review explores the evolution of infectious disease perception from ancient humoral theories to the modern “One Health” framework, reflecting the integration of environmental, animal, and human health. Vaccines have not only reduced morbidity and mortality but have also provided profound economic and developmental benefits across societies. Climate change, antimicrobial resistance, and the rapid emergence of new infectious threats have prompted innovations in vaccine technologies, including messenger RNA, DNA, viral vector, and nanoparticle-based platforms. These advances support personalized vaccine strategies, such as vaccinomics, and extend their application to noncommunicable diseases, including cancer and Alzheimer disease. Despite their success, vaccines face challenges including global access disparities, waning immunity, pathogen evolution, and vaccine hesitancy. Nonetheless, vaccination remains a cornerstone of global health security, with strong returns on investment and crucial roles in socioeconomic stabilization during pandemics. Future vaccine strategies must integrate technological innovation with equitable access and public trust, for instance, through global initiatives like the Coalition for Epidemic Preparedness Innovations and the World Health Organization COVID-19 Vaccines Global Access, and the establishment of regional manufacturing hubs to effectively respond to unpredictable threats like “Disease X.”