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.

Background: Periprosthetic osteolysis is a prevalent complication following total ankle arthroplasty (TAA), implicating various cytokines in osteoclastogenesis as pivotal in this process. This study aimed to evaluate the relationship between osteolysis and the concentrations of osteoclastogenesis-related cytokines in synovial fluid and investigate its clinical value following TAA. Methods: Synovial fluid samples from 23 ankles that underwent revision surgery for osteolysis following TAA were analyzed as the osteolysis group. As a control group, we included synovial fluid samples obtained from 23 ankles during primary TAA for osteoarthritis. The receptor activator of nuclear factor-κB ligand (RANKL)/osteoprotegerin (OPG) ratio in these samples was quantified using sandwich enzyme-linked immunosorbent assay techniques, and a bead-based multiplex immunoassay facilitated the detection of specific osteoclastogenesis-related cytokines. Results: RANKL levels averaged 487.9 pg/mL in 14 of 23 patients in the osteolysis group, with no detection in the control group’s synovial fluid. Conversely, a significant reduction in OPG levels was observed in the osteolysis group (p = 0.002), resulting in a markedly higher mean RANKL/OPG ratio (0.23) relative to controls (p = 0.020). Moreover, the osteolysis group had increased concentrations of various osteoclastogenesis-related cytokines (tumor necrosis factor-α, interleukin [IL]-1β, IL-6, IL-8, IP-10, and monocyte chemotactic protein-1) in the synovial fluid relative to the control group. Conclusions Our results demonstrated that periprosthetic osteolysis was associated with osteoclastogenesis activation through an elevated RANKL/OPG ratio following TAA. We assume that RANKL and other osteoclastogenesis-related cytokines in the synovial fluid have clinical value as a potential marker for the development and progression of osteolysis following TAA.

Background: Sagittal talar translation is an important factor influencing the sagittal alignment of total ankle arthroplasty (TAA). Thus, accurate measurement of sagittal talar translation is crucial. This study proposes a simple method (tibiotalar distance [TTD]) that can quantify talar translation without being affected by the ankle and subtalar joint condition or the talar component position in patients with TAA. Methods: We enrolled 280 eligible patients (296 ankles) who underwent primary TAA between 2005 and 2019 and retrospectively reviewed them for sagittal talar translation. The TTD was measured for each patient on weight-bearing lateral ankle radiographs by 3 raters. In addition, we analyzed interrater and intrarater reliability for the TTD method. Results: We found that the TTD method could quantify the talar translation and was not affected by the preoperative condition of the ankle joint surface, subtalar joint pathologies, or the postoperative talar component position. The TTD method showed an excellent intraclass correlation coefficient (> 0.9) in all interrater and intrarater reliability analyses. In the analysis of 157 healthy, unoperated contralateral ankles, we identified that TTD showed a Gaussian distribution (p = 0.284) and a mean of 38.91 mm (normal range, 29.63–48.20 mm). Conclusions The TTD method is a simple and reliable method that could be applied to patients with TAA to assess the sagittal talar translation regardless of the pre-and postoperative joint condition and implantation status.

Purpose: This study aimed to evaluate and compare the accuracy of the size of the posterior malleolar fragment measured using lateral plain radiography and three-dimensional computed tomography (3DCT) in patients with ankle trimalleolar fractures. Materials and Methods: This study enrolled 80 patients (80 ankles) with ankle trimalleolar fractures and analyzed the size of the posterior malleolar fragments using plain radiography and 3D-CT. The articular involvement of the posterior malleolar fragments was measured as a percentage of the articular surface in the sagittal length of the tibial plafond using lateral plain radiography, and the articular surface area was directly measured using 3D-CT. In addition, we classified the patients into three groups based on the morphology of the posterior malleolar fracture, according to the Haraguchi classification method, and evaluated and compared the accuracy of the size of the posterior malleolar fragments. Results: The mean articular involvement of the posterior malleolar fragments on plain radiography was 27.6% (range, 6.0%-53.1%), which was significantly higher than the mean of 21.9% (range, 4.7%-47.1%) measured using 3D-CT (p=0.004). In the analysis, according to the fracture morphology, the mean difference between the two methods was the largest for type I fractures at 9.1% (range, 1.8%-19.5%) and the smallest for type II fractures at 1.1% (range, –7.7% to 8.8%). Conclusion The articular involvement of posterior malleolar fragments measured using plain radiography showed low accuracy and significantly higher values than the actual articular involvement. Therefore, careful evaluation using 3D-CT is crucial for accurate analysis and optimal treatment in patients with ankle trimalleolar fractures.