Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Background: The aim of this study was to determine if it was feasible and safe to perform total hip arthroplasty (THA) using the direct anterior approach (DAA) when compared with the conventional posterolateral approach (PA) in patients with femoral neck fractures. The time required to start walking was investigated to identify advantages of the muscle-sparing approach. Safety of the approach was judged based on the incidence and nature of all complications. Methods: We retrospectively reviewed 67 THA cases due to femoral neck fractures from October 2015 to January 2019. The PA was used in 31 cases, and the DAA was used in 36 cases. The average operative time and amount of bleeding were evaluated. Cup inclination, anteversion, and leg length discrepancy (LLD) were also measured on radiographs. The time to start walking and complications (e.g., intraoperative fracture, infection, and dislocation) were recorded. Results: The mean operative time was 84.35 ± 13.95 minutes in PA group and 99.22 ± 20.33 minutes in DAA group (p = 0.010). But after experiencing 20 cases using the DAA, there was no statistically significant difference in the operative time between the groups. The mean volume of bleeding was 428.73 ± 207.26 mL in the PA group and 482.47 ± 150.14 mL in the DAA group. There was no difference in the acetabular cup position between two groups. Ambulation was started at 3.94 days after surgery on average in the PA group and 3.14 days in the DAA group, showing a statistically significant difference. Intraoperative fracture and infection were not observed in either group. The incidence of LLD was 1 in each group. The dislocation rate was 3.2% (1 case) in the PA group and 5.5% (2 cases) in the DAA group. Conclusions Although the DAA for THA was similar to the PA in terms of operative time, volume of bleeding, and complications, the DAA showed a great advantage in early rehabilitation as a muscle-sparing procedure in the elderly with femoral neck fractures.

The ferret is an established animal model of influenza virus infection. Although viral replication in the upper respiratory tract is usually measured with consecutively collected nasal washes, daily evaluation of viral replication in the lung is limited because a large numbers of ferrets need to be sacrificed at consecutive time points. To overcome this limitation, we performed a virus quantification assay using bronchoalveolar lavage (BAL) fluid. This non-invasive BAL technique allows consecutive quantification of virus replication in the lungs of living ferrets. Our method can be used for the longitudinal evaluation of virus tropism in the lower respiratory tract.
Animals ; Bronchoalveolar Lavage/*veterinary ; Disease Models, Animal ; Female ; Ferrets/*virology ; Influenza A Virus, H3N2 Subtype/*physiology ; Orthomyxoviridae Infections/*veterinary/virology ; Respiratory System/*virology ; Virus Replication/*physiology

A 37-year-old woman presented to our hospital with a 1-month history of fever. She also complained of lower leg pain. Transthoracic echocardiography showed large vegetations on the mitral valve leaflets. Staphylococcus lugdunensis was isolated from blood cultures. She was diagnosed with infectious endocarditis due to S. lugdunensis and was treated with antibiotics and surgery. Infective endocarditis caused by S. lugdunensis can be invasive and often resembles endocarditis due to Staphylococcus aureus. Thus, whenever this organism is found in patients with endocarditis, early surgical treatment of the infected valve should be considered.
Adult ; Anti-Bacterial Agents ; Echocardiography ; Endocarditis ; Female ; Fever ; Humans ; Leg ; Mitral Valve ; Staphylococcus ; Staphylococcus aureus ; Staphylococcus lugdunensis

Thienopyridines are antiplatelet agents used in post-percutaneous coronary angioplasty patients and patients with acute coronary syndrome, stroke, and peripheral arterial disease. Ticlopidine has been shown to reduce the incidence of stent thrombosis, but it may also cause serious hematological side effects. Among the thienopyridines, clopidogrel is considered to be a safe alternative to ticlopidine because of its decreased incidence of hematological adverse effects. However, some hematological side effects can occur and may be fatal. In this case, a 47-year-old man complained of dyspnea and generalized edema. He had been taking clopidogrel after coronary angioplasty. His laboratory findings showed acute renal failure, microangiopathic hemolytic anemia, and thrombocytopenia, which were consistent with hemolytic uremic syndrome (HUS). After discontinuing clopidogrel and undergoing plasma exchange, he recovered fully. To our knowledge, this is the first reported case of clopidogrel-induced HUS in Korea.
Acute Coronary Syndrome ; Acute Kidney Injury ; Anemia, Hemolytic ; Angioplasty ; Dyspnea ; Edema ; Hemolytic-Uremic Syndrome ; Humans ; Incidence ; Korea ; Middle Aged ; Peripheral Arterial Disease ; Plasma Exchange ; Platelet Aggregation Inhibitors ; Stents ; Stroke ; Thienopyridines ; Thrombocytopenia ; Thrombosis ; Ticlopidine

The object of this study is to measure the transit time and passage rate of capsule endoscopy (CE) in the gastrointestinal tract in medium sized beagle dogs (7~13 kg). Animals were divided into four groups: only capsule (group 1, n=10), capsule+water (group 2, n=10), mettoclopramide+capsule (group 3, n=10), metoclopramide +capsule+water (group 4, n=10). The capsule transit times through the stomach and small bowel were evaluated by radiography findings. Gastric transit time (GTT), small intestinal transit time (SITT) and complete passage rate were measured in four groups. GTT's for each group were as follows; 45+/-20 min (group 1), 117+/-35 min (group 2), 150+/-40 min (group 3), and 154+/-65 min (group 4), while SITT's were 75+/-20 min (group 1), 195+/-55 min (group 2), 70+/-15 min (group 3), and 76+/-15 min (group 4). The complete passage rates were 20% (group 1), 40% (group 2), 20% (group 3), 50% (group 4). In all groups, if CE could pass through the pylorus, it passed all small intestinal tracts within 8 hours (battery life). Administration of water helped CE to pass pylori, except in case of metoclopramide administration. These results indicate that CE could be an useful tool for examining gastrointestinal diseases in the veterinary medicine.
Animals ; Capsule Endoscopy ; Dogs ; Gastrointestinal Diseases ; Gastrointestinal Tract ; Gastrointestinal Transit ; Metoclopramide ; Pylorus ; Stomach ; Veterinary Medicine ; Water