This case report investigates the effects of semi-occluded vocal tract exercises (SOVTEs) on voice improvement in elderly female patients with presbyphonia. Elderly female patients with presbyphonia commonly present with symptoms such as hoarseness, decreased vocal intensity, and phonatory difficulties. These symptoms are often associated with age-related vocal fold atrophy, leading to compensatory muscle tension and inefficient phonation, which necessitate targeted therapeutic interventions. In this study, two elderly female patients, aged 73 years and 71 years, participated in a voice therapy program centered on SOVTEs designed to promote vocal fold vibration efficiency and reduce compensatory tension. Case 1 underwent five therapy sessions, while Case 2 completed sixteen sessions. Pre- and post-treatment voice assessments revealed notable improvements in vocal quality, suggesting that SOVTEs may be an effective therapeutic approach for managing presbyphonia in elderly women.

This case report investigates the effects of semi-occluded vocal tract exercises (SOVTEs) on voice improvement in elderly female patients with presbyphonia. Elderly female patients with presbyphonia commonly present with symptoms such as hoarseness, decreased vocal intensity, and phonatory difficulties. These symptoms are often associated with age-related vocal fold atrophy, leading to compensatory muscle tension and inefficient phonation, which necessitate targeted therapeutic interventions. In this study, two elderly female patients, aged 73 years and 71 years, participated in a voice therapy program centered on SOVTEs designed to promote vocal fold vibration efficiency and reduce compensatory tension. Case 1 underwent five therapy sessions, while Case 2 completed sixteen sessions. Pre- and post-treatment voice assessments revealed notable improvements in vocal quality, suggesting that SOVTEs may be an effective therapeutic approach for managing presbyphonia in elderly women.

This case report investigates the effects of semi-occluded vocal tract exercises (SOVTEs) on voice improvement in elderly female patients with presbyphonia. Elderly female patients with presbyphonia commonly present with symptoms such as hoarseness, decreased vocal intensity, and phonatory difficulties. These symptoms are often associated with age-related vocal fold atrophy, leading to compensatory muscle tension and inefficient phonation, which necessitate targeted therapeutic interventions. In this study, two elderly female patients, aged 73 years and 71 years, participated in a voice therapy program centered on SOVTEs designed to promote vocal fold vibration efficiency and reduce compensatory tension. Case 1 underwent five therapy sessions, while Case 2 completed sixteen sessions. Pre- and post-treatment voice assessments revealed notable improvements in vocal quality, suggesting that SOVTEs may be an effective therapeutic approach for managing presbyphonia in elderly women.

Purpose: This longitudinal cohort study aimed to evaluate the relationship between osteonecrosis of the jaw and pulp and periapical disease in patients who were administered bisphosphonates. Methods: Using data from a nationwide cohort, we examined the association among dental caries, pulp and periapical disease, and osteonecrosis of the jaw in women aged >50 years who received bisphosphonates for more than 1 year between 2002 and 2015.Because of ambiguities in the diagnosis of osteonecrosis of the jaw in population-based data, we operationally defined and categorized the condition into established and potential osteonecrosis of the jaw. Results: Pulp and periapical disease significantly increased the development of both established and potential osteonecrosis of the jaw (hazard ratio, 2.21; 95% confidence interval, 1.40–3.48; and hazard ratio, 2.22; 95% confidence interval, 1.65–2.98, respectively). Root canal treatment did not have any influence on the development of osteonecrosis of the jaw. Conclusions Pulp and periapical disease may be a major risk factor for osteonecrosis of the jaw. The study findings suggest that patients should undergo regular dental examinations to detect pulp and periapical disease before or during the administration of bisphosphonates and that root canal treatment should be considered to decrease the risk of osteonecrosis of the jaw.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background: We aimed at evaluating the diagnostic performance of rapid antigen test (RAT) compared to polymerase chain reaction (PCR) for severe acute respiratory syndrome coronavirus 2 and the possible transmission of infection to close contacts from patients with negative RAT and positive PCR results. Materials and Methods: Patients/guardians urgently requiring admission to the ward on the same day had been hospitalized with RAT-negative result before the PCR results were available. We performed an epidemiologic investigation of the close contacts of those with negative RAT but positive PCR results after hospitalization. Results: A total of 4,237 RATs were performed from March to August 2022. When the PCR test was used as the reference, RAT had a sensitivity of 28.8% (17/59; 95% confidence interval [CI], 17.8 - 42.1), a specificity of 100% (4,220/4,220; 95% CI, 99.9 – 100.0), a positive predictive value of 100.0% (17/17; 95% CI, 100.0 - 100.0), and a negative predictive value of 99.0% (4,178/4,220; 95% CI, 99.3 - 99.8). The epidemiologic investigation revealed that among the 32 patients with negative RAT and subsequent positive PCR results after admission into multi-patient room, two (6.3%) showed secondary coronavirus disease 2019. Conclusion The secondary transmission rate from patients with negative RAT and positive PCR results was low. Our data suggest that RAT may be useful for rapid exclusion of high transmissible cases. However, further evaluation using whole genome sequencing is needed to determine the potential for transmissibility in cases showing a negative RAT but a positive PCR result

Background: Ralstonia mannitolilytica is a causative organism of nosocomial infections, particularly associated with contaminated water, and resistant to various antibiotics, including carbapenems. Several clusters of R. mannitolilytica infections appeared in children at our institute from August 2018 to November 2019. Methods: From March 2009 to March 2023, all patients admitted to Asan Medical Center Children’s Hospital in Seoul, Korea, with culture-confirmed R. mannitolilytica and corresponding clinical signs of infection were identified. Epidemiological and environmental investigations were conducted. Polymerase chain reaction (PCR) was performed for the genes of OXA-443 and OXA-444 on R. mannitolilytica isolates. Results: A total of 18 patients with R. mannitolilytica infection were included in this study, with 94.4% (17/18) and 5.6% (1/18) being diagnosed with pneumonia and central line-associated bloodstream infection, respectively. All-cause 30-day mortality rate was 61.1% (11/18), and seven of the fatal cases were caused by R. mannitolilytica infection itself. The resistance rates to meropenem and imipenem werew 94.4% (17/18) and 5.6% (1/18), respectively. Although four out of nine meropenem-resistant R.mannitolilytica isolates had positive PCR results for OXA-443 and OXA-444 genes, there were no significant differences in antimicrobial susceptibility patterns. Environmental sampling identified R. mannitolylica at two sites: a cold-water tap of a water purifier and an exhalation circuit of a patient mechanical ventilator.After implementing and improving adherence to infection control policies, no additional R. mannitolilyticainfection cases have been reported since December 2019. Conclusion R. mannitolilytica can cause life-threatening infections with high mortality in fragile pediatric populations. To prevent outbreaks, healthcare workers should be aware of R. mannitolilytica infections and strive to comply with infection control policies.