Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement.The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement.The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Background: The recently introduced super-resolution (SR) deep learning image reconstruction (DLR) is potentially effective in reducing noise level and enhancing the spatial resolution. We aimed to investigate whether SR-DLR has advantages in the overall image quality and intensity homogeneity on coronary computed tomography (CT) angiography with four different approaches: filtered-back projection (FBP), hybrid iterative reconstruction (IR), DLR, and SR-DLR. Methods: Sixty-three patients (mean age, 61 ± 11 years; range, 18–81 years; 40 men) who had undergone coronary CT angiography between June and October 2022 were retrospectively included. Image noise, signal to noise ratio, and contrast to noise ratio were quantified in both proximal and distal segments of the major coronary arteries. The left ventricle myocardium contrast homogeneity was analyzed. Two independent reviewers scored overall image quality, image noise, image sharpness, and myocardial homogeneity. Results: Image noise in Hounsfield units (HU) was significantly lower (P < 0.001) for the SR-DLR (11.2 ± 2.0 HU) compared to those associated with other image reconstruction methods including FBP (30.5 ± 10.5 HU), hybrid IR (20.0 ± 5.4 HU), and DLR (14.2 ± 2.5 HU) in both proximal and distal segments. SR-DLR significantly improved signal to noise ratio and contrast to noise ratio in both the proximal and distal segments of the major coronary arteries.No significant difference was observed in the myocardial CT attenuation with SR-DLR among different segments of the left ventricle myocardium (P = 0.345). Conversely, FBP and hybrid IR resulted in inhomogeneous myocardial CT attenuation (P < 0.001). Two reviewers graded subjective image quality with SR-DLR higher than other image recon‑ struction techniques (P < 0.001). Conclusions SR-DLR improved image quality, demonstrated clearer delineation of distal segments of coronary arter‑ ies, and was seemingly accurate for quantifying CT attenuation in the myocardium.

Background: The recently introduced super-resolution (SR) deep learning image reconstruction (DLR) is potentially effective in reducing noise level and enhancing the spatial resolution. We aimed to investigate whether SR-DLR has advantages in the overall image quality and intensity homogeneity on coronary computed tomography (CT) angiography with four different approaches: filtered-back projection (FBP), hybrid iterative reconstruction (IR), DLR, and SR-DLR. Methods: Sixty-three patients (mean age, 61 ± 11 years; range, 18–81 years; 40 men) who had undergone coronary CT angiography between June and October 2022 were retrospectively included. Image noise, signal to noise ratio, and contrast to noise ratio were quantified in both proximal and distal segments of the major coronary arteries. The left ventricle myocardium contrast homogeneity was analyzed. Two independent reviewers scored overall image quality, image noise, image sharpness, and myocardial homogeneity. Results: Image noise in Hounsfield units (HU) was significantly lower (P < 0.001) for the SR-DLR (11.2 ± 2.0 HU) compared to those associated with other image reconstruction methods including FBP (30.5 ± 10.5 HU), hybrid IR (20.0 ± 5.4 HU), and DLR (14.2 ± 2.5 HU) in both proximal and distal segments. SR-DLR significantly improved signal to noise ratio and contrast to noise ratio in both the proximal and distal segments of the major coronary arteries.No significant difference was observed in the myocardial CT attenuation with SR-DLR among different segments of the left ventricle myocardium (P = 0.345). Conversely, FBP and hybrid IR resulted in inhomogeneous myocardial CT attenuation (P < 0.001). Two reviewers graded subjective image quality with SR-DLR higher than other image recon‑ struction techniques (P < 0.001). Conclusions SR-DLR improved image quality, demonstrated clearer delineation of distal segments of coronary arter‑ ies, and was seemingly accurate for quantifying CT attenuation in the myocardium.

Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement.The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Background: The recently introduced super-resolution (SR) deep learning image reconstruction (DLR) is potentially effective in reducing noise level and enhancing the spatial resolution. We aimed to investigate whether SR-DLR has advantages in the overall image quality and intensity homogeneity on coronary computed tomography (CT) angiography with four different approaches: filtered-back projection (FBP), hybrid iterative reconstruction (IR), DLR, and SR-DLR. Methods: Sixty-three patients (mean age, 61 ± 11 years; range, 18–81 years; 40 men) who had undergone coronary CT angiography between June and October 2022 were retrospectively included. Image noise, signal to noise ratio, and contrast to noise ratio were quantified in both proximal and distal segments of the major coronary arteries. The left ventricle myocardium contrast homogeneity was analyzed. Two independent reviewers scored overall image quality, image noise, image sharpness, and myocardial homogeneity. Results: Image noise in Hounsfield units (HU) was significantly lower (P < 0.001) for the SR-DLR (11.2 ± 2.0 HU) compared to those associated with other image reconstruction methods including FBP (30.5 ± 10.5 HU), hybrid IR (20.0 ± 5.4 HU), and DLR (14.2 ± 2.5 HU) in both proximal and distal segments. SR-DLR significantly improved signal to noise ratio and contrast to noise ratio in both the proximal and distal segments of the major coronary arteries.No significant difference was observed in the myocardial CT attenuation with SR-DLR among different segments of the left ventricle myocardium (P = 0.345). Conversely, FBP and hybrid IR resulted in inhomogeneous myocardial CT attenuation (P < 0.001). Two reviewers graded subjective image quality with SR-DLR higher than other image recon‑ struction techniques (P < 0.001). Conclusions SR-DLR improved image quality, demonstrated clearer delineation of distal segments of coronary arter‑ ies, and was seemingly accurate for quantifying CT attenuation in the myocardium.

Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement.The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Purpose: This study aimed to identify the main keyword, network structure, and main topics of the national petition related to “nursing” in South Korea. Methods: Data were gathered from petitions related to the national petition in Korea Blue House related to the topic “nursing” or “nurse” from August 17, 2017, to May 9, 2022. A total of 5,154 petitions were searched, and 995 were selected for the final analysis. Text network analysis and topic modeling were analyzed using the Netminer 4.5.0 program. Results: Regarding network characteristics, a density of 0.03, an average degree of 144.483, and an average distance of 1.943 were found. Compared to results of degree centrality and betweenness centrality, keywords such as “work environment,” “nursing university,” “license,” and “education” appeared typically in the eigenvector centrality analysis. Topic modeling derived four topics: (1) “Improving the working environment and dealing with nursing professionals,” (2) “requesting investigation and punishment related to medical accidents,” (3) “requiring clear role regulation and legislation of medical and nonmedical professions,” and (4) “demanding improvement of healthcare-related systems and services.” Conclusion This is the first study to analyze Korea's national petitions in the field of nursing. This study's results confirmed both the internal needs and external demands for nurses in South Korea. Policies and laws that reflect these results should be developed.

As of April 18, 2020, there have been a total of 10,653 confirmed cases and 232 deaths due to coronavirus disease 2019 (COVID-19) in Korea. The pathogen spread quickly, and the outbreak caused nationwide anxiety and shock. This study presented the anecdotal records that provided a detailed process of the multidisciplinary teamwork in mental health during the COVID-19 outbreak in the country. Psychosocial support is no less important than infection control during an epidemic, and collaboration and networking are at the core of disaster management. Thus, a multidisciplinary team of mental health professionals was immediately established and has collaborated effectively with its internal and external stakeholders for psychosocial support during the COVID-19 outbreak.

Chest pain in kidney transplant patients is usually caused by cardiac or pulmonary problems. However, it may be rarely caused by opportunistic esophageal infections. A 66-year-old female kidney transplant recipient was admitted because of chest pain. She had been treated with high-dose steroid and immunosuppressants for acute T-cell-mediated rejection. Cardiologic and pulmonary evaluations had normal results. Endoscopic examination revealed three clear ulcerative lesions in the esophagus. Histological and immunohistochemical staining of the endoscopic biopsy specimens revealed coinfection of herpes simplex virus and cytomegalovirus. The patient was treated with intravenous ganciclovir for 2 weeks. Her symptoms completely resolved, and follow-up endoscopy revealed complete healing of the previous ulcers. Viral esophagitis should be considered in the differential diagnosis in kidney transplant recipients presenting with chest pain.
Aged ; Biopsy ; Chest Pain ; Coinfection ; Cytomegalovirus ; Diagnosis, Differential ; Endoscopy ; Esophagitis ; Esophagus ; Female ; Follow-Up Studies ; Ganciclovir ; Herpes Simplex ; Humans ; Immunosuppressive Agents ; Kidney ; Kidney Transplantation ; Simplexvirus ; Thorax ; Transplant Recipients ; Ulcer