Journal of Korean medical science
-
J. Korean Med. Sci. · Aug 2023
ReviewClinical Outcomes of Bronchoscopic Cryotherapy for Central Airway Obstruction in Adults: An 11-Years' Experience of a Single Center.
Although bronchoscopic cryotherapy (BC) is a pragmatic modality for recanalization of central airway obstruction (CAO), the risk of complications, such as bleeding, remains a concern. This study aimed to present the clinical outcomes of BC and evaluate the factors associated with its complications. ⋯ BC is an efficient and relatively safe intervention for patients with CAO. Our findings suggest that diabetes, respiratory failure before BC, and the absence of distal airway atelectasis may be risk factors of moderate to severe intrabronchial bleeding.
-
J. Korean Med. Sci. · Aug 2023
ReviewDevelopment of Items for Transitional Care Service and Outcome Indicators of Discharged Patients for Improvement in Quality of Care.
In this study, with the aim of improving the quality of transitional care service for discharged patients, the Health Care Quality and Outcomes Indicators of the Organization for Economic Co-operation and Development and National Health Service Outcomes Framework of the UK were applied to derive service items for provision and develop evaluation indicators under categories of effectiveness, safety, and patient-centeredness. ⋯ This study suggest practical implications for the service with high relevance and necessity for transitional period. It also presented outcome indicators of transitional care service to contribute toward an improvement in the quality of care.
-
J. Korean Med. Sci. · Aug 2023
Effects of COVID-19 and Influenza Vaccination on Rheumatic Diseases: Results From a Survey of Patient-Reported Outcomes After Vaccination.
This study aimed to compare the occurrence of adverse events (AEs) and disease flares after vaccination against coronavirus disease 2019 (COVID-19) and influenza in patients with autoimmune rheumatic diseases (ARDs). ⋯ The results of the survey of patients with ARD revealed that patient-reported AEs and underlying disease flares after receiving the COVID-19 vaccine were significantly higher than those after the influenza vaccine.
-
J. Korean Med. Sci. · Aug 2023
Factors Influencing Postmortem Catecholamine Level and Its Correlations With Agony Time and Cause of Death in Medicolegal Autopsy.
Catecholamines consisting of epinephrine (EP), norepinephrine (NE), and dopamine (DA) are known as a class of chemical neurotransmitters and hormones essential for regulation of physiological processes including stress responses. Many researchers have tried to establish a relationship between postmortem catecholamine level and agony time or underlying cause of death. However, relevant studies have yielded debatable results. This study was performed to determine characteristics of catecholamine distribution in postmortem specimens with various influencing factors and to assess relationships of postmortem catecholamine levels with agony time and cause of death. ⋯ Results of this study have important implications for understanding postmortem catecholamine distribution and their mutual associations, influences of clinical and demographic factors, and relationships with agony time and cause of death in Korean population. Although comprehensive demonstration of catecholamine level as stress index was not possible in the present study, the assessment of postmortem catecholamine levels could be used as a supportive tool in classification of agonal status and differential diagnosis of the cause of death in particular cases. Further investigation is needed on this issue.
-
J. Korean Med. Sci. · Aug 2023
ReviewThe Present and Future of Artificial Intelligence-Based Medical Image in Diabetes Mellitus: Focus on Analytical Methods and Limitations of Clinical Use.
Artificial intelligence (AI)-based diagnostic technology using medical images can be used to increase examination accessibility and support clinical decision-making for screening and diagnosis. To determine a machine learning algorithm for diabetes complications, a literature review of studies using medical image-based AI technology was conducted using the National Library of Medicine PubMed, and the Excerpta Medica databases. Lists of studies using diabetes diagnostic images and AI as keywords were combined. ⋯ Major limitations in AI-based detection of diabetes complications using medical images were the lack of datasets (36.1%, 82/227 cases) and severity misclassification (26.4%, 60/227 cases). Although it remains difficult to use and fully trust AI-based imaging analysis technology clinically, it reduces clinicians' time and labor, and the expectations from its decision-support roles are high. Various data collection and synthesis data technology developments according to the disease severity are required to solve data imbalance.