Purpose: This study aimed to establish a basis for minimizing readmission of patients with heart failure by comparing their demographic, clinical, psychosocial, and behavioral characteristics based on the presence or absence of readmission. Methods: This retrospective descriptive study included 160 elderly patients with heart failure aged 60 years and older, who regularly visited the cardiovascular outpatient clinic in K hospital in Daegu.Data were collected from April to December 2021 using self-report questionnaires including the Lubben Social Network Scale, the Scale of Positive and Negative Experience, and European Heart Failure Self-care Behaviour 9-Item Tools, which were translated in the Korean context. IBM SPSS Statistics 25 was used for analysis, and descriptive statistics, χ2 test, Fisher’s exact test, t-test, and logistic regression analysis were conducted. Results: The factors that significantly affected the readmission of elderly patients with heart failure were social network and the type of medications taken. The total explanatory power of the regression model was 22.7%. Social network (OR=0.93, p=.037) and the type of medication taken were 4~5 (OR=4.80, p=.014) and more than 6 medications (OR=7.84, p=.037) had a significant impact on readmission. Conclusion Social network was the most influential factor for readmission. Further studies are needed to minimize readmission by analyzing additional factors that show significant differences.

Purpose: This study aimed to establish a basis for minimizing readmission of patients with heart failure by comparing their demographic, clinical, psychosocial, and behavioral characteristics based on the presence or absence of readmission. Methods: This retrospective descriptive study included 160 elderly patients with heart failure aged 60 years and older, who regularly visited the cardiovascular outpatient clinic in K hospital in Daegu.Data were collected from April to December 2021 using self-report questionnaires including the Lubben Social Network Scale, the Scale of Positive and Negative Experience, and European Heart Failure Self-care Behaviour 9-Item Tools, which were translated in the Korean context. IBM SPSS Statistics 25 was used for analysis, and descriptive statistics, χ2 test, Fisher’s exact test, t-test, and logistic regression analysis were conducted. Results: The factors that significantly affected the readmission of elderly patients with heart failure were social network and the type of medications taken. The total explanatory power of the regression model was 22.7%. Social network (OR=0.93, p=.037) and the type of medication taken were 4~5 (OR=4.80, p=.014) and more than 6 medications (OR=7.84, p=.037) had a significant impact on readmission. Conclusion Social network was the most influential factor for readmission. Further studies are needed to minimize readmission by analyzing additional factors that show significant differences.

Purpose: This study aimed to establish a basis for minimizing readmission of patients with heart failure by comparing their demographic, clinical, psychosocial, and behavioral characteristics based on the presence or absence of readmission. Methods: This retrospective descriptive study included 160 elderly patients with heart failure aged 60 years and older, who regularly visited the cardiovascular outpatient clinic in K hospital in Daegu.Data were collected from April to December 2021 using self-report questionnaires including the Lubben Social Network Scale, the Scale of Positive and Negative Experience, and European Heart Failure Self-care Behaviour 9-Item Tools, which were translated in the Korean context. IBM SPSS Statistics 25 was used for analysis, and descriptive statistics, χ2 test, Fisher’s exact test, t-test, and logistic regression analysis were conducted. Results: The factors that significantly affected the readmission of elderly patients with heart failure were social network and the type of medications taken. The total explanatory power of the regression model was 22.7%. Social network (OR=0.93, p=.037) and the type of medication taken were 4~5 (OR=4.80, p=.014) and more than 6 medications (OR=7.84, p=.037) had a significant impact on readmission. Conclusion Social network was the most influential factor for readmission. Further studies are needed to minimize readmission by analyzing additional factors that show significant differences.

Purpose: This study aimed to establish a basis for minimizing readmission of patients with heart failure by comparing their demographic, clinical, psychosocial, and behavioral characteristics based on the presence or absence of readmission. Methods: This retrospective descriptive study included 160 elderly patients with heart failure aged 60 years and older, who regularly visited the cardiovascular outpatient clinic in K hospital in Daegu.Data were collected from April to December 2021 using self-report questionnaires including the Lubben Social Network Scale, the Scale of Positive and Negative Experience, and European Heart Failure Self-care Behaviour 9-Item Tools, which were translated in the Korean context. IBM SPSS Statistics 25 was used for analysis, and descriptive statistics, χ2 test, Fisher’s exact test, t-test, and logistic regression analysis were conducted. Results: The factors that significantly affected the readmission of elderly patients with heart failure were social network and the type of medications taken. The total explanatory power of the regression model was 22.7%. Social network (OR=0.93, p=.037) and the type of medication taken were 4~5 (OR=4.80, p=.014) and more than 6 medications (OR=7.84, p=.037) had a significant impact on readmission. Conclusion Social network was the most influential factor for readmission. Further studies are needed to minimize readmission by analyzing additional factors that show significant differences.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Purpose: This study aimed to investigate medication regimen complexity, social support, and beliefs about medicine as factors related to medication adherence, with the eventual goal of targeting these factors to improve medication adherence in patients undergoing hemodialysis. Methods: This study included 143 patients undergoing hemodialysis (hospitalized or outpatients) from two hospitals located in Daegu city. Data were collected from January 11 to March 31, 2023, using self-reported questionnaires, including the Morisky Medication Adherence Scale (MMAS-8), medication regimen complexity index, multidimensional scale of perceived social support, and beliefs about medicine. The collected data were analyzed using descriptive tests, the independent t-test, one-way analysis of variance, Pearson’s correlation coefficients, and hierarchical multiple regression via SPSS for Windows version 25.0. Results: Based on the MMAS-8 scores, the prevalence of medication nonadherence was determined to be 53.8%. In hierarchical regression analysis, the factors affecting medication adherence included beliefs about medicine (β=.34, p<.001) and social support (β=.30, p<.001). The total explanatory power of the regression model was 44% (F=16.83, p<.001). Conclusion Social support and beliefs about medicine can be effective strategies for positively changing medication adherence in patients undergoing hemodialysis. It is essential to establish nursing intervention programs to increase social support and modify beliefs about medicine in patients undergoing hemodialysis.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Background: Since the clinical application of flow cytometry, many clinical laboratories have utilized this method for diagnosing hematologic malignancies. However, delays in testing can occur due to various reasons.To address this issue, whole blood fixatives are occasionally administered.Hence, this study aimed to determine the impact of applying whole blood fixative on bone marrow specimens. Methods: Nine samples without lymphoma/leukemia bone marrow involvement were examined. Flow cytometry was performed using 17 common markers. The samples were stored at room temperature (RT) and 4°C without fixative treatment, stored at 4°C after TransFix (Cytomark, UK) treatment, and stored at RT after Cyto-Chex (Streck, USA) treatment.Subsequently, the samples were divided into groups and examined. A total of 13 tests were conducted on each sample for up to 5 days. Results: The neutrophil and monocyte fractions improved when the samples were stored at 4°C, while no significant difference was observed in the lymphocyte fractions. The fluorescence intensity of the markers varied depending on the marker and conditions, with the most stable markers observed when stored in TransFix at 4°C, followed by storage at 4°C, CytoChex RT, and RT. Conclusions The use of fixative on bone marrow specimens maintained the stability of markers during delayed testing. Both fixatives are more effective in preserving marker intensity and cell fractions compared with RT storage.Refrigeration and the use of fixatives may be beneficial for examinations delayed beyond 72 hours.

Objective: Early trauma significantly affects the severity of panic disorder (PD) symptoms and suicidal ideation. However, few studies have explored the specific effects of different early trauma subtypes on PD. This study analyzed how childhood trauma subtypes, including general, physical, emotional, and sexual, influence panic and phobia levels and suicidal ideation in adults with PD and healthy controls (HCs). Methods: In total, 455 adults with PD and 149 HCs participated in this study. The independent variables were sociodemographic and clinical variables such as coping strategies and early trauma subtypes from the Early Trauma Inventory Self Report-Short Form. The dependent variables were the Albany Panic and Phobia Questionnaire (APPQ), the Panic Disorder Severity Scale, and the Scale for Suicide Ideation (SSI). Results: Early emotional trauma significantly influenced the APPQ scores, whereas early physical trauma significantly influenced the SSI scores in patients with PD. However, in HCs, only early emotional trauma was significantly associated with the APPQ and SSI scores. Conclusion These findings highlight the influence of early trauma subtypes on the phobic symptom severity of PD and suicidal ideation among patients with PD. Early emotional trauma is associated with the severity of phobic symptoms, whereas early physical trauma is associated with suicidal ideation, suggesting distinct clinical outcomes based on the type of trauma in patients with PD.

A three-dimensional (3D) segmentation and model reconstruction is a specialized tool to reveal spatial interrelationship between multiple internal organs by generating images without overlapping structures. This technique can also be applicable to mummy studies, but related reports have so far been very rare. In this study, we applied 3D segmentation and model reconstruction to computed tomography images of a Korean mummy with congenital diaphragmatic hernia. As originally revealed by the autopsy in 2013, the current 3D reconstruction reveals that the mummy’s heart is shifted to the left due to the liver pushing up to thoracic cavity thorough diaphragmatic hernial defect. We can generate 3D images by calling up the data exclusively from mummy’s target organs, thus minimizing the confusion of diagnosis that could be caused by overlapping organs.