Background: Obstructive sleep apnea (OSA) increases the risk of dyslipidemia, thereby heightening the likelihood of developing cardiovascular diseases. Hence, prior to the diagnosis of OSA, it is essential to investigate the association with dyslipidemia in at-risk individuals. Methods: Using raw data obtained from the 2021 Korea National Health and Nutrition Examination Survey, we examined the details of 2,882 participants aged 40 years and older, who were not diagnosed with sleep apnea and did not use lipid-lowering medications. Participants who had reported snoring, fatigue, or witnessed apnea episodes, were categorized into the “OSA Risk Group” (OSARG), and logistic regression analysis was performed to examine the association between serum lipid levels and dyslipidemia. Results: OSARG participants were found to have a higher prevalence of hypertriglyceridemia and increased prevalence of dyslipidemia. After adjusting for sex, age, education, economic status, housing type, obesity, physical activity, smoking, and alcohol consumption, only hypertriglyceridemia remained significantly associated with the OSARG, and the odds ratio for OSA was significantly higher among those patients with hypertriglyceridemia (1.39; 95% confidence interval, 1.06–1.83). Conclusion Among adults aged 40 years and older, compared with those not at risk, individuals at risk of OSA were characterized by a higher prevalence of hypertriglyceridemia. These findings thus indicate that the management of hypertriglyceridemia and dyslipidemia may be warranted prior to the diagnosis of OSA in this population.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Background: Obstructive sleep apnea (OSA) increases the risk of dyslipidemia, thereby heightening the likelihood of developing cardiovascular diseases. Hence, prior to the diagnosis of OSA, it is essential to investigate the association with dyslipidemia in at-risk individuals. Methods: Using raw data obtained from the 2021 Korea National Health and Nutrition Examination Survey, we examined the details of 2,882 participants aged 40 years and older, who were not diagnosed with sleep apnea and did not use lipid-lowering medications. Participants who had reported snoring, fatigue, or witnessed apnea episodes, were categorized into the “OSA Risk Group” (OSARG), and logistic regression analysis was performed to examine the association between serum lipid levels and dyslipidemia. Results: OSARG participants were found to have a higher prevalence of hypertriglyceridemia and increased prevalence of dyslipidemia. After adjusting for sex, age, education, economic status, housing type, obesity, physical activity, smoking, and alcohol consumption, only hypertriglyceridemia remained significantly associated with the OSARG, and the odds ratio for OSA was significantly higher among those patients with hypertriglyceridemia (1.39; 95% confidence interval, 1.06–1.83). Conclusion Among adults aged 40 years and older, compared with those not at risk, individuals at risk of OSA were characterized by a higher prevalence of hypertriglyceridemia. These findings thus indicate that the management of hypertriglyceridemia and dyslipidemia may be warranted prior to the diagnosis of OSA in this population.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Background: Obstructive sleep apnea (OSA) increases the risk of dyslipidemia, thereby heightening the likelihood of developing cardiovascular diseases. Hence, prior to the diagnosis of OSA, it is essential to investigate the association with dyslipidemia in at-risk individuals. Methods: Using raw data obtained from the 2021 Korea National Health and Nutrition Examination Survey, we examined the details of 2,882 participants aged 40 years and older, who were not diagnosed with sleep apnea and did not use lipid-lowering medications. Participants who had reported snoring, fatigue, or witnessed apnea episodes, were categorized into the “OSA Risk Group” (OSARG), and logistic regression analysis was performed to examine the association between serum lipid levels and dyslipidemia. Results: OSARG participants were found to have a higher prevalence of hypertriglyceridemia and increased prevalence of dyslipidemia. After adjusting for sex, age, education, economic status, housing type, obesity, physical activity, smoking, and alcohol consumption, only hypertriglyceridemia remained significantly associated with the OSARG, and the odds ratio for OSA was significantly higher among those patients with hypertriglyceridemia (1.39; 95% confidence interval, 1.06–1.83). Conclusion Among adults aged 40 years and older, compared with those not at risk, individuals at risk of OSA were characterized by a higher prevalence of hypertriglyceridemia. These findings thus indicate that the management of hypertriglyceridemia and dyslipidemia may be warranted prior to the diagnosis of OSA in this population.

Background: Obstructive sleep apnea (OSA) increases the risk of dyslipidemia, thereby heightening the likelihood of developing cardiovascular diseases. Hence, prior to the diagnosis of OSA, it is essential to investigate the association with dyslipidemia in at-risk individuals. Methods: Using raw data obtained from the 2021 Korea National Health and Nutrition Examination Survey, we examined the details of 2,882 participants aged 40 years and older, who were not diagnosed with sleep apnea and did not use lipid-lowering medications. Participants who had reported snoring, fatigue, or witnessed apnea episodes, were categorized into the “OSA Risk Group” (OSARG), and logistic regression analysis was performed to examine the association between serum lipid levels and dyslipidemia. Results: OSARG participants were found to have a higher prevalence of hypertriglyceridemia and increased prevalence of dyslipidemia. After adjusting for sex, age, education, economic status, housing type, obesity, physical activity, smoking, and alcohol consumption, only hypertriglyceridemia remained significantly associated with the OSARG, and the odds ratio for OSA was significantly higher among those patients with hypertriglyceridemia (1.39; 95% confidence interval, 1.06–1.83). Conclusion Among adults aged 40 years and older, compared with those not at risk, individuals at risk of OSA were characterized by a higher prevalence of hypertriglyceridemia. These findings thus indicate that the management of hypertriglyceridemia and dyslipidemia may be warranted prior to the diagnosis of OSA in this population.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

This study presents transatrial stenting as a palliative treatment for central venous obstruction in dogs with cardiac tumors. Two dogs presented with lethargy and respiratory distress. On diagnostic imaging, a large cardiac tumor with central venous obstruction was identified in both dogs. One dog showed pleural effusion, plethoric caudal vena cava (CdVC), hepatic congestion, and ascites. The other dog had cervical swelling and pleural effusion. Transatrial stenting was performed in the cranial vena cava, right atrium, and CdVC for the relief of caval and atrial compression due to cardiac tumors. Clinical improvement was observed post-procedure, despite thrombus formation within the stent in the second case. Endovascular transatrial stenting is a promising palliative treatment for venous return obstruction caused by cardiac tumors, effectively alleviating clinical symptoms and providing a viable management option.