Background/Aims: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent nature. This study aims to develop reliable artificial intelligence (AI) algorithms to detect early signs of AF in patients with normal sinus rhythm (NSR) using a 12-lead electrocardiogram (ECG). Methods: Between 2013 and 2020, 552,372 ECG traces from 318,321 patients were collected and split into training (n = 331,422), validation (n = 110,475), and test sets (n = 110,475). Deep neural networks were then trained to predict AF onset within one month of NSR. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). An explainable AI technique was employed to identify the inference evidence underlying the predictions of deep learning models. Results: The AUROC for early diagnosis of PAF was 0.905 ± 0.007. The findings reveal that the vicinity of the T wave, including the ST segment and S-peak, significantly influences the ability of the trained neural network to diagnose PAF. Additionally, comparing the summarized ECG in NSR with those in PAF revealed that nonspecific ST-T abnormalities and inverted T waves were associated with PAF. Conclusions Deep learning can predict AF onset from NSR while detecting key features that influence decisions. This suggests that identifying undetected AF may serve as a predictive tool for PAF screening, offering valuable insights into cardiac dysfunction and stroke risk.

Purpose: Cognitive behavioral therapy (CBT) has long been recognized as an effective treatment for depression and suicidality.Virtual reality (VR) technology is widely used for cognitive training for conditions such as anxiety disorder and post-traumatic stress disorder, but little research has considered VR-based CBT for depressive symptoms and suicidality. We tested the effectiveness and safety of a VR-based CBT program for depressive disorders. Materials and Methods: We recruited 57 participants from May 2022 through February 2023 using online advertisements. This multi-center, assessor-blinded, randomized, controlled exploratory trial used two groups: VR treatment group and treat as usual (TAU) group. VR treatment group received a VR mental health training/education program. TAU group received standard pharmacotherapy. Assessments were conducted at baseline, immediately after the 6-week treatment period, and 4 weeks after the end of the treatment period in each group. Results: Depression scores decreased significantly over time in both VR treatment and TAU groups, with no differences between the two groups. The suicidality score decreased significantly only in VR group. No group differences were found in the remission or response rate for depression, perceived stress, or clinical severity. No adverse events or motion sickness occurred during the VR treatment program. Conclusion VR CBT treatment for major depressive disorder has the potential to be equivalent to the gold-standard pharmacotherapy in reducing depressive symptoms, suicidality, and related clinical symptoms, with no difference in improvement found in this study. Thus, VR-based CBT might be an effective alternative to pharmacotherapy for depressive disorders.

Background: Complete revascularization has demonstrated better outcomes in patients with acute myocardial infarction (AMI) and multivessel disease. However, in the case of left main (LM) culprit lesion AMI with multivessel disease, there is limited evidence to suggest that complete revascularization is better. Methods: We reviewed 16,831 patients in the Korea Acute Myocardial Infarction Registry who were treated from July 2016 to June 2020, and 399 patients were enrolled with LM culprit lesion AMI treated with percutaneous coronary intervention. We categorized the patients as those treated with complete revascularization (n=295) or incomplete revascularization (n=104). The study endpoint was major adverse cardiac and cerebrovascular events (MACCE), a composite of all-cause death, myocardial infarction, ischemia-driven revascularization, stent thrombosis, and stroke. We performed propensity score matching (PSM) and analyzed the incidence of MACCE at 1 year. Results: After PSM, the two groups were well balanced. There was no significant difference between the two groups in MACCE at 1 year (12.1% vs. 15.2%; hazard ratio, 1.28; 95% confidence interval, 0.60–2.74; p=0.524) after PSM. The components of MACCE and major bleeding were also not significantly different. Conclusion There was no significant difference in clinical outcomes between the groups treated with complete or incomplete revascularization for LM culprit lesion AMI with multivessel disease.

Background and Objectives: The risk profiles, procedural characteristics, and clinical outcomes for women undergoing bifurcation percutaneous coronary intervention (PCI) are not well defined compared to those in men. Methods: COronary BIfurcation Stenting III (COBIS III) is a multicenter, real-world registry of 2,648 patients with bifurcation lesions treated with second-generation drug-eluting stents.We compared the angiographic and procedural characteristics and clinical outcomes based on sex. The primary outcome was 5-year target lesion failure (TLF), a composite of cardiac death, myocardial infarction, and target lesion revascularization. Results: Women (n=635, 24%) were older, had hypertension and diabetes more often, and had smaller main vessel and side branch reference diameters than men. The pre- and post-PCI angiographic percentage diameter stenoses of the main vessel and side branch were comparable between women and men. There were no differences in procedural characteristics between the sexes. Women and men had a similar risk of TLF (6.3% vs. 7.1%, p=0.63) as well as its individual components and sex was not an independent predictor of TLF. This finding was consistent in the left main and 2 stenting subgroups. Conclusions In patients undergoing bifurcation PCI, sex was not an independent predictor of adverse outcome.

Purpose: This study aimed to analyze nationwide trends and regional disparities in inguinal hernia surgeries in South Korea between 2016 and 2022. Additionally, we aimed to evaluate changes in surgery frequency, including urban concentration and the introduction of robotic surgery. Methods: This retrospective review used nationwide data on inguinal hernia surgeries from the Health Insurance Review and Assessment Service database. Results: From 2016 to 2022, 254,367 inguinal hernia surgeries were performed in South Korea, with males accounting for 88.9% of cases. The annual number of surgeries fluctuated, particularly in 2020, owing to the coronavirus disease 2019 pandemic. Medical costs increased from $1,218.4 to $1,970 on average, whereas patient copayments rose from $180.2 to $293.3. Robotic inguinal hernia surgeries, introduced in 2019, increased to 226 cases in 2022. Pediatric surgeries steadily declined, whereas adult surgeries remained stable, with a slight increase in 2022. The average hospital stay did not change significantly but varied between pediatric and adult patients. Regional disparities were notable, especially in pediatric surgery rates between metropolitan areas, such as Seoul and the surrounding provinces. Conclusion This study highlights stable overall surgery rates, a decline in pediatric cases, and an increase in robotic inguinal hernia surgeries. The persistent concentration of healthcare services in metropolitan areas suggests a need for policy interventions to address regional disparities and ensure equitable healthcare access. The findings underscore the importance of ongoing efforts to improve healthcare distribution and the need for long-term strategies to address changing surgical trends.

Background/Aims: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent nature. This study aims to develop reliable artificial intelligence (AI) algorithms to detect early signs of AF in patients with normal sinus rhythm (NSR) using a 12-lead electrocardiogram (ECG). Methods: Between 2013 and 2020, 552,372 ECG traces from 318,321 patients were collected and split into training (n = 331,422), validation (n = 110,475), and test sets (n = 110,475). Deep neural networks were then trained to predict AF onset within one month of NSR. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). An explainable AI technique was employed to identify the inference evidence underlying the predictions of deep learning models. Results: The AUROC for early diagnosis of PAF was 0.905 ± 0.007. The findings reveal that the vicinity of the T wave, including the ST segment and S-peak, significantly influences the ability of the trained neural network to diagnose PAF. Additionally, comparing the summarized ECG in NSR with those in PAF revealed that nonspecific ST-T abnormalities and inverted T waves were associated with PAF. Conclusions Deep learning can predict AF onset from NSR while detecting key features that influence decisions. This suggests that identifying undetected AF may serve as a predictive tool for PAF screening, offering valuable insights into cardiac dysfunction and stroke risk.

Purpose: Cognitive behavioral therapy (CBT) has long been recognized as an effective treatment for depression and suicidality.Virtual reality (VR) technology is widely used for cognitive training for conditions such as anxiety disorder and post-traumatic stress disorder, but little research has considered VR-based CBT for depressive symptoms and suicidality. We tested the effectiveness and safety of a VR-based CBT program for depressive disorders. Materials and Methods: We recruited 57 participants from May 2022 through February 2023 using online advertisements. This multi-center, assessor-blinded, randomized, controlled exploratory trial used two groups: VR treatment group and treat as usual (TAU) group. VR treatment group received a VR mental health training/education program. TAU group received standard pharmacotherapy. Assessments were conducted at baseline, immediately after the 6-week treatment period, and 4 weeks after the end of the treatment period in each group. Results: Depression scores decreased significantly over time in both VR treatment and TAU groups, with no differences between the two groups. The suicidality score decreased significantly only in VR group. No group differences were found in the remission or response rate for depression, perceived stress, or clinical severity. No adverse events or motion sickness occurred during the VR treatment program. Conclusion VR CBT treatment for major depressive disorder has the potential to be equivalent to the gold-standard pharmacotherapy in reducing depressive symptoms, suicidality, and related clinical symptoms, with no difference in improvement found in this study. Thus, VR-based CBT might be an effective alternative to pharmacotherapy for depressive disorders.

Background/Aims: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent nature. This study aims to develop reliable artificial intelligence (AI) algorithms to detect early signs of AF in patients with normal sinus rhythm (NSR) using a 12-lead electrocardiogram (ECG). Methods: Between 2013 and 2020, 552,372 ECG traces from 318,321 patients were collected and split into training (n = 331,422), validation (n = 110,475), and test sets (n = 110,475). Deep neural networks were then trained to predict AF onset within one month of NSR. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). An explainable AI technique was employed to identify the inference evidence underlying the predictions of deep learning models. Results: The AUROC for early diagnosis of PAF was 0.905 ± 0.007. The findings reveal that the vicinity of the T wave, including the ST segment and S-peak, significantly influences the ability of the trained neural network to diagnose PAF. Additionally, comparing the summarized ECG in NSR with those in PAF revealed that nonspecific ST-T abnormalities and inverted T waves were associated with PAF. Conclusions Deep learning can predict AF onset from NSR while detecting key features that influence decisions. This suggests that identifying undetected AF may serve as a predictive tool for PAF screening, offering valuable insights into cardiac dysfunction and stroke risk.

Purpose: Cognitive behavioral therapy (CBT) has long been recognized as an effective treatment for depression and suicidality.Virtual reality (VR) technology is widely used for cognitive training for conditions such as anxiety disorder and post-traumatic stress disorder, but little research has considered VR-based CBT for depressive symptoms and suicidality. We tested the effectiveness and safety of a VR-based CBT program for depressive disorders. Materials and Methods: We recruited 57 participants from May 2022 through February 2023 using online advertisements. This multi-center, assessor-blinded, randomized, controlled exploratory trial used two groups: VR treatment group and treat as usual (TAU) group. VR treatment group received a VR mental health training/education program. TAU group received standard pharmacotherapy. Assessments were conducted at baseline, immediately after the 6-week treatment period, and 4 weeks after the end of the treatment period in each group. Results: Depression scores decreased significantly over time in both VR treatment and TAU groups, with no differences between the two groups. The suicidality score decreased significantly only in VR group. No group differences were found in the remission or response rate for depression, perceived stress, or clinical severity. No adverse events or motion sickness occurred during the VR treatment program. Conclusion VR CBT treatment for major depressive disorder has the potential to be equivalent to the gold-standard pharmacotherapy in reducing depressive symptoms, suicidality, and related clinical symptoms, with no difference in improvement found in this study. Thus, VR-based CBT might be an effective alternative to pharmacotherapy for depressive disorders.

Background: Complete revascularization has demonstrated better outcomes in patients with acute myocardial infarction (AMI) and multivessel disease. However, in the case of left main (LM) culprit lesion AMI with multivessel disease, there is limited evidence to suggest that complete revascularization is better. Methods: We reviewed 16,831 patients in the Korea Acute Myocardial Infarction Registry who were treated from July 2016 to June 2020, and 399 patients were enrolled with LM culprit lesion AMI treated with percutaneous coronary intervention. We categorized the patients as those treated with complete revascularization (n=295) or incomplete revascularization (n=104). The study endpoint was major adverse cardiac and cerebrovascular events (MACCE), a composite of all-cause death, myocardial infarction, ischemia-driven revascularization, stent thrombosis, and stroke. We performed propensity score matching (PSM) and analyzed the incidence of MACCE at 1 year. Results: After PSM, the two groups were well balanced. There was no significant difference between the two groups in MACCE at 1 year (12.1% vs. 15.2%; hazard ratio, 1.28; 95% confidence interval, 0.60–2.74; p=0.524) after PSM. The components of MACCE and major bleeding were also not significantly different. Conclusion There was no significant difference in clinical outcomes between the groups treated with complete or incomplete revascularization for LM culprit lesion AMI with multivessel disease.