Purpose: Postoperative complications following gastric cancer surgery significantly impact patient outcomes, yet standardized definitions for these events have not been consistently applied across institutions in Korea. This study aimed to develop a consensus-based, standardized complication classification system specific to gastrectomy for gastric cancer as part of the Korean Quality Improvement Platform in Surgery (K-QIPS) initiative. Methods: As part of K-QIPS, a dedicated task force team (TFT) was formed with surgical experts from fourteen high-volume hospitals across Korea. The TFT conducted ten formal meetings to review existing literature and international guidelines, and incorporated findings from randomized controlled trials. The final complication list was developed through expert consensus and structured into a standardized framework. A Data Entry Manual was created to support consistent data collection by surgical clinical reviewers. Results: The TFT defined specific postoperative complications following gastrectomy for gastric cancer, including anastomotic leakage, duodenal stump leakage, pancreatic fistula, intra-abdominal and luminal bleeding, delayed gastric emptying, and internal hernia. Notably, internal hernia was described in standardized form for the first time. General complications were developed first and overlapped in part with the gastric cancer-specific list. The task force also produced a Data Entry Manual that provides practical instructions to ensure consistency and accuracy in complication reporting. Conclusion This nationwide consensus initiative established the first standardized complication classification system for gastric cancer surgery in Korea. The proposed definitions and data entry system are expected to improve complication reporting, enable multicenter research, support surgical quality benchmarking, and ultimately enhance patient outcomes.

Purpose: The aim of this study is to compare the detection ability of quality of life (QoL) changes and responsiveness of the KOrean QUality of life in Stomach cancer patients Study group (KOQUSS)-40 and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ). Materials and Methods: A multicenter prospective observational study was conducted to evaluate QoL changes after various gastrectomies between January 2021 and April 2022. Participants were instructed to complete the KOQUSS-40 and EORTC QLQ-C30/STO22 preoperatively and at 1, 3, 6, and 12 months postoperatively. QoL changes over time and QoL responsiveness were assessed for each questionnaire. Results: Data from 491 patients who underwent curative gastrectomy for gastric cancer at 22 institutions were analyzed. The summary scores of the KOQUSS-40 and EORTC QLQ-STO22 showed significant differences between the total and proximal gastrectomy groups (p=0.044 and p=0.038, respectively), but no difference was observed for the EORTC QLQ-C30. Dysphagia on the KOQUSS-40 was significantly different between the total and proximal gastrectomy groups (p=0.031); however, dysphagia on the EORTC QLQ-STO22 did not differ. The responsiveness of the KOQUSS-40 was similar to that of the EORTC QLQ in patients who experienced ≥ 10% body weight loss, but approximately 10% less in patients receiving adjuvant chemotherapy than the EORTC QLQ. Conclusion KOQUSS-40 has several advantages over EORTC QLQ-C30/STO22 when comparing QoL between the total and proximal gastrectomy groups. The findings provide information for researchers investigating the QoL of patients who have undergone curative gastrectomy for gastric cancer.

Objective: Patients with panic disorder (PD) are approximately four times more likely to experience suicidal thoughts and attempts compared to healthy controls (HCs). Despite the elevated risk compared to HCs, the relationship between cortical thickness (CT) in PD and suicidality remains underexplored. Methods: We recruited 161 right-handed participants, including 82 PD patients and 79 HCs, and assessed them using a comprehensive battery of psychological scales, including the Scale for Suicidal Ideation (SSI), Early Trauma Inventory Self Report-Short Form, Neuroticism-Extraversion-Openness Personality Inventory-Neuroticism (NEO-N), State-Trait Anxiety Inventory-Trait Anxiety (STAI-T), Panic Disorder Severity Scale (PDSS), and Beck Depression Inventory. Results: In whole-brain vertex-wise group comparison, patients with PD demonstrated significantly lower CT values in the insula, lateral occipital sulcus, and precentral gyrus compared to HCs. Notably, paradoxical significant positive correlations were observed between SSI total scores and CT in the above-mentioned regions within the PD cohort.Pearson’s correlation analyses further indicated that CT in these regions may be linked to high levels of early trauma, trait anxiety (e.g., NEO-N, STAI-T), panic symptom severity (e.g., PDSS), and treatment response in patients with PD. Conclusion This study suggest that suicidality in PD may be associated with CT in specific EFN regions related to suicidal brain and that CT in these regions could play a critical role in anxiety symptomatology in PD.

Background: Transthoracic echocardiography (TTE) requires time-intensive integration of quantitative measure‑ ments and qualitative visual assessment. Fully automated artificial intelligence (AI)-based analysis may reduce total analysis time while preserving accuracy, but systematic real-world validation remains limited. Methods: This prospective, single-center pilot study enrolled 40 TTE examinations. Identical deidentified DICOM datasets were independently provided to a trained cardiac sonographer and a fully automated AI system comprising quantitative and qualitative visual interpretation modules. All outputs were compared with a cardiologist-adjudicated reference standard. Primary endpoints were total analysis time and noninferiority of AI-derived left ventricular ejection fraction (LVEF) versus the reference standard, with a prespecified margin of 3 percentage points (one-sided α = 0.025). Results: Median analysis time was 94 s (interquartile range [IQR], 82–106 s) for the AI workflow versus 490 s (IQR, 438–626 s) for the human workflow (P < 0.001). AI-derived LVEF met the noninferiority criterion (mean difference, 0.00 percentage points; upper one-sided 95% confidence bound, 1.41 percentage points; P < 0.001), with an intraclass correlation coefficient (ICC) of 0.902 (95% confidence interval, 0.822–0.947). ICCs for secondary quantitative indi‑ ces ranged from 0.625 to 0.989. For aortic regurgitation severity grading, AI’s overall accuracy was 75.0% (quadratic weighted κ = 0.762), compared with 82.5% for human interpretation (κ = 0.812, McNemar P = 0.579). Conclusions Fully automated AI-assisted TTE analysis substantially reduced total analysis time while maintaining noninferior LVEF accuracy and acceptable performance across secondary quantitative and qualitative indices. These findings support the use of AI as a practical workflow accelerator in routine echocardiography.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Background and Objectives: Although various cardiac parameters on echocardiography have clinical importance, their measurement by conventional manual methods is time-consuming and subject to variability. We evaluated the feasibility, accuracy, and predictive value of an artificial intelligence (AI)-based automated system for echocardiographic analysis in patients with ST-segment elevation myocardial infarction (STEMI). Methods: The AI-based system was developed using a nationwide echocardiographic dataset from five tertiary hospitals, and automatically identified views, then segmented and tracked the left ventricle (LV) and left atrium (LA) to produce volume and strain values. Both conventional manual measurements and AI-based fully automated measurements of the LV ejection fraction and global longitudinal strain, and LA volume index and reservoir strain were performed in 632 patients with STEMI. Results: The AI-based system accurately identified necessary views (overall accuracy, 98.5%) and successfully measured LV and LA volumes and strains in all cases in which conventional methods were applicable. Inter-method analysis showed strong correlations between measurement methods, with Pearson coefficients ranging 0.81–0.92 and intraclass correlation coefficients ranging 0.74–0.90. For the prediction of clinical outcomes (composite of all-cause death, re-hospitalization due to heart failure, ventricular arrhythmia, and recurrent myocardial infarction), AI-derived measurements showed predictive value independent of clinical risk factors, comparable to those from conventional manual measurements. Conclusions Our fully automated AI-based approach for LV and LA analysis on echocardiography is feasible and provides accurate measurements, comparable to conventional methods, in patients with STEMI, offering a promising solution for comprehensive echocardiographic analysis, reduced workloads, and improved patient care.

Objective: This study aimed to empirically evaluate the effectiveness of chronic disease management services utilizing ICT for patients with chronic illnesses. Methods: From May to December, 2023, 452 people who were diagnosed with hypertension and diabetes at 9 participating public health centers were provided with customized health care services for 24 weeks, and 15 performance indicators were analyzed to evaluate their effectiveness. Results: Health behavior indicators and health risk factors decreased before and after participation in the project, blood pressure control rate, hypertension and diabetes management rate, medication compliance, weight, BMI, BP, WC, FBG, and HDL-cholesterol improved(p<0.001).Service factors that influence the improvement of health behaviors included the number of activity monitor transmissions(p=0.049), confirmed concentrated consultations on physical activity(p=0.003) and nutrition(p=0.005), and the adherence to medication missions for hypertension(p=0.020).As for service factors influencing chronic disease management, the improvement in blood pressure regulation rate was due to the number of times the blood pressure monitor was linked(p=0.004), and the number of confirmed intensive consultations on physical activity(p=0.026), and nutrition(p=0.049); the improvement in hypertension control rate was due to the number of times the activity monitor and blood pressure monitor were linked(p<0.001), and the number of hypertension medication missions carried out (p=0.004); and the improvement in diabetes control rate was due to the number of times the blood pressure monitor(p=0.022) and blood sugar system were linked(p=0.017). Conclusion Although this study has limitations as a comparative study before and after the service, it has proved that chronic disease management using ICT has a positive effect on improvement of health behavior indicator, reduction of health risk factors, hypertension, diabetes management index, weight, BMI, TG, BP, FBG improvement.