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.

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.

Background: Anastomotic leakage (AL) following esophagectomy represents a serious complication that often results in prolonged hospitalization and necessitates repeated interventions, including nothing-by-mouth (NPO) restriction, endoscopic vacuum therapy (EVT), or surgical repair. In this study, we evaluated the patterns and outcomes of AL treatment. Methods: We retrospectively reviewed the medical records of patients who underwent esophagectomy for esophageal cancer at a single center between 2003 and 2020. Of 3,096 examined cases, 181 patients (5.8%) with AL were included in the study: 114 patients (63%) with cervical anastomosis (CA) and 67 (37%) with intrathoracic anastomosis (TA). Results: The incidence of AL was 11.9% in the CA and 3.2% in the TA group (p<0.001).Among patients with CA who developed AL, 87 (76.3%) were managed with NPO, 15 (13.2%) with EVT, and 12 (10.5%) with surgical repair. Over 90% of patients with cervical AL resumed an oral diet by the time of discharge, regardless of treatment method. Among patients with TA and AL, 36 (53.7%) received NPO, 25 (37.7%) underwent EVT, and 6 (9%) required surgery. Of these, 34 patients who were managed with NPO and 19 with EVT could resume an oral diet. However, only 2 patients who underwent surgery resumed an oral diet, and 2 patients required additional EVT. Conclusion Although patients with CA displayed a higher incidence of AL, their rate of successful oral intake exceeded that of those with TA, regardless of treatment method.Among patients exhibiting AL with TA, EVT was more commonly employed than in CA cases, and it appears effective.

Background: The US Food and Drug Administration (FDA) and European Medicines Agency (EMA) approved empagliflozin for reducing cardiovascular mortality and heart failure (HF) hospitalization in patients with both HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF). However, limited data are available on the generalizability of empagliflozin to clinical practice. Therefore, we evaluated real-world eligibility and potential cost-effectiveness based on a nationwide prospective HF registry. Methods: A total of 3,108 HFrEF and 2,070 HFpEF patients from the Korean Acute Heart Failure (KorAHF) registry were analyzed. Eligibility was estimated by inclusion and exclusion criteria of EMPagliflozin outcomE tRial in Patients With chrOnic heaRt Failure With Reduced Ejection Fraction (EMPEROR-Reduced) and EMPagliflozin outcomE tRial in Patients With chrOnic heaRt Failure With Preserved Ejection Fraction (EMPEROR-Preserved) trials and by FDA & EMA label criteria. The cost-utility analysis was done using a Markov model to project the lifetime medical cost and quality-adjusted life year (QALY). Results: Among the KorAHF patients, 91.4% met FDA & EMA label criteria, while 44.7% met the clinical trial criteria. The incremental cost-effectiveness ratio of empagliflozin was calculated at US$6,764 per QALY in the overall population, which is far below a threshold of US$18,182 per QALY. The cost-effectiveness benefit was more evident in patients with HFrEF (US$5,012 per QALY) than HFpEF (US$8,971 per QALY). Conclusion There is a large discrepancy in real-world eligibility for empagliflozin between FDA & EMA labels and clinical trial criteria. Empagliflozin is cost-effective in HF patients regardless of ejection fraction in South Korea health care setting. The efficacy and safety of empagliflozin in real-world HF patients should be further investigated for a broader range of clinical applications.

Background: Diabetes mellitus (DM) is one of the most common endocrine diseases, and the relationship between diabetes and skin diseases is well-known and its mechanisms have been studied. Objective: This study aimed to examine the association between DM and skin diseases. Methods: We used the medical record database provided by the National Health Insurance Service. We constructed a cohort with 1,197,225 patients diagnosed with type 2 DM from 2011 to 2015. We analyzed 3,992,368 medical records of patients with DM who visited the hospital from January 1, 2009 to December 13, 2018 with skin and subcutaneous tissue diseases (ICD-10 code, L00-L99). After that, we compared the changes in skin and subcutaneous tissue diseases before and after the diagnosis of type 2 DM. Results: The number of patients with skin diseases, after the diagnosis of type 2 DM was 1,629,756 (50.6%). The frequency of skin diseases increased after the diagnosis of type 2 DM compared to that before the diagnosis. Particularly, infectious diseases (＋29.03%,p＜0.001), vesiculobullous diseases (＋33.13%, p＜0.001) and ulcerrelated diseases (pressure sores [＋530.18%], and lower extremity ulcers [＋321.56%], p＜0.001) increased sharply whereas dermatitis and eczematous diseases (−9.96%, p＜0.001) and urticaria (−12.99%, p＜0.001) decreased. Conclusion Skin diseases increased following the diagnosis of diabetes, and there were changes in the pattern of skin diseases before and after the diagnosis of diabetes.

Despite the various medications used in clinics, the efforts to develop more effective treatments for depression continue to increase in the past decades mainly because of the treatment-resistant population, and the testing of several hypotheses- and target-based treatments. Undesirable side effects and unresponsiveness to current medications fuel the drive to solve this top global health problem. In this study, we focused on neuroinflammatory response-mediated depression which represents a cluster of depression etiology both in animal models and humans. Several meta-analyses reported that proinflammatory cytokines such as interleukin 6 (IL-6) and tumor necrosis factor-α (TNF-α) were increased in major depressive disorder patients. Inflammatory mediators implicated in depression include type-I interferon and inflammasome pathways. To elucidate the molecular mechanisms of neuroinflammatory cascades underlying the pathophysiology of depression, we introduced hycanthone, an antischistosomal drug, to check whether it can counteract depressive-like behaviors in vivo and normalize the inflammation-induced changes in vitro. Lipopolysaccharide (LPS) treatment increased proinflammatory cytokine expression in the murine microglial cells as well as the stimulation of type I interferon-related pathways that are directly or indirectly regulated by Janus kinase-signal transducer and activator of transcription (JAK-STAT) activation. Hycanthone treatment attenuated those changes possibly by inhibiting the JAK-STAT pathway and inflammasome activation. Hycanthone also ameliorated depressive-like behaviors by LPS. Taken together, we suggest that the inhibitory action of hycanthone against the interferon pathway leading to attenuation of depressive-like behaviors can be a novel therapeutic mechanism for treating depression.

The coronavirus disease-19 (COVID-19) pandemic leaded to inevitable expeditious vaccine rollout without sufficient safety profile. Especially, severe acute respiratory syndrome coronavirus 2 infection has known to induce overreacted immune responses such as releasing of proteinase-3 and myeloperoxidase (MPO) by neutrophil. This overreacted immune response leads to the concern of the development of autoimmune diseases after COVID-19 vaccination. We report the case of de novo MPO-associated systemic vasculitis involving central nervous system following heterogeneous mRNA1273 COVID-19 booster vaccination.

Purpose: This study aimed to investigate the efficacy of adjuvant chemotherapy after neoadjuvant chemoradiotherapy (CCRTx) followed by surgery in patients with esophageal squamous cell carcinoma (ESCC). Materials and Methods: We retrospectively analyzed the data from 382 patients who received neoadjuvant CCRTx and esophagectomy for ESCC between 2003 and 2018. Results: This study included 357 (93.4%) men, and the years median patient age was 63 (range, 40 to 84 years). Overall, 69 patients (18.1%) received adjuvant chemotherapy, whereas 313 patients (81.9%) did not. The median follow-up period was 28.07 months (interquartile range, 15.50 to 62.59). The 5-year overall survival (OS) and disease-free survival were 47.1% and 42.6%, respectively. Adjuvant chemotherapy did not improve OS in all patients, but subgroup analysis revealed that adjuvant chemotherapy improved the 5-year OS in patients with ypT+N+ (24.8% vs. 29.9%, p=0.048), whereas the survival benefit of adjuvant chemotherapy was not observed in patients with ypT0N0, ypT+N0, or ypT0N+. Multivariable analysis revealed that ypStage and adjuvant chemotherapy (hazard ratio, 0.601; p=0.046) were associated with OS in patients with ypT+N+. Freedom from distant metastasis was marginally different according to the adjuvant chemotherapy (48.3% vs. 41.3%, p=0.141). Conclusion Adjuvant chemotherapy after neoadjuvant therapy followed by surgery reduces the distant metastasis in ypT+N+ ESCC patients, thereby improving the OS. The consideration could be given to administration of adjuvant chemotherapy to ypT+N+ ESCC patients with tolerable conditions.