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.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Connective tissue disease (CTD), comprising a range of autoimmune disorders, is often accompanied by lung involvement, which can lead to life-threatening complications. The primary types of CTDs that manifest as interstitial lung disease (ILD) include rheumatoid arthritis, systemic sclerosis, Sjögren’s syndrome, mixed CTD, idiopathic inflammatory myopathies, and systemic lupus erythematosus. CTD-ILD presents a significant challenge in clinical diagnosis and management due to its heterogeneous nature and variable prognosis. Early diagnosis through clinical, serological, and radiographic assessments is crucial for distinguishing CTD-ILD from idiopathic forms and for implementing appropriate therapeutic strategies. Hence, we have reviewed the multiple clinical manifestations and diagnostic approaches for each type of CTD-ILD, acknowledging the diversity and complexity of the disease. The importance of a multidisciplinary approach in optimizing the management of CTD-ILD is emphasized by recent therapeutic advancements, which include immunosuppressive agents, antifibrotic therapies, and newer biological agents targeting specific pathways involved in the pathogenesis. Therapeutic strategies should be customized according to the type of CTD, the extent of lung involvement, and the presence of extrapulmonary manifestations. Additionally, we aimed to provide clinical guidance, including therapeutic recommendations, for the effective management of CTD-ILD, based on patient, intervention, comparison, outcome (PICO) analysis.

Background: Small cell lung cancer (SCLC) is called ‘smoker’s disease’ because it is strongly associated with smoking and most cases occur in smokers. However, it can also occur in never smokers. We investigated the clinical features of never smokers with SCLC and compared their treatment outcomes with those of smokers with SCLC. Methods: We retrospectively reviewed the clinical data of patients who had proven SCLC and had received chemotherapy at a single cancer center between July 2002 and April 2021. Results: Of 1,643 patients, 1,416 (86.2%) were enrolled in this study. A total of 162 (11.4%) and 1,254 (88.6%) patients were never smokers and smokers, respectively. There were more female never smokers than smokers (n=130; 80.2% vs. 79, 6.3%, p=0.000), and the incidence of ischemic heart disease was lower among never smokers than among smokers (4/1,416, [2.5%] vs. 83/1,416 [6.6%], p=0.036). Never smokers showed less symptoms at diagnosis than smokers (80.9% vs. 87.2%, p=0.037); however, they showed more toxicity after first-line treatment (61.7% vs. 47.8%, p=0.001). The objective response rate (ORR) was significantly higher in never smokers (74.1% vs. 59.6%, p=0.000). In the multivariate analysis, never smoking and second-line treatment were associated with a better ORR. However, progression-free survival and overall survival were not significantly different between never smokers and smokers. Conclusion In conclusion, never smokers accounted for 11.4% of patients with SCLC. They had distinguishing clinical characteristics and showed better chemotherapeutic responses than smokers.

Background: This study aimed to identify the clinical characteristics of multidrug-resistant/ rifampicin-resistant tuberculosis (MDR/RR-TB) in the Republic of Korea. Methods: Data of notified people with tuberculosis between July 2018 and December 2021 were retrieved from the Korea Tuberculosis Cohort database. MDR/RR-TB was further categorized according to isoniazid susceptibility as follows: multidrug-resistant tuberculosis (MDR-TB), rifampicin-monoresistant tuberculosis (RMR-TB), and RR-TB if susceptibility to isoniazid was unknown. Multivariable logistic regression analysis was conducted to identify the factors associated with MDR/RR-TB. Results: Between 2018 and 2021, the proportion of MDR/RR-TB cases among all TB cases and TB cases with known drug susceptibility test results was 2.1% (502/24,447). The proportions of MDR/RR-TB and MDR-TB cases among TB cases with known drug susceptibility test results were 3.3% (502/15,071) and 1.9% (292/15,071), respectively. Among all cases of rifampicin resistance, 31.7% (159/502) were RMR-TB and 10.2% (51/502) were RR-TB. Multivariable logistic regression analyses revealed that younger age, foreigners, and prior tuberculosis history were significantly associated with MDR/ RR-TB. Conclusion Rapid identification of rifampicin resistance targeting the high-risk populations, such as younger generations, foreign-born individuals, and previously treated patients are necessary for patient-centered care.

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.

Purpose: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries. Materials and Methods: Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers. Results: A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001). Conclusion ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.

Methods: Uropathogenic E. coli (UPEC) strains were analyzed for phylogenetic grouping polymerase chain reaction, AMR, transferable resistance plasmids, and multilocus sequence typing. Results: Sixty-seven UPECs were isolated from urine samples of dogs (n = 57) and cats (n = 10).Regarding age, the incidence of UTI was the highest in the 11 to 15 years range (46.3%, 31/67). Regarding sex, it accounted for 58.2% (n = 39) in female dogs and 11.9% (8/67) in female cats. Phylogroup B2 was the most frequent (n = 51, 75.0%) among all strains, followed by D (16.2%), A (7.4%), and B1 (1.5%). Thirty-seven (55.2%) UPECs were multidrugresistant (MDR), and 24 (35.8%) of them belonged to phylogroup B2. Extended-spectrum cephalosporin and carbapenemase genes were detected in 18 (26.9%) UPECs and plasmids carrying these resistance genes were conjugated between strains. Thirty sequence types (STs) were identified among the total strains. Among the UPECs (n = 51) with phylogroup B2, 23 STs were identified, with ST73 being the most frequent (n = 12, 17.9%), followed by ST131 (n = 9, 13.4%). Conclusions and Relevance: Phylogroup B2 strains, particularly ST73 and ST121, were most prevalent in UPECs from Korean companion dogs and cats. For MDR UPECs, appropriate antibiotic selection is essential for the treatment of UTIs.

Objective: To improve our understanding of EPEC, this study focused on analyzing and comparing the genomic characteristics of EPEC isolates from humans and companion animals in Korea. Methods: The whole genome of 26 EPEC isolates from patients with diarrhea and 20 EPEC isolates from companion animals in Korea were sequenced using the Illumina HiSeq X (Illumina, USA) and Oxford Nanopore MinION (Oxford Nanopore Technologies, UK) platforms. Results: Most isolates were atypical EPEC, and did not harbor the bfpA gene. The most prevalent virulence genes were found to be ompT (humans: 61.5%; companion animals:60.0%) followed by lpfA (humans: 46.2%; companion animals: 60.0%). Although pangenome analyses showed no apparent correlation among the origin of the strains, virulence profiles, and antimicrobial resistance profiles, isolates included in clade A obtained from both humans and companion animals exhibited high similarity. Additionally, all the isolates included in clade A encoded the ompT gene and did not encode the hlyE gene. The two isolates from companion animals harbored an incomplete bundle-forming pilus region encoding bfpA and bfpB. Moreover, the type IV secretion system-associated genes tra and trb were found in the bfpA-encoding isolates from humans. Conclusions and Relevance: Whole-genome sequencing enabled a more accurate analysis of the phylogenetic structure of EPEC and provided better insights into the understanding of EPEC epidemiology and pathogenicity.

Background and Objectives: The Korean Organ Transplant Registry (KOTRY) provided data for this third official report on adult heart transplantation (HT), including information from 709 recipients. Methods: Data from HTs performed at seven major centers in Korea between March 2014 and December 2020 were analyzed, focusing on immunosuppression, acute rejection, cardiac allograft vasculopathy (CAV), post-transplant survival, and mechanical circulatory support (MCS) usage. Results: The median ages of the recipients and donors were 56.0 and 43.0 years, respectively.Cardiomyopathy and ischemic heart disease were the most common preceding conditions for HT. A significant portion of patients underwent HT at waiting list status 1 and 0. In the multivariate analysis, a predicted heart mass mismatch was associated with a higher risk of 1-year mortality. Patients over 70 years old had a significantly increased risk of 6-year mortality. The risk of CAV was higher for male donors and donors older than 45 years. Acute rejection was more likely in patients with panel reactive antibody levels above 80%, while statin use was associated with a reduced risk. The employment of left ventricular assist device as a bridge to transplantation increased from 2.17% to 22.4%. Pre-transplant extra-corporeal membrane oxygenation was associated with worse post-transplant survival. Conclusions In this third KOTRY report, we analyzed changes in the characteristics of adult HT recipients and donors and their impact on post-transplant outcomes. The most notable discovery was the increased use of MCS before HT and their impact on post-transplant outcomes.