Objective: This study aimed to develop a reliable and valid Mixed State Severity Index (MSSI) to assess mood instability in patients with mood disorders and determine cutoff scores. Methods: Twenty-one items were selected based on Koukopoulos’ criteria for mixed depressive episode, historically referred to as agitated depression, and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision mixed features criteria. The MSSI was administered to 242 patients (major depressive disorder [n=92], bipolar disorder [BD] I [n=78], and BD II [n=72]) and 726 controls. Results: The MSSI demonstrated high internal consistency (α=0.78–0.90). Exploratory factor analysis revealed a stable four-factor structure. Based on receiver operating characteristic analysis, optimal cutoff scores were identified to distinguish mood disorder groups from controls, ranging from 19.5 to 27.5 depending on diagnosis. Conclusion The MSSI is a reliable and valid instrument for assessing the severity of mixed features in patients with mood disorders. The established cutoff scores enhance its clinical utility, providing robust diagnosis and treatment planning support.

Purpose: To report a nationwide survey on neuroblastoma conducted by the Korean Association of Pediatric Surgeons (KAPS) in 2020. Methods: The clinical data of pediatric patients diagnosed with and treated for neuroblastoma from 2005 to 2019 in 19 hospitals of KAPS members were collected. Survival and prognostic factor analyses were performed using the log rank test and Cox proportional hazard analysis. A p-value <0.05 was considered significant. Results: A total of 669 patients with neuroblastoma were registered for the study. The results were presented and discussed at the 36th annual meeting of the KAPS, which was held in Seoul on August 21, 2020. Conclusion This study provides information on patient demographics, prognostic outcomes, and comprehensive treatment outcomes for neuroblastoma. The study is expected to be an important reference for improving pediatric surgeons’ understanding and treatment of neuroblastoma.

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.

Objective: Interpersonal sensitivity, characterized by a heightened awareness of others’ behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. Methods: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. Results: Network analysis detected five communities. Item 10 (“I worry about being criticized for things that I have said or done”) showed the highest value in strength. Multiple items on “Interpersonal Worry/Dependency” and “Low Self-Esteem” showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. Conclusion Our findings emphasize the importance of addressing “Interpersonal Worry/Dependency” and “Low Self-Esteem” in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

Objective: Mood instability (MI) is a clinically significant trait associated with psychiatric disorders. However, there are no concise measurements to evaluate MI. The initial Mood Instability Questionnaire-Trait (MIQ-T) was developed to fill this gap. The current study aimed to create a short form of MIQ-T (MIQ-T-SF) that measures MI with high validity and reliability in the Korean general population. Methods: Of the 59 items in the MIQ-T, 17 items were chosen for the MIQ-T-SF following the factor analysis process. In total, 540 participants completed the MIQ-T-SF. Cronbach’s alpha and McDonald’s omega were used to evaluate reliability. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to determine construct validity. Concurrent validity was confirmed via comparisons with Personality Assessment Inventory-Borderline Features Scale. Measurement invariance across gender and age groups was confirmed before analyzing differences in scores using Kruskal-Wallis test. Results: The MIQ-T-SF displayed expected correlations and high internal consistency (α=0.71–0.90, Ωt=0.72–0.92). Using EFA and CFA, a five-factor structure was confirmed. Measurement invariance was supported, and gender differences were observed. Conclusion The MIQ-T-SF is an accurate and reliable method to detect MI in the Korean general population. The study’s results offer new perspectives for future studies on MI.

Objective: Mood disorder and borderline personality pathology (BPP) are frequently comorbid and relate to childhood trauma. We investigated the relationship between childhood trauma and BPP features in mood disorder patients versus controls. Methods: A total of 488 mood disorder patients, particularly major depressive disorder (MDD), bipolar I disorder (BD I), and bipolar II disorder (BD II), and 734 controls were included. We examined between-group BPP-related differences and correlated between BPP and childhood trauma using the Childhood Trauma Questionnaire-Short Form (CTQ) and the Personality Assessment Inventory–Borderline Features Scale. Results: BD II patients showed significantly higher BPP. Emotional abuse and neglect were prominently associated with BPP, while affective instability and negative relationships exhibited a stronger association with childhood trauma. We also found a positive relationship between childhood trauma and BPP in MDD, BD I, and BD II patients. Conclusion The findings of the present study imply that BPP features are more likely to be found in patients with BD II than BD I or MDD. Mood disorder patients with severe childhood trauma may have higher BPP features. Thus, further study of the relationship between childhood trauma and BPP features could improve the therapeutic approaches and help understand patients with mood disorders.

Objective: The Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire (TEMPS-A) has been validated in more than 30 languages and is noted for its broad application in research and clinical settings. This study presents the first attempt to examine the reliability and validity of the TEMPS-A in Korea. Methods: A total of 540 non-clinical participants completed the Korean TEMPS-A, which was adapted from the original English version via a comprehensive translation procedure. Reliability was assessed using Cronbach’s α, and associations between temperaments were examined using Spearman’s correlation coefficient. Exploratory factor analysis (EFA) was performed, and differences in TEMPS-A scores between the gender- and age-based groups were examined using Kruskal-Wallis analysis. Results: The Korean TEMPS-A exhibited excellent internal consistency (0.70–0.91) and significant correlations between subscales. EFA resulted in a two-factor structure: Factor I (depressive, cyclothymic, irritable, and anxious) and Factor II (hyperthymic). Gender and age group differences were observed. Conclusion Overall, our results suggest that TEMPS-A is a reliable and valid measure of affective temperaments for the Korean population. This study opens new possibilities for further research on affective temperaments and their related traits.

Purpose: The severity of a patient’s medical condition, changing pharmacodynamics and pharmacokinetics, and variability in medication highlight the importance of pharmacological intervention by intensive care unit (ICU) specialized pharmacists.
Methods: Retrospective observations of ICU interventions (omission, changes in medicine, side effects, changes in administration route and dosage, redundancy, and nutritional care) performed between April 2017 and March 2018, determined by an interdisciplinary team (including a specialized ICU pharmacist and a surgical intensivist) on their surgical ICU round, were analyzed. Medicinal prescriptions were screened weekly during the surgical ICU round, and interventions were made if any corrections were necessary. Two days later another team including a surgical intensivist, a pharmacist, and a nutritionist evaluated the patients’ nutritional status (performed weekly).
Results: In the 23-bed ICU, the average number of patients whose prescriptions were examined was 22.38 per surgical round. There were 382 interventions made over 1 year, which was 9.68 interventions per day. The interventions were for nutritional care (161 cases, 42.2%), followed by changes in administration route and dosage (94 cases, 24.6%), omission (59 cases, 15.5%), redundancy (40 cases, 10.4%), changes in medicine (15 cases, 3.9%), and side effects (13 cases, 3.4%).
Conclusion The conditions of patients admitted to ICU are typically unstable. Pharmacological interventions suggested by a specialized pharmacist may help control the changing medical condition of patients in ICU. A higher participation of pharmacists specialized in working in an interdisciplinary ICU team-based system could lead to safer treatments.

Background: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea.For rapid triage, we studied machine learning-based triage systems composed of a speech recognition model and natural language processing-based classification. Methods: We simulated 762 triage cases that consisted of 18 classes with six types of the main symptom (chest pain, dyspnea, fever, stroke, abdominal pain, and headache) and three levels of KTAS. In addition, we recorded conversations between emergency patients and clinicians during the simulation. We used speech recognition models to transcribe the conversation. Bidirectional Encoder Representation from Transformers (BERT), support vector machine (SVM), random forest (RF), and k-nearest neighbors (KNN) were used for KTAS and symptom classification. Additionally, we evaluated the Shapley Additive exPlanations (SHAP) values of features to interpret the classifiers. Results: The character error rate of the speech recognition model was reduced to 25.21% through transfer learning. With auto-transcribed scripts, support vector machine (area under the receiver operating characteristic curve [AUROC], 0.86; 95% confidence interval [CI], 0.81–0.9), KNN (AUROC, 0.89; 95% CI, 0.85–0.93), RF (AUROC, 0.86; 95% CI, 0.82–0.9) and BERT (AUROC, 0.82; 95% CI, 0.75–0.87) achieved excellent classification performance.Based on SHAP, we found “stress”, “pain score point”, “fever”, “breath”, “head” and “chest” were the important vocabularies for determining KTAS and symptoms. Conclusion We demonstrated the potential of an automatic KTAS classification system using speech recognition models, machine learning and BERT-based classifiers.