Purpose: Compassion is integral to nursing, yet the concept of compassionate care is not thoroughly understood. This study aimed to clarify the nature of compassionate care among Korean clinical nurses using a hybrid model. Methods: This study utilized a mixed methods approach involving hybrid concept analysis to explore the nature and attributes of compassionate care, encompassing both theoretical and empirical stages. In the theoretical stage, the domains, attributes, and a preliminary definition of compassionate care were formulated. In the fieldwork stage, in-depth interviews with 18 nurses were conducted to gather insights, which were integrated in the final stage. Results: Compassionate care was categorized into three domains: cognitive, relational, and behavioral, with 11 defining attributes. It was defined as the capacity to recognize individual patient needs, engage empathetically with their suffering, establish trust through emotional connection, and deliver therapeutic partnership, specialized, personalized, ethical, and holistic care. Conclusion This study advances the understanding of compassionate care in nursing by providing a multidimensional framework. It lays the groundwork for future research and practical applications, emphasizing the need for measurement tools and strategies to promote compassionate care among clinical nurses.

Background: Children, adolescents, and young adults (CAYAs) with severe illnesses require intensive treatment, often relying on medical devices and advanced medical services.Modern medical technology has improved the lifespans of these patients. In addition, CAYAs represent a vulnerable group, resulting in a significant caregiving burden on the entire family.This study examined patterns of medical utilization following diagnosis of a life-limiting condition (LLC). Methods: We establish a cohort of 176,236 CAYAs who were first diagnosed with an LLC using National Health Insurance data between 2011 and 2013. Patients diagnosed with an LLC within the 3 years preceding this period and those who had died were excluded, and only those receiving care at a general medical hospital were included. In total, 25,410,411 claims for medical expenses, outpatient visits, and lengths of stay for medical utilization over the approximately 10 years up to 2020 were investigated (2.3% inpatients, 97.7% outpatients). Results: The average annual medical utilization per LLC patient among CAYAs following initial diagnosis included medical expenses of $1,163, 16.8 outpatient visits, and 18.7 days of admission. Among inpatients, cancer patients averaged $5,340 for total medical expenses and 21.0 days of admission, while non-cancer patients averaged $3,013 and 18.1 days, respectively. The overall average medical expenses during the first year following diagnosis of an LLC were $3,012, whereas for cancer patients they were $5,962. In addition, there was a sharp increase in total medical expenses as death approached, particularly in the last month of life, with a considerable proportion attributable to critical-care treatments. Conclusion Our investigation into medical utilization by CAYAs with an LLC in Korea provides a foundation for healthcare policy development. Timely treatment at each stage and tailored policies that take into account the heterogeneity among diseases are of paramount importance.

Background: There are few safe effective ways to relieve osteoarthritis (OA) pain; as a result, off-label psychotropic drug prescriptions have increased worldwide. This study examined the change in psychotropic drug prescriptions for patients with OA from 2011 to 2020 using the Korean National Health Insurance Service dataset. Methods: The study population consisted of patients with hip or knee OA aged ≥ 65 years.Psychotropic drugs included opioids, benzodiazepines, non-benzodiazepine hypnotics (Z-drugs), anti-epileptics, tricyclic antidepressants, selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), typical antipsychotics, atypical antipsychotics, and anxiolytics. The prevalence and long-term (> 3 months) prescription rates of psychotropic drugs in OA patients were calculated. Results: The study included 1,821,158 patients with OA (mean age 71.7 years; 65.32% female).Of the cohort, 49% had comorbidities for which psychotropics were indicated. The prevalence of psychotropic prescriptions decreased from 58.2% to 52.0% in 2018 and then leveled off.The long-term prescription rate remained constant until 2018 and then increased slightly.The most commonly prescribed psychotropics were opioids and long- and short-acting benzodiazepines. The prescription rates of opioids and long-acting benzodiazepines decreased from 2011 to 2020. For those with psychiatric co-morbidities, the prescription rates of anti-epileptics and SNRIs increased, while the prescription rates of anti-epileptics, SSRIs, other antidepressants, and atypical psychotropics increased for those without such co-morbidities. The most commonly prescribed psychotropics were diazepam and alprazolam, excluding tramadol and tramadol–acetaminophen combination. For those with psychiatric co-morbidities, the prescription rates of gabapentin and fentanyl increased, while for those without such co-morbidities, the prescription rates of lorazepam, fentanyl, escitalopram and quetiapine increased. Conclusion A significant number of older Korean patients with OA were prescribed psychotropic drugs in the absence of comorbidities requiring such drugs, including drugs that have little effect on OA and unfavorable safety profiles in older adults.

Background: We evaluated severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-specific humoral and cellular responses for up to 6 months after the 3rd dose of ancestral coronavirus disease 2019 (COVID-19) vaccination in people living with HIV (PLWH) and healthy controls (HCs) who were not infected with COVID-19. Methods: Anti-spike receptor-binding domain IgG (anti-RBD IgG) concentrations using chemiluminescence immunoassay and neutralizing antibodies using focus reduction neutralization test (FRNT) were assessed at 1 week after each dose of vaccination, and 3 and 6 months after the 3rd dose in 62 PLWH and 25 HCs. T-cell responses using intracellular cytokine stain were evaluated at 1 week before, and 1 week and 6 months after the 3rd dose. Results: At 1 week after the 3rd dose, adequate anti-RBD IgG (> 300 binding antibody unit /mL) was elicited in all PLWH except for one patient with 36 CD4 T-cell count/mm3 . The geometric mean titers of 50% FRNT against wild type (WT) and omicron BA.5 strains of SARS-CoV-2 in PLWH with CD4 T-cell count ≥ 500 cells/mm3(high CD4 recovery, HCDR) were comparable to HC, but they were significantly decreased in PLWH with CD4 T-cell count < 500/mm3 (low CD4 recovery, LCDR). After adjusting for age, gender, viral suppression, and number of preexisting comorbidities, CD4 T-cell counts < 500/mm3 significantly predicted a poor magnitude of neutralizing antibodies against WT, omicron BA.5, and XBB 1.5 strains among PLWH. Multivariable linear regression adjusting for age and gender revealed that LCDR was associated with reduced neutralizing activity (P = 0.017) and interferon-γ-producing T-cell responses (P = 0.049 for CD T-cell; P = 0.014 for CD8 T-cell) against WT, and strongly associated with more decreased cross-neutralization against omicron BA.5 strains (P < 0.001). Conclusion HCDR demonstrated robust humoral and cell-mediated immune responses after a booster dose of ancestral SARS-CoV-2 vaccine, whereas LCDR showed diminished immune responses against WT virus and more impaired cross-neutralization against omicron BA.5 strain.

Objective: This study aims to objectively evaluate turning gait parameters in Parkinson’s disease (PD) patients using 2D-RGB video-based analysis and explore their relationships with imbalance. Methods: We prospectively enrolled PD patients for clinical assessment, balance analysis and gait with 180º turning. Spatiotemporal gait parameters during turning were derived using video-based analysis and correlated with modified Hoehn and Yahr (mHY) stages and center of pressure (COP) oscillations. Results: A total of 64 PD patients were enrolled. The PD patients with higher mHY stages (≥2.5) had significantly longer turning times, greater numbers of steps, wider step bases and less variability in step length during turns. COP oscillations were positively correlated with the mean turning time on both the anterior-posterior and right-left axes. Conclusion Spatiotemporal gait parameter during turning, derived from video-based gait analysis, may represent apromising biomarker for monitoring postural instability in PD patients.

Purpose: To identify US findings suggestive of malignancy in thyroid nodules with follicular lesions of undetermined significance (FLUS) or follicular neoplasm (FN) on fine-needle aspiration cytology (FNAC) and evaluate the diagnostic performance. Materials and Methods: Seventy FLUS (n = 57) or FN (n = 13) nodules on FNAC that underwent surgical excision between February 2018 and November 2020 were selected. US findings were retrospectively reviewed. Orientation, margin, echogenicity, calcification, additional findings of the rim, echogenicity, heterogeneity of the solid portion, and the ratio of anterior posterior diameter to lateral diameter (criteria) were assessed. The diagnostic performances of US findings, criteria, and the Korean Society of Thyroid Radiology Thyroid Imaging Reporting and Data System (K-TIRADS) were evaluated using logistic regression analysis. Results: Microcalcification, homogeneous solid echotexture, and thickened rims were suggestive of malignancy. Our criteria showed a highest area under the ROC curve (AUC) value of 0.771, sensitivity of 97.14%, accuracy of 77.14%, positive predictive value of 93.33%, negative predictive value of 95.24%, and specificity of 97.14%. The criteria showed a significantly higher AUC value than K-TIRADS. Conclusion US findings of homogenous solid portions, thick rims, and microcalcifications suggested malignancy in nodules with FLUS or FN on FNAC. These additional US findings could improve the diagnostic performance of K-TIRADS.

This paper details the development and implementation of Yonsei Medical E-Learning System 3.0 (YES 3.0), a new learning management system (LMS) for Yonsei University College of Medicine. Driven by the need to adapt to a rapidly changing medical education landscape, YES 3.0 addresses the previous system’s limitations and incorporates advanced features designed to improve learning experiences and educational outcomes. The development process involved extensive collaboration among faculty, students, staff, and the system developer, ensuring the system's alignment with the unique needs of the medical education environment. YES 3.0 features real-time monitoring of learning progress, comprehensive evaluation and grade management, personalized learning path recommendations, effective learner history management, and interview/guidance management functionalities. The system also supports the newly revised CDP2023 (Curriculum Development Project 2023) curriculum, with integrated learning across all courses and a strengthened scholarly advanced course. By automating and streamlining various educational processes, YES 3.0 enables maximized learning efficiency, promotes learner-centered education, and supports the cultivation of future medical professionals equipped to navigate the evolving healthcare environment. Implementing the system is expected to have positive impacts on both educational and economic aspects, contributing to the advancement of medical education at Yonsei University College of Medicine. This study also aims to offer insights and expected outcomes that can serve as a reference for other medical schools in adopting and operating LMS, ultimately providing useful information to educators considering establishing a digital learning environment.

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.