Background: Mycoplasma pneumoniae is a major cause of community-acquired pneumonia (CAP) in children, with a rising incidence of macrolide resistance. Early diagnosis is crucial for reducing the disease burden; however, current diagnostic tools have limitations.We evaluated the diagnostic accuracy of serological assays and their performance based on symptom onset in children with CAP. Methods: From September 2023 to September 2024, we prospectively enrolled children with CAP, classified as M. pneumoniae pneumonia (MPP) or non-MPP, from 16 hospitals in Korea. Serological testing included chemiluminescence immunoassay (CLIA) and ELISA for detecting IgM and IgG, along with particle agglutination (PA) for total antibody measurements. Serological responses were analyzed at different times after symptom onset (0–4, 5–9, and 10–21 days). Results: Among 472 children with CAP (362 MPP, 110 non-MPP), 138 (29.2%) underwent PA testing, and 334 (70.8%) underwent IgM testing. PA at a 1:640 cutoff showed 48.0% sensitivity and 100% specificity. CLIA and ELISA showed comparable sensitivities (69.1% vs. 69.2%) and specificities (76.9% vs. 66.7%) for IgM testing. Seropositivity increased significantly with time since symptom onset (P for trend < 0.001), reaching 97.9% for IgM, 62.5% for IgG, and 94.7% for PA at 10–21 days. Conclusions The time post-symptom onset significantly influenced the diagnostic utility of serological tests for pediatric MPP, which showed limited value during the early stage of illness. These findings emphasize the importance of symptom onset-based interpretation of serological test results and their utility in complementing PCR when optimizing MPP diagnosis in children.

Objectives: This study investigated medication perceptions, adherence patterns, self-discontinuation experiences, and information sources among psychiatric outpatients to provide evidence for improving adherence strategies. Methods: A cross-sectional survey was conducted with 79 outpatients from a University Hospital, Department of Psychiatry. Self-administered questionnaires assessed diagnostic awareness, medication perceptions, adherence behaviors, discontinuation experiences, side effects, and information sources. Results: Overall, 89.7% knew their psychiatric diagnosis and 88.2% perceived medication as effective. While 73.1% rarely forgot medication, 35.9% had previously self-discontinued treatment. Medication adherence was significantly associated with previous discontinuation experience (p=0.006), whereas diagnostic awareness and efficacy perception were not. Primary discontinuation reasons were symptom improvement (53.6%) and physical discomfort (35.7%). Common side effects included weight gain (n=31), daytime drowsiness (n=26), memory impairment (n=24), and concentration problems (n=22). Patients primarily obtained side effect information from TV/internet (27.8%) rather than healthcare providers (20.3%). Most patients desired additional information about side effects (57.0%) and medication effects (54.4%). Conclusion Daily medication-taking behaviors were more predictive of treatment discontinuation than cognitive factors in this outpatient sample. Discontinuation due to symptom improvement and reliance on non-medical information sources highlights the need for enhanced patient education regarding relapse risks and systematic provision of accurate medication information.

Background and Objectives: Graves’ ophthalmopathy (GO) is an autoimmune inflammatory disorder that can adversely affect quality of life in patients with Graves’ disease (GD). The objective of this study was to characterize the clinical features of patients with GO and to identify risk factors associated with its development and the need for anti-inflammatory treatment. Materials and Methods: In this multicenter, retrospective observational study, 818 patients with GD were identified via electronic medical record review. Clinical characteristics were assessed, and logistic regression analyses were performed to identify risk factors for GO development and the need for anti-inflammatory treatment. Results: Among the 818 patients with GD, 135 (16.5%) developed GO, and 60 (7.3%) of these patients received anti-inflammatory treatment. GO was diagnosed at the time of GD diagnosis in 54.8% of cases, and proptosis and eyelid/orbital swelling were the common presenting features. In multivariable analysis, female sex (odds ratio [OR]: 1.75, confidence interval [CI]: 1.02-3.03), goiter (OR: 1.71, CI: 1.08-2.71), and smoking (ex-smokers: OR, 2.18; 95% CI: 1.02-4.65; current smokers: OR, 3.11; CI, 1.78-5.44) were independently associated with GO development, whereas diabetes (OR: 0.35, CI: 0.14-0.89) was inversely associated. Higher total cholesterol (OR: 1.31, CI: 1.01-1.04) and elevated thyrotropin-binding inhibitory immunoglobulin levels (OR: 1.07, CI: 1.02-1.11) were also significantly associated with the need for anti-inflammatory treatment. Conclusion This study delineated the clinical features of GO and identified risk factors for its development and the need for anti-inflammatory treatment in patients with GD, providing valuable information for the management of GO in Korean patients.

Purpose: This study evaluated the clinical outcomes and prognostic factors in patients with borderline resectable pancreatic cancer (BRPC) and locally advanced pancreatic cancer (LAPC) treated with upfront FOLFIRINOX followed by local-regional therapy (LRT), surgical resection (SR), and radiotherapy (RT). We aimed to identify specific patient subgroups for which RT may serve as a reasonable alternative to SR for local tumor control. Methods: We retrospectively analyzed 116 patients (SR group, n= 70; RT group, n= 46) at a single center between 2015 and 2020. Survival outcomes were compared based on LRT modalities, focusing on identifying subgroups in which RT provided an efficacy comparable to that of SR. Results: Among 116 patients, the SR group achieved a significantly higher 5-year overall survival (OS) than the RT group (27.1% vs. 8.7%, P< 0.0001), despite similar progression-free survival (P= 0.23). Significant prognostic factors for OS included carbohydrate antigen 19-9 (CA19-9) response in BRPC (P= 0.02) and radiologic partial response in LAPC (P= 0.05). Subgroup analysis revealed that, while SR provided a survival advantage in CA19-9 responders, no significant difference in OS was observed between SR and RT in CA19-9 non-responders (P= 0.37). Conclusion Although surgery remains the gold standard, RT may be considered a justifiable local alternative for CA19-9 non-responders and surgically ineligible patients with LAPC, yielding comparable outcomes in these specific, biologically unfavorable subgroups.

Background: Community acquired lower respiratory tract infection (LRTI) is a leading cause for hospitalization in children and important cause for antibiotic prescription. We aimed to describe the aetiology of LRTI in children and analyse factors associated with bacterial or viral infection. Methods: Patients aged < 19 years with a diagnosis of LRTI were identified from the Observational Medical Outcomes Partnership Common Data Model Database of Seoul National University Bundang Hospital from January 2005–July 2019, and their clinical characteristics were obtained from the electronic medical records and retrospectively reviewed. Results: Among 5,924 cases of LRTI, 74.2% were pneumonia and 25.8% were bronchiolitis/ bronchitis. Patients’ median age was 1.8 (interquartile range, 3.1) years and 79.9% were < 5 years old. Pathogens were identified in 37.8%; 69.1% were viral and 30.9% were bacterial/ Mycoplasma pneumoniae. Respiratory syncytial virus was most common (70.9%) among viruses and M. pneumoniae (94.6%) was most common among bacteria. Viral LRTI was associated with winter, age < 2 years, rhinorrhoea, dyspnoea, lymphocytosis, thrombocytosis, wheezing, stridor, chest retraction, and infiltration on imaging. Bacteria/ M. pneumoniae LRTI was associated with summer, age ≥ 2 years, fever, decreased breathing sounds, leucocytosis, neutrophilia, C-reactive protein elevation, and positive imaging findings (consolidation, opacity, haziness, or pleural effusion). Conclusion In children with LRTI, various factors associated with viral or bacterial/ M. pneumoniae infections were identified, which may serve as guidance for antibiotic prescription.

Background: Community acquired lower respiratory tract infection (LRTI) is a leading cause for hospitalization in children and important cause for antibiotic prescription. We aimed to describe the aetiology of LRTI in children and analyse factors associated with bacterial or viral infection. Methods: Patients aged < 19 years with a diagnosis of LRTI were identified from the Observational Medical Outcomes Partnership Common Data Model Database of Seoul National University Bundang Hospital from January 2005–July 2019, and their clinical characteristics were obtained from the electronic medical records and retrospectively reviewed. Results: Among 5,924 cases of LRTI, 74.2% were pneumonia and 25.8% were bronchiolitis/ bronchitis. Patients’ median age was 1.8 (interquartile range, 3.1) years and 79.9% were < 5 years old. Pathogens were identified in 37.8%; 69.1% were viral and 30.9% were bacterial/ Mycoplasma pneumoniae. Respiratory syncytial virus was most common (70.9%) among viruses and M. pneumoniae (94.6%) was most common among bacteria. Viral LRTI was associated with winter, age < 2 years, rhinorrhoea, dyspnoea, lymphocytosis, thrombocytosis, wheezing, stridor, chest retraction, and infiltration on imaging. Bacteria/ M. pneumoniae LRTI was associated with summer, age ≥ 2 years, fever, decreased breathing sounds, leucocytosis, neutrophilia, C-reactive protein elevation, and positive imaging findings (consolidation, opacity, haziness, or pleural effusion). Conclusion In children with LRTI, various factors associated with viral or bacterial/ M. pneumoniae infections were identified, which may serve as guidance for antibiotic prescription.

Background: Community acquired lower respiratory tract infection (LRTI) is a leading cause for hospitalization in children and important cause for antibiotic prescription. We aimed to describe the aetiology of LRTI in children and analyse factors associated with bacterial or viral infection. Methods: Patients aged < 19 years with a diagnosis of LRTI were identified from the Observational Medical Outcomes Partnership Common Data Model Database of Seoul National University Bundang Hospital from January 2005–July 2019, and their clinical characteristics were obtained from the electronic medical records and retrospectively reviewed. Results: Among 5,924 cases of LRTI, 74.2% were pneumonia and 25.8% were bronchiolitis/ bronchitis. Patients’ median age was 1.8 (interquartile range, 3.1) years and 79.9% were < 5 years old. Pathogens were identified in 37.8%; 69.1% were viral and 30.9% were bacterial/ Mycoplasma pneumoniae. Respiratory syncytial virus was most common (70.9%) among viruses and M. pneumoniae (94.6%) was most common among bacteria. Viral LRTI was associated with winter, age < 2 years, rhinorrhoea, dyspnoea, lymphocytosis, thrombocytosis, wheezing, stridor, chest retraction, and infiltration on imaging. Bacteria/ M. pneumoniae LRTI was associated with summer, age ≥ 2 years, fever, decreased breathing sounds, leucocytosis, neutrophilia, C-reactive protein elevation, and positive imaging findings (consolidation, opacity, haziness, or pleural effusion). Conclusion In children with LRTI, various factors associated with viral or bacterial/ M. pneumoniae infections were identified, which may serve as guidance for antibiotic prescription.

Background: Community acquired lower respiratory tract infection (LRTI) is a leading cause for hospitalization in children and important cause for antibiotic prescription. We aimed to describe the aetiology of LRTI in children and analyse factors associated with bacterial or viral infection. Methods: Patients aged < 19 years with a diagnosis of LRTI were identified from the Observational Medical Outcomes Partnership Common Data Model Database of Seoul National University Bundang Hospital from January 2005–July 2019, and their clinical characteristics were obtained from the electronic medical records and retrospectively reviewed. Results: Among 5,924 cases of LRTI, 74.2% were pneumonia and 25.8% were bronchiolitis/ bronchitis. Patients’ median age was 1.8 (interquartile range, 3.1) years and 79.9% were < 5 years old. Pathogens were identified in 37.8%; 69.1% were viral and 30.9% were bacterial/ Mycoplasma pneumoniae. Respiratory syncytial virus was most common (70.9%) among viruses and M. pneumoniae (94.6%) was most common among bacteria. Viral LRTI was associated with winter, age < 2 years, rhinorrhoea, dyspnoea, lymphocytosis, thrombocytosis, wheezing, stridor, chest retraction, and infiltration on imaging. Bacteria/ M. pneumoniae LRTI was associated with summer, age ≥ 2 years, fever, decreased breathing sounds, leucocytosis, neutrophilia, C-reactive protein elevation, and positive imaging findings (consolidation, opacity, haziness, or pleural effusion). Conclusion In children with LRTI, various factors associated with viral or bacterial/ M. pneumoniae infections were identified, which may serve as guidance for antibiotic prescription.

Objective: Suicide is a significant public health issue, particularly among older adults, where the risk is heightened.Early identification of individuals at risk for suicidal ideation is essential for timely interventions, greatly improving prevention efforts. This study aimed to develop a predictive model for suicidal ideation in community-dwelling older adults using psychiatric self-report scales and machine learning classifiers. Methods: A total of 238 older adults were assessed using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7, Perceived Stress Scale-10, and World Health Organization Quality of Life Scale – Abbreviated Version.A nested 5-fold cross-validation procedure repeated 100 times was used for feature selection and model evaluation.Various classifiers—including support vector machines, random forest, logistic regression, linear discriminant analysis, and gradient boosting—were employed. Results: As the number of PHQ-9 items increased from two to six, the area under the curve (AUC) rose from 0.835 to 0.892. When a set of nine features—selected based on feature stability across iterations—was used, the AUC further improved to 0.904. This progression indicates that inclusion of additional informative items enhances classification performance. Conclusion This study demonstrates that psychiatric self-report scales can effectively predict suicidal ideation risk in community-dwelling older adults. By utilizing efficient features, the predictive accuracy of the model can be enhanced, offering valuable insights for developing early identification systems for high-risk groups. These findings suggest that a community-based suicide prevention program could be promoted by implementing a screening system to identify individuals at high risk for suicidal ideation among the elderly.

Objective: This study aimed to develop a machine learning-based classification model to differentiate bipolar disorder from major depressive disorder using self-report scales, including the Mood Disorder Questionnaire (MDQ), Bipolar Spectrum Diagnostic Scale (BSDS), and Anger Coping Scale (ACS). Methods: A total of 122 bipolar and 67 depressive patients participated. Recursive feature elimination with 1,000 iterations was used to identify the most informative features. Machine learning classifiers assessed combinations of MDQ, BSDS, and ACS items for classification performance. Results: The AUC values for MDQ and BSDS were 0.8212 and 0.7934, respectively. Combining MDQ and BSDS increased the AUC to 0.8477, which improved further to 0.8548 when ACS was included. For MDQ, the best performance was achieved when all 13 items were included. In contrast, the combined model of MDQ, BSDS, and ACS showed optimal performance when BSDS items 18 (conflicts with colleagues or police), 19 (alcohol or substance use), and ACS item 15 (beating others) were excluded. Conclusion Integrating anger coping styles with mood symptoms enhanced diagnostic accuracy, particularly when items related to undesirable behaviors were excluded. This machine learning approach shows potential for effectively evaluating bipolarity and underscores the importance of refining self-report scales to optimize diagnostic tools. Future research should incorporate clinical and objective data to enhance classification models.