Although many wearable devices are used to assess sleep, their accuracy remains controversial. This study aimed to investigate the accuracy of the Actiwatch, a research-grade device, and the Fitbit, a consumer-grade device, against sleep diaries to assess sleep patterns. Methods: Twenty participants wore Fitbit and Actiwatch for two weeks and tracked their sleep patterns using sleep diaries. Total sleep time (TST), time-in-bed (TIB), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO) from the two devices and sleep diaries were analyzed using analysis of variance and Bland-Altman analysis. Results: The TIB measured by the sleep log, Fitbit, and Actiwatch were 420.9 minutes, 417.3 minutes, and 567.4 minutes, respectively. Compared to the sleep log, the Fitbit underestimated TST, TIB, and SE, with significant differences observed for TST (p<0.001) and SE (p<0.001), but not for TIB. The Actiwatch overestimated TIB (p<0.001) and TST (p=0.02) and underestimated SE (p<0.001) compared to the sleep log. The difference between the Fitbit and Actiwatch was significant for TST, TIB, and SE (all p<0.001). Conclusions: The Fitbit showed a smaller difference than the Actiwatch when compared with the sleep logs. The Fitbit could be used as a tool to assess sleep patterns in the clinic as well as in daily life.

Purpose: This study aimed to investigate the relationship between body composition and glaucoma by analyzing the associations between anthropometric and ocular parameters. Methods: A total of 494 eyes from 247 patients were reviewed from a general health examination database at a tertiary hospital. Anthropometric parameters were assessed using a multifrequency bioelectrical impedance device. Mean ocular perfusion pressure (MOPP) was calculated based on systolic and diastolic blood pressures and intraocular pressure (IOP). Retinal thickness and other ocular parameters were analyzed for their association with body composition. Results: A total of 221 eyes from 221 patients, including 104 with glaucoma, were enrolled in the final analysis. The prevalence of sarcopenia was significantly higher in patients with glaucomatous damage than in those without (p = 0.025). Higher IOP showed significant associations with lower MOPP (p < 0.001), higher body mass index (BMI; p = 0.001), and higher waist to hip ratio (p = 0.001). Retinal thickness was not significantly associated with body composition parameters, including BMI and appendicular lean mass adjusted with squared height. Higher MOPP was significantly correlated with lower IOP (p < 0.001), higher BMI (p < 0.001), higher waist to hip ratio (p < 0.001), and higher appendicular lean mass divided by squared height (p = 0.009). Conclusions Skeletal muscle mass and BMI were significantly associated with MOPP. Since low MOPP is a known risk factor for glaucoma, its association with skeletal muscle mass may indicate a relationship between systemic muscle health, ocular blood perfusion, and glaucomatous damage. Further large-scale studies are needed to validate these associations between skeletal muscle mass and glaucoma and explore their clinical implications.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

Objective: To establish local diagnostic reference levels (DRLs) for pediatric neck CT based on age, weight, and water-equivalent diameter (WED) across multiple university hospitals in South Korea. Materials and Methods: This retrospective study analyzed pediatric neck CT examinations from nine university hospitals, involving patients aged 0–18 years. Data were categorized by age, weight, and WED, and radiation dose metrics, including volume CT dose index (CTDIvol) and dose length product, were recorded. Data retrieval and analysis were conducted using a commercially available dose-management system (Radimetrics, Bayer Healthcare). Local DRLs were established following the International Commission on Radiological Protection guidelines, using the 75th percentile as the reference value. Results: A total of 1159 CT examinations were analyzed, including 169 scans from Institution 1, 132 from Institution 2, 126 from Institution 3, 129 from Institution 4, 128 from Institution 5, 105 from Institution 6, 162 from Institution 7, 127 from Institution 8, and 81 from Institution 9. Radiation dose metrics increased with age, weight, and WED, showing significant variability both within and across institutions. For patients weighing less than 10 kg, the DRL for CTDIvol was 5.2 mGy. In the 10–19 kg group, the DRL was 5.8 mGy; in the 20–39 kg group, 7.6 mGy; in the 40–59 kg group, 11.0 mGy; and for patients weighing 60 kg or more, 16.2 mGy. DRLs for CTDIvol by age groups were as follows: 5.3 mGy for infants under 1 year, 5.7 mGy for children aged 1–4 years, 7.6 mGy for ages 5–9 years, 11.2 mGy for ages 10–14 years, and 15.6 mGy for patients 15 years or older. Conclusion Local DRLs for pediatric neck CT were established based on age, weight, and WED across nine university hospitals in South Korea.

Purpose: This study aimed to characterize the clinical patterns and severity of brain injury in neonates who survived extracorporeal membrane oxygenation (ECMO) therapy for acute respiratory failure during the neonatal period, to evaluate their short-term neurodevelopmental outcomes, and to identify the factors associated with these outcomes. Methods: We retrospectively reviewed the medical records of neonates who survived ECMO between 2018 and 2024. Based on brain magnetic resonance imaging (MRI) findings, the patients were classified into two groups: no/mild and moderate/severe brain injury. Neurodevelopmental outcomes were assessed at 12–40 months of age using the Bayley Scale of Infant Development II/III and/or the Korean Developmental Screening Test. Results: Among the 19 neonates included in the study, 18 (94.7%) showed varying degrees of brain injury on MRI (mild: 12, moderate: 1, severe: 5). Neonates with moderate/severe brain injury had significantly longer durations of ECMO support and extended durations of mechanical ventilation and were more likely to receive continuous renal replacement therapy than those with no or mild injury. Developmental delay was identified in 36.8% of survivors and was significantly associated with prolonged mechanical ventilation, longer neonatal intensive care unit stays, and a higher incidence of seizures. Conclusion Brain injury is frequently observed on MRI in neonates treated with ECMO. However, its direct association with adverse neurodevelopmental outcomes is not definitive. Since MRI findings alone cannot predict developmental outcomes, clinical and environmental factors should be integrated into prognostic assessments.

Purpose: Congenital hypothyroidism (CH) is a major preventable cause of intellectual disability, particularly in very low birth weight (VLBW) infants, who are at increased risk due to hypothalamic-pituitary-thyroid axis immaturity. Early differentiation between transient CH (TCH) and permanent CH (PCH) is crucial to optimize L-thyroxine (LT4) treatment duration. This study aimed to determine the incidence of PCH among Korean VLBW infants and to identify clinical factors that may aid in distinguishing TCH from PCH. Methods: This retrospective cohort study included VLBW infants diagnosed with CH and treated with LT4 at a single tertiary neonatal intensive care unit between 2011 and 2020. Infants requiring LT4 beyond 3 years were classified as PCH, while those who discontinued earlier were considered TCH. Clinical characteristics, neonatal morbidities, and thyroid-related parameters were compared between the groups. Results: Among 1,292 VLBW infants, 122 (9.4%) were diagnosed with CH. After excluding deaths and those lost to follow-up, 73 infants were included in the final analysis (TCH, n=50; PCH, n=23). The PCH group had a significantly higher mean gestational age and greater LT4 requirements at both 12 and 36 months of age. Major anomalies were more frequently observed in PCH infants, including congenital heart defects. In multivariate analysis, higher gestational age, the presence of major anomalies, screening thyroid-stimulating hormone (TSH) >10 μIU/mL, and higher LT4 dose at 36 months were significantly associated with PCH. Conclusion The incidence of PCH in Korean VLBW infants was relatively higher than that reported in previous studies studies. Screening TSH level and LT4 dose requirements may support individualized follow-up and help distinguish PCH from TCH.

Objectives: To assess the trends and disparities in the utilization of F-18 fluorodeoxyglucose positron emission tomography/ computed tomography (FDG PET/CT) in Korea between 2018 and 2022, with a focus on disease classification, patient demographics, and regional distribution. Methods: This national surveillance retrospective study uses data from the Health Insurance Review and Assessment Service (HIRA) database, which includes all FDG PET/CT examinations conducted in Korea from 2018 to 2022. Disease classifications, cancer types, age groups, gender, and geographic regions were analyzed using descriptive statistics. Utilization rates per 100,000 population were calculated for regional comparisons. Results: FDG PET/CT utilization increased by 25.4%, from 174,885 examinations in 2018 to 219,377 in 2022. Older age groups (60 years and above) accounted for the majority of examinations, with males undergoing more examinations than females. Oncology remained the primary indication, with lung, colorectal, and non-Hodgkin lymphoma leading in examination numbers. The number of examinations performed on patients aged 60 and above increased at a higher rate compared to those under 60. Significant geographic disparities were found, with Seoul reporting the highest utilization rate (1,114.3 examinations per 100,000 population), while Gyeongbuk exhibited much lower rate (26.2 examinations per 100,000 population). Conclusions This study highlights the growing utilization of FDG PET/CT in Korea, particularly among older adults, with significant gender differences in cancer types. The findings also reveal disparities in FDG PET/CT utilization across regions, indicating varying access to advanced imaging technology.

Purpose: This study aimed to leverage Shapley additive explanation (SHAP)-based feature engineering to predict appendix cancer. Traditional models often lack transparency, hindering clinical adoption. We propose a framework that integrates SHAP for feature selection, construction, and weighting to enhance accuracy and clinical relevance. Methods: Data from the Kaggle Appendix Cancer Prediction dataset (260,000 samples, 21 features) were used in this prediction study conducted from January through March 2025, in accordance with TRIPOD-AI guidelines. Preprocessing involved label encoding, SMOTE (synthetic minority over-sampling technique) to address class imbalance, and an 80:20 train-test split. Baseline models (random forest, XGBoost, LightGBM) were compared; LightGBM was selected for its superior performance (accuracy=0.8794). SHAP analysis identified key features and guided 3 engineering steps: selection of the top 15 features, construction of interaction-based features (e.g., chronic severity), and feature weighting based on SHAP values. Performance was evaluated using accuracy, precision, recall, and F1-score. Results: Four LightGBM model configurations were evaluated: baseline (accuracy=0.8794, F1-score=0.8691), feature selection (accuracy=0.8968, F1-score=0.8860), feature construction (accuracy=0.8980, F1-score=0.8872), and feature weighting (accuracy=0.8986, F1-score=0.8877). SHAP-based engineering yielded performance improvements, with feature weighting achieving the highest precision (0.9940). Key features (e.g., red blood cell count and chronic severity) contributed to predictions while maintaining interpretability. Conclusion The SHAP-based framework substantially improved the accuracy and transparency of appendix cancer predictions using LightGBM (F1-score=0.8877). This approach bridges the gap between predictive power and clinical interpretability, offering a scalable model for rare disease prediction. Future validation with real-world data is recommended to ensure generalizability.