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.

Cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS) is a neurodegenerative disorder caused by a biallelic expansion of pentanucleotide repeats in the RFC1 gene. Previous studies have reported up to 22% of patients with late-onset ataxia harbor this pathogenic repeat expansion. Despite its relatively high prevalence, CANVAS is often underdiagnosed because the disease is not well recognized and genetic testing is not performed in clinical practice. Here, we present a patient with characteristic clinical features, confirmed by genetic testing.

Purpose: This study examined the status of arthroscopic shoulder surgery in ambulatory settings by analyzing a single institutional database. Materials and Methods: Three hundred and eight arthroscopic shoulder surgeries performed between June 2022 and March 2023 were reviewed retrospectively. Propensity score matching (1-to-2) was performed between the day surgery group and the inpatient group according to sex, age, tear size, and interscalene nerve block (ISNB). Finally, 59 patients in the day surgery group and 118 patients in the inpatient group were matched. The indications of the day surgery were pre-determined according to the American Society of Anesthesiologists classification I or II, and the patient's social, medical, and surgical factors were thoroughly analyzed to define the target group of the day surgery. Complications related to voiding difficulty were prevented by classifying the patients using the International Prostate Symptom Score (IPSS) before surgery, and preventive medications were prescribed in the higher-risk patients with an IPSS of more than 7. To reduce postoperative pain, ISNB and patient-controlled analgesia (PCA) were applied to all patients during the study period, while day surgery patients received an additional bolus injection (5 cc of 0.375% ropivacaine+5 cc of normal saline) before discharge instead of continuous ISNB PCA. This study compared the postoperative pain assessments at discharge and on postoperative days 1, 2, and 14, as well as the total volume of saline irrigation, surgical time, and complications between the day surgery and inpatient groups. Results: The visual analogue scale for pain (pVAS) at the time of surgery were comparable in the day surgery group (4.1±1.5) and inpatient surgery group (4.1±1.1), with no significant difference between them (p=0.35). Similarly, the postoperative pVAS at 1, 2, and 14 days postoperatively was similar in the two groups (all p>0.05). The surgical-related factors, such as the total volume of saline irrigation and surgical time, were similar in the two groups. Furthermore, there was no significant difference in postoperative complications between the two groups (all p>0.05). Conclusion These results show that arthroscopic shoulder surgery in ambulatory settings is a safe alternative to inpatient surgery.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

Background/Aims: Multiple myeloma (MM) predominantly affects elderly individuals, but studies on older patients with MM are limited. The clinical characteristics and survival outcomes of patients with MM aged 80 years or over were retrospectively analyzed. Methods: This retrospective multicenter study was conducted to investigate the clinical characteristics, treatment patterns, and survival outcomes of patients aged 80 years or over who were newly diagnosed with MM at five academic hospitals in Daegu, Korea, between 2010 and 2019. Results: A total of 127 patients with a median age of 83 years (range, 80–93 yr) were enrolled: 52 (40.9%) with Eastern Cooperative Oncology Group Performance Status (ECOG PS) > 2, 84 (66.1%) with International Staging System (ISS) stage III disease, and 93 (73.2%) with a Charlson comorbidity index (CCI) > 4. Chemotherapy was administered to 86 patients (67.7%). The median overall survival was 9.3 months. Overall survival was significantly associated with ECOG PS > 2 (HR 2.26, 95% CI 1.43–3.59), ISS stage III (HR 1.99, 95% CI 1.18–3.34), and chemotherapy (HR 0.34, 95% CI 0.21–0.55). There was no statistically significant difference in event-free survival according to the type of anti-myeloma chemotherapy administered. The early mortality (EM) rate was 28.3%. Conclusions Even in patients with MM aged 80 years or over, chemotherapy can result in better survival outcomes than supportive care. Patients aged ≥ 80 years should not be excluded from chemotherapy based on age alone. However, reducing EM in elderly patients with newly diagnosed MM remains challenging.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

Background: s/Aims: Hepatocellular carcinoma (HCC) is the sixth most common cancer and second leading cause of cancer-related deaths in South Korea. This study evaluated the characteristics of Korean patients newly diagnosed with HCC in 2016-2018. Methods: Data from the Korean Primary Liver Cancer Registry (KPLCR), a representative database of patients newly diagnosed with HCC in South Korea, were analyzed. This study investigated 4,462 patients with HCC registered in the KPLCR in 2016-2018. Results: The median patient age was 63 years (interquartile range, 55-72). 79.7% of patients were male. Hepatitis B infection was the most common underlying liver disease (54.5%). The Barcelona Clinic Liver Cancer (BCLC) staging system classified patients as follows: stage 0 (14.9%), A (28.8%), B (7.5%), C (39.0%), and D (9.8%). The median overall survival was 3.72 years (95% confidence interval, 3.47-4.14), with 1-, 3-, and 5-year overall survival rates of 71.3%, 54.1%, and 44.3%, respectively. In 2016-2018, there was a significant shift toward BCLC stage 0-A and Child-Turcotte-Pugh liver function class A (P<0.05), although survival rates did not differ by diagnosis year. In the treatment group (n=4,389), the most common initial treatments were transarterial therapy (31.7%), surgical resection (24.9%), best supportive care (18.9%), and local ablation therapy (10.5%). Conclusions Between 2016 and 2018, HCC tended to be diagnosed at earlier stages, with better liver function in later years. However, since approximately half of the patients remained diagnosed at an advanced stage, more rigorous and optimized HCC screening strategies should be implemented.