Background: This study aimed to identify key priorities for the development of guidelines for information and communication technology (ICT)-based patient education tailored to the needs of patients with rheumatic diseases (RDs) in the Republic of Korea, based on expert consensus. Methods: A two-round modified Delphi study was conducted with 20 rheumatology, patient education, and digital health literacy experts. A total of 35 items covering 7 domains and 18 subdomains were evaluated. Each item was evaluated for its level of importance, and the responses were rated on a 4-point Likert scale. Consensus levels were defined as “high” (interquartile range [IQR] ≤ 1, agreement ≥ 80%, content validity ratio [CVR] ≥ 0.7), "Moderate" (IQR ≥ 1, agreement 50–79%, CVR 0.5–0.7), and "Low" (IQR > 1, agreement < 50%, CVR < 0.5). Results: Strong consensus was reached for key priorities for developing guidelines in areas such as health literacy, digital health literacy, medical terminology, user interface, and user experience design for mobile apps. Chatbot use and video (e.g., YouTube) also achieved high consensus, whereas AI-powered platforms such as ChatGPT showed moderate-to-high agreement. Telemedicine was excluded because of insufficient consensus. Conclusion The key priorities identified in this study provide a foundation for the development of ICT-based patient education guidelines for RDs in the Republic of Korea.Future efforts should focus on integrating digital tools into clinical practice to enhance patient engagement and improve clinical outcomes.

Background: This study aimed to identify key priorities for the development of guidelines for information and communication technology (ICT)-based patient education tailored to the needs of patients with rheumatic diseases (RDs) in the Republic of Korea, based on expert consensus. Methods: A two-round modified Delphi study was conducted with 20 rheumatology, patient education, and digital health literacy experts. A total of 35 items covering 7 domains and 18 subdomains were evaluated. Each item was evaluated for its level of importance, and the responses were rated on a 4-point Likert scale. Consensus levels were defined as “high” (interquartile range [IQR] ≤ 1, agreement ≥ 80%, content validity ratio [CVR] ≥ 0.7), "Moderate" (IQR ≥ 1, agreement 50–79%, CVR 0.5–0.7), and "Low" (IQR > 1, agreement < 50%, CVR < 0.5). Results: Strong consensus was reached for key priorities for developing guidelines in areas such as health literacy, digital health literacy, medical terminology, user interface, and user experience design for mobile apps. Chatbot use and video (e.g., YouTube) also achieved high consensus, whereas AI-powered platforms such as ChatGPT showed moderate-to-high agreement. Telemedicine was excluded because of insufficient consensus. Conclusion The key priorities identified in this study provide a foundation for the development of ICT-based patient education guidelines for RDs in the Republic of Korea.Future efforts should focus on integrating digital tools into clinical practice to enhance patient engagement and improve clinical outcomes.

Background: This study aimed to identify key priorities for the development of guidelines for information and communication technology (ICT)-based patient education tailored to the needs of patients with rheumatic diseases (RDs) in the Republic of Korea, based on expert consensus. Methods: A two-round modified Delphi study was conducted with 20 rheumatology, patient education, and digital health literacy experts. A total of 35 items covering 7 domains and 18 subdomains were evaluated. Each item was evaluated for its level of importance, and the responses were rated on a 4-point Likert scale. Consensus levels were defined as “high” (interquartile range [IQR] ≤ 1, agreement ≥ 80%, content validity ratio [CVR] ≥ 0.7), "Moderate" (IQR ≥ 1, agreement 50–79%, CVR 0.5–0.7), and "Low" (IQR > 1, agreement < 50%, CVR < 0.5). Results: Strong consensus was reached for key priorities for developing guidelines in areas such as health literacy, digital health literacy, medical terminology, user interface, and user experience design for mobile apps. Chatbot use and video (e.g., YouTube) also achieved high consensus, whereas AI-powered platforms such as ChatGPT showed moderate-to-high agreement. Telemedicine was excluded because of insufficient consensus. Conclusion The key priorities identified in this study provide a foundation for the development of ICT-based patient education guidelines for RDs in the Republic of Korea.Future efforts should focus on integrating digital tools into clinical practice to enhance patient engagement and improve clinical outcomes.

Background: This study aimed to identify key priorities for the development of guidelines for information and communication technology (ICT)-based patient education tailored to the needs of patients with rheumatic diseases (RDs) in the Republic of Korea, based on expert consensus. Methods: A two-round modified Delphi study was conducted with 20 rheumatology, patient education, and digital health literacy experts. A total of 35 items covering 7 domains and 18 subdomains were evaluated. Each item was evaluated for its level of importance, and the responses were rated on a 4-point Likert scale. Consensus levels were defined as “high” (interquartile range [IQR] ≤ 1, agreement ≥ 80%, content validity ratio [CVR] ≥ 0.7), "Moderate" (IQR ≥ 1, agreement 50–79%, CVR 0.5–0.7), and "Low" (IQR > 1, agreement < 50%, CVR < 0.5). Results: Strong consensus was reached for key priorities for developing guidelines in areas such as health literacy, digital health literacy, medical terminology, user interface, and user experience design for mobile apps. Chatbot use and video (e.g., YouTube) also achieved high consensus, whereas AI-powered platforms such as ChatGPT showed moderate-to-high agreement. Telemedicine was excluded because of insufficient consensus. Conclusion The key priorities identified in this study provide a foundation for the development of ICT-based patient education guidelines for RDs in the Republic of Korea.Future efforts should focus on integrating digital tools into clinical practice to enhance patient engagement and improve clinical outcomes.

Purpose: This study aimed to predict high-risk neuroblastoma among neuroblastic tumors using radiomics features extracted from MRI. Materials and Methods: Pediatric patients (age≤18 years) diagnosed with neuroblastic tumors who had pre-treatment MR images available were enrolled from institution A from January 2010 to November 2019 (training set) and institution B from January 2016 to January 2022 (test set). Segmentation was performed with regions of interest manually drawn along tumor margins on the slice with the widest tumor area by two radiologists. First-order and texture features were extracted and intraclass correlation coefficients (ICCs) were calculated. Multivariate logistic regression (MLR) and random forest (RF) models from 10-fold cross-validation were built using these features. The trained MLR and RF models were tested in an external test set. Results: Thirty-two patients (M:F=23:9, 26.0±26.7 months) were in the training set and 14 patients (M:F=10:4, 33.4±20.4 months) were in the test set with radiomics features (n=930) being extracted. For 10 of the most relevant features selected, intra- and interobserver variability was moderate to excellent (ICCs 0.633–0.911, 0.695–0.985, respectively). The area under the receiver operating characteristic curve (AUC) was 0.94 (sensitivity 67%, specificity 91%, and accuracy 84%) for the MLR model and the average AUC was 0.83 (sensitivity 44%, specificity 87%, and accuracy 75%) for the RF model from 10-fold cross-validation. In the test set, AUCs of the MLR and RF models were 0.94 and 0.91, respectively. Conclusion An MRI-based radiomics model can help predict high-risk neuroblastoma among neuroblastic tumors.

Background/Aims: We aimed to compare the effectiveness and safety of Janus kinase inhibitors (JAKi) vs. biologic disease- modifying antirheumatic drugs (bDMARD) in Korean patients with rheumatoid arthritis (RA) who had an inadequate response to conventional synthetic DMARDs. Methods: A quasi-experimental, multi-center, prospective, non-randomized study was conducted to compare response rates between JAKi and bDMARDs in patients with RA naïve to targeted therapy. An interim analysis was performed to estimate the proportion of patients achieving low disease activity (LDA) based on disease activity score (DAS)–28– erythroid sedimentation rate (ESR) (DAS28-ESR) at 24 weeks after treatment initiation and to evaluate the development of adverse events (AEs). Results: Among 506 patients enrolled from 17 institutions between April 2020 and August 2022, 346 (196 JAKi group and 150 bDMARD group) were included in the analysis. After 24 weeks of treatment, 49.0% of JAKi users and 48.7% of bDMARD users achieved LDA (p = 0.954). DAS28-ESR remission rates were also comparable between JAKi and bDMARD users (30.1% and 31.3%, respectively; p = 0.806). The frequency of AEs reported in the JAKi group was numerically higher than that in the bDMARDs group, but the frequencies of serious and severe AEs were comparable between the groups. Conclusions Our interim findings reveal JAKi have comparable effectiveness and safety to bDMARDs at 24 weeks after treatment initiation.

Objectives: This study investigated the 24-hour ambulatory blood pressure monitoring (ABPM) and Holter parameters for evaluating their prognostic significance of cardiovascular events including stroke in population without atrial fibrillation (AF). Methods: Among 3,199 patients that underwent ABPM, 335 who also underwent Holter recordings were selected in a tertiary hospital. Seventeen patients who had been documented with AF on Holter monitoring or diagnosed with AF were excluded, and finally 318 patients were analyzed. The association between cardiovascular events and ABPM/Holter parameters was analyzed by a logistic regression model, and the risk factors were estimated by a Cox hazard model. Age, sex, and histories of cardiovascular disease were adjusted by a multivariable analysis, and the cut-off values were suggested by a Kaplan-Meyer analysis. Results: During the total follow-up (28.5±1.7 months), 13 (4.1%) stroke, 6 (1.9%) heart failure, and 12 (3.8%) acute coronary syndrome incidences were observed. In the univariate analysis of the ABPM parameters, an increment in the night systolic BP (hazard ratio=1.034, P=0.020) and night diastolic BP (hazard ratio=1.063, P=0.031) significantly elevated the risk of a stroke occurrence. According to the Kaplan-Meyer analysis, there was a significant difference in the stroke incidence between the groups divided by a cut-off value of the night systolic BP of 120 mmHg (P=0.014) and night diastolic BP of 75 mmHg (P=0.023). Conclusion In a population without AF, the nocturnal BP was a significant predictor of a stroke incidence. At this point, the cut-off value of mean 120/75 mmHg in 24 ABPM was advisable.

Objective: Farmers are known to have high prevalence of asthma and chronic obstructive pulmonary disease(COPD). This study aims to investigate the current status of asthma and COPD in domestic and foreign farmers with the ultimate goal of raising awareness of asthma and COPD among farmers and contribute to supporting evidence for the prevention of respiratory diseases in farmers. Methods: The study utilized data from the "Farmer’s Occupational Disease Survey," conducted by the Rural Development Administration, to determine the prevalence of respiratory diseases in domestic farmers.The prevalence of asthma and COPD in overseas farmers was evaluated by researching other foreign studies and articles. Results: The prevalence of asthma and COPD in domestic farmers was less than of foreign farmers’.The prevalence of asthma in domestic farmers was high as upto 8.4% and COPD upto 5.5%. Studies from Europe and America showed prevalence of asthma in farmers high as upto 14.8% and COPD upto 17.1%. Conclusions This study conducted an investigation using the 'Survey on Occupational Diseases and Injuries in Farmers to understand the current status of asthma and COPD in domestic farmers. Due to a lack of relevant domestic research, we examined and compared with the research results on asthma and COPD among overseas farmers. Further research is necessary and preventive measures for respiratory diseases need to be developed.

OBJECTIVES: This study aimed to determine an effective survey method for the accurate calculation of obesity prevalence by comparing the self-reported and measured height, weight, and body mass index (BMI) using the 2018 Korea Community Healthy Survey (CHS) data. METHODS: Raw data from the 2018 CHS were used to analyze the differences, correlation, and agreement between self-reported and measured height, weight, and BMI. RESULTS: The self-reported height was over-reported than the measured height (0.59 cm greater for men and 0.71 cm greater for women), while the self-reported weight was under-reported than the measured weight (0.55 kg less for men and 0.67 kg less for women). Subsequently, the self-reported BMI was under-estimated (0.35 kg/m2 lower for men and 0.49 kg/m2 lower for women) compared with the measured BMI. The kappa statistic and agreement between measured and self-reported values per BMI category (underweight, normal, overweight, and obesity) were 0.82 and 79.6%, respectively. CONCLUSIONS The prevalence of obesity should be calculated using the measured values provided in the CHS in order to promote local health projects based on accurate evidence.

Background: Pierre Robin sequence (PRS) patients have an increased risk of difficult intubation due to anatomical airway abnormalities, and intubation simulation with a three-dimensional (3D) printed airway model before anesthesia may facilitate safe airway management. Case: We describe the case of a 6.5-year-old boy with a history of PRS (a triad of micrognathia, glossoptosis, and airway obstruction), tracheostomy, and subglottic fibrosis who required general anesthesia. Preparation for this potentially difficult intubation included estimation of endotracheal tube size using a 3D printed airway model derived from 3D computed tomography of the airway, which enabled successful endotracheal intubation via video laryngoscopy. Conclusions If general anesthesia is necessary in patients with dysmorphic features such as PRS and there is a history of tracheal pathology, the possibility of difficult intubation should always be considered and simulation of endotracheal intubation using a 3D printed model of the airway can be helpful clinically in such situations.