This review provides a comprehensive framework for the diagnostic approach and management of Huntington’s disease (HD) tailored to the Korean population. Key topics include genetic counseling, predictive testing, and reproductive options like preimplantation genetic testing. Strategies for assessing disease progression in premanifest HD through laboratory investigations, biofluid, and imaging biomarkers are highlighted. Special considerations for juvenile and late-onset HD, along with associated comorbidities like diabetes mellitus, hypertension, and cardiovascular abnormalities, are discussed. The guide emphasizes personalized symptom management, including pharmacotherapy, physical therapy, and nutritional support, while exploring emerging disease-modifying treatments. A multidisciplinary care model is advocated to improve outcomes for HD patients and caregivers in Korea.

Objective: Using a nationally representative cohort of medical claims data in Korea, this study aimed to analyze the association between the use of various anti-rheumatic agents and the risk of acute myocardial infarction (AMI) in patients with rheumatoid arthritis (RA). Methods: This nested case-control study used the Korean Health Insurance Review and Assessment data of 35,133 patients newly diagnosed with RA between 2011 and 2020. Incident AMI patients were identified and matched at a 1:4 ratio with randomly selected controls. The usage of anti-rheumatic agents was measured from the date of RA diagnosis to the index date and stratified based on exposure time and duration. The risk of AMI associated with each anti-rheumatic agent was estimated using conditional logistic regression, adjusted for comorbidities and concomitant drug use. Results: Of the 35,133 patients with RA, 484 were diagnosed with AMI. In total, 484 AMI patients and 1,924 controls with newly diagnosed RA were included in the analysis. Current exposure and long-term exposure to glucocorticoids (adjusted odds ratio [aOR]: 2.301, 95% confidence interval [CI]: 1.741~3.041; aOR: 1.792, 95% CI: 1.378~2.330) and leflunomide (aOR: 1.525, 95% CI: 1.196~1.944; aOR: 1.740, 95% CI: 1.372~2.207) were associated with an increased risk of AMI. Conclusion The study demonstrates a significant association between the current and long-term use of glucocorticoids and leflunomide and an increased risk of AMI in patients with RA. These findings underscore the importance of careful consideration of cardiovascular risks when selecting anti-rheumatic agents for RA treatment.

We evaluated the effectiveness of the predictive low-glucose suspend (PLGS) algorithm in the DIA:CONN G8. Forty people with type 1 diabetes mellitus (T1DM) who used a DIA:CONN G8 for at least 2 months with prior experience using pumps without and with PLGS were retrospectively analyzed. The objective was to assess the changes in time spent in hypoglycemia (percent of time below range [%TBR]) before and after using PLGS. The mean age, sensor glucose levels, glucose threshold for suspension, and suspension time were 31.1±22.8 years, 159.7±23.2 mg/dL, 81.1±9.1 mg/dL, and 111.9±79.8 min/day, respectively. Overnight %TBR <70 mg/dL was significantly reduced after using the algorithm (differences=0.3%, from 1.4%±1.5% to 1.1%±1.2%, P=0.045). The glycemia risk index (GRI) improved significantly by 4.2 (from 38.8±20.9 to 34.6±19.0, P=0.002). Using the PLGS did not result in a change in the hyperglycemia metric (all P>0.05). Our findings support the PLGS in DIA:CONN G8 as an effective algorithm to improve night-time hypoglycemia and GRI in people with T1DM.

Purpose: This study aimed to develop a Korean version of the frailty model that reflects a holistic perspective. There were three phases of the study: a literature review, a two-round Delphi study, and a public hearing. Methods: The model was developed based on the middle-range theory generation approach proposed by Roy. A literature search was conducted, and a review of 36 studies on frailty involving Koreans led to the development of an initial frailty model. A two-round Delphi study was then conducted with nine experts to evaluate the appropriateness of the model. The revised model was presented at a public hearing to achieve consensus. Based on feedback indicating the need for improved visualization, a finalized diagrammatic model was developed. Results: The final frailty model comprised four domains, seven subdomains, and 30 items. It included specific items reflecting the distinctive characteristics of Korean culture, such as relationships with adult children (filial piety), nutritional status (consumption of red meat), and type of residential building. Conclusion The final frailty model provides a comprehensive perspective on the factors contributing to frailty, their interactions, and the potential interventions that healthcare providers can implement to prevent frailty.

We evaluated the effectiveness of the predictive low-glucose suspend (PLGS) algorithm in the DIA:CONN G8. Forty people with type 1 diabetes mellitus (T1DM) who used a DIA:CONN G8 for at least 2 months with prior experience using pumps without and with PLGS were retrospectively analyzed. The objective was to assess the changes in time spent in hypoglycemia (percent of time below range [%TBR]) before and after using PLGS. The mean age, sensor glucose levels, glucose threshold for suspension, and suspension time were 31.1±22.8 years, 159.7±23.2 mg/dL, 81.1±9.1 mg/dL, and 111.9±79.8 min/day, respectively. Overnight %TBR <70 mg/dL was significantly reduced after using the algorithm (differences=0.3%, from 1.4%±1.5% to 1.1%±1.2%, P=0.045). The glycemia risk index (GRI) improved significantly by 4.2 (from 38.8±20.9 to 34.6±19.0, P=0.002). Using the PLGS did not result in a change in the hyperglycemia metric (all P>0.05). Our findings support the PLGS in DIA:CONN G8 as an effective algorithm to improve night-time hypoglycemia and GRI in people with T1DM.

We evaluated the effectiveness of the predictive low-glucose suspend (PLGS) algorithm in the DIA:CONN G8. Forty people with type 1 diabetes mellitus (T1DM) who used a DIA:CONN G8 for at least 2 months with prior experience using pumps without and with PLGS were retrospectively analyzed. The objective was to assess the changes in time spent in hypoglycemia (percent of time below range [%TBR]) before and after using PLGS. The mean age, sensor glucose levels, glucose threshold for suspension, and suspension time were 31.1±22.8 years, 159.7±23.2 mg/dL, 81.1±9.1 mg/dL, and 111.9±79.8 min/day, respectively. Overnight %TBR <70 mg/dL was significantly reduced after using the algorithm (differences=0.3%, from 1.4%±1.5% to 1.1%±1.2%, P=0.045). The glycemia risk index (GRI) improved significantly by 4.2 (from 38.8±20.9 to 34.6±19.0, P=0.002). Using the PLGS did not result in a change in the hyperglycemia metric (all P>0.05). Our findings support the PLGS in DIA:CONN G8 as an effective algorithm to improve night-time hypoglycemia and GRI in people with T1DM.

Purpose: This study aimed to develop a Korean version of the frailty model that reflects a holistic perspective. There were three phases of the study: a literature review, a two-round Delphi study, and a public hearing. Methods: The model was developed based on the middle-range theory generation approach proposed by Roy. A literature search was conducted, and a review of 36 studies on frailty involving Koreans led to the development of an initial frailty model. A two-round Delphi study was then conducted with nine experts to evaluate the appropriateness of the model. The revised model was presented at a public hearing to achieve consensus. Based on feedback indicating the need for improved visualization, a finalized diagrammatic model was developed. Results: The final frailty model comprised four domains, seven subdomains, and 30 items. It included specific items reflecting the distinctive characteristics of Korean culture, such as relationships with adult children (filial piety), nutritional status (consumption of red meat), and type of residential building. Conclusion The final frailty model provides a comprehensive perspective on the factors contributing to frailty, their interactions, and the potential interventions that healthcare providers can implement to prevent frailty.

This review provides a comprehensive framework for the diagnostic approach and management of Huntington’s disease (HD) tailored to the Korean population. Key topics include genetic counseling, predictive testing, and reproductive options like preimplantation genetic testing. Strategies for assessing disease progression in premanifest HD through laboratory investigations, biofluid, and imaging biomarkers are highlighted. Special considerations for juvenile and late-onset HD, along with associated comorbidities like diabetes mellitus, hypertension, and cardiovascular abnormalities, are discussed. The guide emphasizes personalized symptom management, including pharmacotherapy, physical therapy, and nutritional support, while exploring emerging disease-modifying treatments. A multidisciplinary care model is advocated to improve outcomes for HD patients and caregivers in Korea.

Objective: Using a nationally representative cohort of medical claims data in Korea, this study aimed to analyze the association between the use of various anti-rheumatic agents and the risk of acute myocardial infarction (AMI) in patients with rheumatoid arthritis (RA). Methods: This nested case-control study used the Korean Health Insurance Review and Assessment data of 35,133 patients newly diagnosed with RA between 2011 and 2020. Incident AMI patients were identified and matched at a 1:4 ratio with randomly selected controls. The usage of anti-rheumatic agents was measured from the date of RA diagnosis to the index date and stratified based on exposure time and duration. The risk of AMI associated with each anti-rheumatic agent was estimated using conditional logistic regression, adjusted for comorbidities and concomitant drug use. Results: Of the 35,133 patients with RA, 484 were diagnosed with AMI. In total, 484 AMI patients and 1,924 controls with newly diagnosed RA were included in the analysis. Current exposure and long-term exposure to glucocorticoids (adjusted odds ratio [aOR]: 2.301, 95% confidence interval [CI]: 1.741~3.041; aOR: 1.792, 95% CI: 1.378~2.330) and leflunomide (aOR: 1.525, 95% CI: 1.196~1.944; aOR: 1.740, 95% CI: 1.372~2.207) were associated with an increased risk of AMI. Conclusion The study demonstrates a significant association between the current and long-term use of glucocorticoids and leflunomide and an increased risk of AMI in patients with RA. These findings underscore the importance of careful consideration of cardiovascular risks when selecting anti-rheumatic agents for RA treatment.