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: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Pneumocystis jirovecii pneumonia (PJP) is a life-threatening infection commonly observed in immunocompromised patients, necessitating prompt diagnosis and treatment. This review evaluates the diagnostic performance of various tests used for PJP diagnosis through a comprehensive literature review. Additionally, we propose a diagnostic algorithm tailored to non-human immunodeficiency virus immunocompromised patients, considering the specific characteristics of current medical resources in Korea.

Background: The relationship between circulating lipid levels and the risk for heart failure (HF) is controversial. We aimed to examine this association, and whether it is modified by the duration of diabetes or treatment regimens in people with type 2 diabetes mellitus. Methods: Individuals (n=2,439,978) who underwent health examinations in 2015 to 2016 were identified from the Korean National Health Information Database. Subjects were categorized according to the duration of diabetes (new-onset, <5, 5–10, or ≥10 years) and number of antidiabetic medications. Incident HF was defined according to the International Classification of Diseases, 10th Revision (ICD-10) code I50 as the primary diagnosis during hospitalization. The risk for HF was estimated using multivariate Cox proportional hazard analysis. Results: During a median follow-up of 4.0 years, 151,624 cases of HF occurred. An inverse association between low-density lipoprotein cholesterol (LDL-C) levels and incident HF was observed in the new-onset diabetes group, with an approximately 25% lower risk in those with LDL-C levels of 100–129, 130–159, and ≥160 mg/dL, compared to those with levels <70 mg/dL. However, J-shaped associations were noted in the long-standing diabetes group, with a 16% higher risk in those with LDL-C level ≥160 mg/dL, compared to those with levels <70 mg/dL. Similar patterns were observed in the relationship between total cholesterol or non-high-density lipoprotein cholesterol and the risk for HF, and when subjects were grouped according to the number of antidiabetic medications instead of diabetes duration. Conclusion Different associations between lipid levels and the risk for HF were noted according to disease progression status among individuals with diabetes.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

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: The relationship between circulating lipid levels and the risk for heart failure (HF) is controversial. We aimed to examine this association, and whether it is modified by the duration of diabetes or treatment regimens in people with type 2 diabetes mellitus. Methods: Individuals (n=2,439,978) who underwent health examinations in 2015 to 2016 were identified from the Korean National Health Information Database. Subjects were categorized according to the duration of diabetes (new-onset, <5, 5–10, or ≥10 years) and number of antidiabetic medications. Incident HF was defined according to the International Classification of Diseases, 10th Revision (ICD-10) code I50 as the primary diagnosis during hospitalization. The risk for HF was estimated using multivariate Cox proportional hazard analysis. Results: During a median follow-up of 4.0 years, 151,624 cases of HF occurred. An inverse association between low-density lipoprotein cholesterol (LDL-C) levels and incident HF was observed in the new-onset diabetes group, with an approximately 25% lower risk in those with LDL-C levels of 100–129, 130–159, and ≥160 mg/dL, compared to those with levels <70 mg/dL. However, J-shaped associations were noted in the long-standing diabetes group, with a 16% higher risk in those with LDL-C level ≥160 mg/dL, compared to those with levels <70 mg/dL. Similar patterns were observed in the relationship between total cholesterol or non-high-density lipoprotein cholesterol and the risk for HF, and when subjects were grouped according to the number of antidiabetic medications instead of diabetes duration. Conclusion Different associations between lipid levels and the risk for HF were noted according to disease progression status among individuals with diabetes.

Background: The relationship between circulating lipid levels and the risk for heart failure (HF) is controversial. We aimed to examine this association, and whether it is modified by the duration of diabetes or treatment regimens in people with type 2 diabetes mellitus. Methods: Individuals (n=2,439,978) who underwent health examinations in 2015 to 2016 were identified from the Korean National Health Information Database. Subjects were categorized according to the duration of diabetes (new-onset, <5, 5–10, or ≥10 years) and number of antidiabetic medications. Incident HF was defined according to the International Classification of Diseases, 10th Revision (ICD-10) code I50 as the primary diagnosis during hospitalization. The risk for HF was estimated using multivariate Cox proportional hazard analysis. Results: During a median follow-up of 4.0 years, 151,624 cases of HF occurred. An inverse association between low-density lipoprotein cholesterol (LDL-C) levels and incident HF was observed in the new-onset diabetes group, with an approximately 25% lower risk in those with LDL-C levels of 100–129, 130–159, and ≥160 mg/dL, compared to those with levels <70 mg/dL. However, J-shaped associations were noted in the long-standing diabetes group, with a 16% higher risk in those with LDL-C level ≥160 mg/dL, compared to those with levels <70 mg/dL. Similar patterns were observed in the relationship between total cholesterol or non-high-density lipoprotein cholesterol and the risk for HF, and when subjects were grouped according to the number of antidiabetic medications instead of diabetes duration. Conclusion Different associations between lipid levels and the risk for HF were noted according to disease progression status among individuals with diabetes.

Pneumocystis jirovecii pneumonia (PJP) is a life-threatening infection commonly observed in immunocompromised patients, necessitating prompt diagnosis and treatment. This review evaluates the diagnostic performance of various tests used for PJP diagnosis through a comprehensive literature review. Additionally, we propose a diagnostic algorithm tailored to non-human immunodeficiency virus immunocompromised patients, considering the specific characteristics of current medical resources in Korea.