A retrospective observational study is one of the most widely used research methods in medicine. However, evidence postulated from a single data source likely contains biases such as selection bias, information bias, and confounding bias. Acquiring enough data from multiple institutions is one of the most effective methods to overcome the limitations.However, acquiring data from multiple institutions from many countries requires enormous effort because of financial, technical, ethical, and legal issues as well as standardization of data structure and semantics. The Observational Health Data Sciences and Informatics (OHDSI) research network standardized 928 million unique records or 12% of the world’s population into a common structure and meaning and established a research network of 453 data partners from 41 countries around the world. OHDSI is a distributed research network wherein researchers do not own or directly share data but only analyzed results. However, sharing evidence without sharing data is difficult to understand. In this review, we will look at the basic principles of OHDSI, common data model, distributed research networks, and some representative studies in the cardiovascular field using the network. This paper also briefly introduces a Korean distributed research network named FeederNet.

Background: Although discharge summaries in patient-friendly language can enhance patient comprehension and satisfaction, they can also increase medical staff workload. Using a large language model, we developed and validated software that generates a patient-friendly discharge summary. Methods: We developed and tested the software using 100 discharge summary documents, 50 for patients with myocardial infarction and 50 for patients treated in the Department of General Surgery. For each document, three new summaries were generated using three different prompting methods (Zero-shot, One-shot, and Few-shot) and graded using a 5-point Likert Scale regarding factuality, comprehensiveness, usability, ease, and fluency. We compared the effects of different prompting methods and assessed the relationship between input length and output quality. Results: The mean overall scores differed across prompting methods (4.19 ± 0.36 in Few-shot, 4.11 ± 0.36 in One-shot, and 3.73 ± 0.44 in Zero-shot; P < 0.001). Post-hoc analysis indicated that the scores were higher with Few-shot and One-shot prompts than in zero-shot prompts, whereas there was no significant difference between Few-shot and One-shot prompts. The overall proportion of outputs that scored ≥ 4 was 77.0% (95% confidence interval: 68.8–85.3%), 70.0% (95% confidence interval [CI], 61.0–79.0%), and 32.0% (95% CI, 22.9–41.1%) with Few-shot, One-shot, and Zero-shot prompts, respectively. The mean factuality score was 4.19 ± 0.60 with Few-shot, 4.20 ± 0.55 with One-shot, and 3.82 ± 0.57 with Zero-shot prompts. Input length and the overall score showed negative correlations in the Zero-shot (r = −0.437, P < 0.001) and One-shot (r = −0.327, P < 0.001) tests but not in the Few-shot (r = −0.050, P = 0.625) tests. Conclusion Large-language models utilizing Few-shot prompts generally produce acceptable discharge summaries without significant misinformation. Our research highlights the potential of such models in creating patient-friendly discharge summaries for Korean patients to support patient-centered care.

BACKGROUND/AIMS: Olmesartan, a widely used angiotensin II receptor blocker (ARB), has been linked to sprue-like enteropathy. No cases of olmesartan-associated enteropathy have been reported in Northeast Asia. We investigated the associations between olmesartan and other ARBs and the incidence of enteropathy in Korea. METHODS: Our retrospective cohort study used data from the Korean National Health Insurance Service to identify 108,559 patients (58,186 females) who were initiated on angiotensin converting enzyme inhibitors (ACEis), olmesartan, or other ARBs between January 2005 and December 2012. The incidences of enteropathy were compared among drug groups. Changes in body weight were compared after propensity score matching of patients in the ACEis and olmesartan groups. RESULTS: Among 108,559 patients, 31 patients were diagnosed with enteropathy. The incidences were 0.73, 0.24, and 0.37 per 1,000 persons, in the ACEis, olmesartan, and other ARBs groups, respectively. Adjusted rate ratios for enteropathy were: olmesartan, 0.33 (95% confidential interval [CI], 0.10 to 1.09; p = 0.070) and other ARBs, 0.34 (95% CI, 0.14 to 0.83; p = 0.017) compared to the ACEis group after adjustment for age, sex, income level, and various comorbidities. The post hoc analysis with matched cohorts revealed that the proportion of patients with significant weight loss did not differ between the ACEis and olmesartan groups. CONCLUSIONS: Olmesartan was not associated with intestinal malabsorption or significant body weight loss in the general Korean population. Additional large-scale prospective studies of the relationship between olmesartan and the incidence of enteropathy in the Asian population are needed.
Angiotensin Receptor Antagonists ; Angiotensin-Converting Enzyme Inhibitors ; Asia ; Asian Continental Ancestry Group ; Body Weight ; Cohort Studies* ; Comorbidity ; Drug-Related Side Effects and Adverse Reactions ; Humans ; Incidence ; Insurance Claim Review ; Intestinal Diseases ; Korea ; National Health Programs ; Propensity Score ; Prospective Studies ; Receptors, Angiotensin ; Retrospective Studies ; Weight Loss

Purpose: Digital Imaging and Communications in Medicine (DICOM), a standard file format for medical imaging data, contains metadata describing each file. However, metadata are often incomplete, and there is no standardized format for recording metadata, leading to inefficiency during the metadata-based data retrieval process. Here, we propose a novel standardization method for DICOM metadata termed the Radiology Common Data Model (R-CDM). Materials and Methods: R-CDM was designed to be compatible with Health Level Seven International (HL7)/Fast Healthcare Interoperability Resources (FHIR) and linked with the Observational Medical Outcomes Partnership (OMOP)-CDM to achieve a seamless link between clinical data and medical imaging data. The terminology system was standardized using the RadLex playbook, a comprehensive lexicon of radiology. As a proof of concept, the R-CDM conversion process was conducted with 41.7 TB of data from the Ajou University Hospital. The R-CDM database visualizer was developed to visualize the main characteristics of the R-CDM database. Results: Information from 2801360 cases and 87203226 DICOM files was organized into two tables constituting the R-CDM. Information on imaging device and image resolution was recorded with more than 99.9% accuracy. Furthermore, OMOP-CDM and RCDM were linked to efficiently extract specific types of images from specific patient cohorts. Conclusion R-CDM standardizes the structure and terminology for recording medical imaging data to eliminate incomplete and unstandardized information. Successful standardization was achieved by the extract, transform, and load process and image classifier. We hope that the R-CDM will contribute to deep learning research in the medical imaging field by enabling the securement of large-scale medical imaging data from multinational institutions.

While advances in cancer treatment have led to improved survival rates, cancer survivors are at a significant risk of developing atherosclerotic cardiovascular disease (ASCVD).This review examines the risk, diagnosis, and prevention of ASCVD in this population.Cancer survivors, especially those diagnosed with certain types, face a significantly higher risk of developing ASCVD than the general population. We introduce the “triad model” to explain this increased risk of ASCVD among cancer patients. This model includes three interconnected components: common catalysts, cancer influence, and treatment impact.The factors contributing to this model are the shared risk factors between cancer and ASCVD, such as smoking, obesity, and systemic inflammation; the direct effects of cancer on cardiovascular health through chronic systemic inflammation and endothelial damage;and the significant effects of anticancer treatments, including chemotherapy and radiation, which can worsen cardiovascular complications and hasten the progression of ASCVD.Furthermore, cancer survivors are at a higher risk of developing and dying from ASCVD, highlighting the necessity for tailored guidelines and strategies for ASCVD prevention and management in this population. The review explores the utility of diagnostic tools, such as coronary artery calcium scoring, in predicting and managing ASCVD risk. It also emphasizes the importance of prevention strategies that include regular cardiovascular monitoring and lifestyle modifications. Finally, the relationship between cancer survival and cardiovascular health highlights the importance of integrated and comprehensive care approaches.Continued research, the development of prediction models, and specific preventative strategies are essential to improve cancer survivors’ overall health outcomes.

While advances in cancer treatment have led to improved survival rates, cancer survivors are at a significant risk of developing atherosclerotic cardiovascular disease (ASCVD).This review examines the risk, diagnosis, and prevention of ASCVD in this population.Cancer survivors, especially those diagnosed with certain types, face a significantly higher risk of developing ASCVD than the general population. We introduce the “triad model” to explain this increased risk of ASCVD among cancer patients. This model includes three interconnected components: common catalysts, cancer influence, and treatment impact.The factors contributing to this model are the shared risk factors between cancer and ASCVD, such as smoking, obesity, and systemic inflammation; the direct effects of cancer on cardiovascular health through chronic systemic inflammation and endothelial damage;and the significant effects of anticancer treatments, including chemotherapy and radiation, which can worsen cardiovascular complications and hasten the progression of ASCVD.Furthermore, cancer survivors are at a higher risk of developing and dying from ASCVD, highlighting the necessity for tailored guidelines and strategies for ASCVD prevention and management in this population. The review explores the utility of diagnostic tools, such as coronary artery calcium scoring, in predicting and managing ASCVD risk. It also emphasizes the importance of prevention strategies that include regular cardiovascular monitoring and lifestyle modifications. Finally, the relationship between cancer survival and cardiovascular health highlights the importance of integrated and comprehensive care approaches.Continued research, the development of prediction models, and specific preventative strategies are essential to improve cancer survivors’ overall health outcomes.

While advances in cancer treatment have led to improved survival rates, cancer survivors are at a significant risk of developing atherosclerotic cardiovascular disease (ASCVD).This review examines the risk, diagnosis, and prevention of ASCVD in this population.Cancer survivors, especially those diagnosed with certain types, face a significantly higher risk of developing ASCVD than the general population. We introduce the “triad model” to explain this increased risk of ASCVD among cancer patients. This model includes three interconnected components: common catalysts, cancer influence, and treatment impact.The factors contributing to this model are the shared risk factors between cancer and ASCVD, such as smoking, obesity, and systemic inflammation; the direct effects of cancer on cardiovascular health through chronic systemic inflammation and endothelial damage;and the significant effects of anticancer treatments, including chemotherapy and radiation, which can worsen cardiovascular complications and hasten the progression of ASCVD.Furthermore, cancer survivors are at a higher risk of developing and dying from ASCVD, highlighting the necessity for tailored guidelines and strategies for ASCVD prevention and management in this population. The review explores the utility of diagnostic tools, such as coronary artery calcium scoring, in predicting and managing ASCVD risk. It also emphasizes the importance of prevention strategies that include regular cardiovascular monitoring and lifestyle modifications. Finally, the relationship between cancer survival and cardiovascular health highlights the importance of integrated and comprehensive care approaches.Continued research, the development of prediction models, and specific preventative strategies are essential to improve cancer survivors’ overall health outcomes.

While advances in cancer treatment have led to improved survival rates, cancer survivors are at a significant risk of developing atherosclerotic cardiovascular disease (ASCVD).This review examines the risk, diagnosis, and prevention of ASCVD in this population.Cancer survivors, especially those diagnosed with certain types, face a significantly higher risk of developing ASCVD than the general population. We introduce the “triad model” to explain this increased risk of ASCVD among cancer patients. This model includes three interconnected components: common catalysts, cancer influence, and treatment impact.The factors contributing to this model are the shared risk factors between cancer and ASCVD, such as smoking, obesity, and systemic inflammation; the direct effects of cancer on cardiovascular health through chronic systemic inflammation and endothelial damage;and the significant effects of anticancer treatments, including chemotherapy and radiation, which can worsen cardiovascular complications and hasten the progression of ASCVD.Furthermore, cancer survivors are at a higher risk of developing and dying from ASCVD, highlighting the necessity for tailored guidelines and strategies for ASCVD prevention and management in this population. The review explores the utility of diagnostic tools, such as coronary artery calcium scoring, in predicting and managing ASCVD risk. It also emphasizes the importance of prevention strategies that include regular cardiovascular monitoring and lifestyle modifications. Finally, the relationship between cancer survival and cardiovascular health highlights the importance of integrated and comprehensive care approaches.Continued research, the development of prediction models, and specific preventative strategies are essential to improve cancer survivors’ overall health outcomes.

Objective: This study aimed to investigate the impact of coronavirus disease-2019 (COVID-19) on suicide attempts and suicide deaths in South Korea, focusing on age and sex differences. Methods: We analyzed the monthly number of suicide attempts and suicide deaths during pre-pandemic (January 2016–February 2020) and pandemic (March–December 2020) periods using nationally representative databases. We conducted an interrupted time series analysis and calculated the relative risk (RR) with a 95% confidence interval (CI), categorizing subjects into adolescents (<18), young adults (18–29), middle-aged (30–59), and older adults (≥60). Results: During the pandemic, the number of suicide attempts abruptly declined in adolescents (RR [95% CI] level change: 0.58 [0.45–0.75]) and older adults (RR [95% CI] level change: 0.74 [0.66–0.84]). In older males, there was a significant rebound in the suicide attempt trend (RR [95% CI] slope change: 1.03 [1.01–1.05]). The number of suicide deaths did not change among age/sex strata significantly except for older males. There was a brief decline in suicide deaths in older males, while the trend showed a following increase with marginal significance (RR [95% CI] level change: 0.76 [0.66–0.88], slope change: 1.02 [1.00–1.04]). Conclusion This study suggests the heterogeneous impact of the COVID-19 pandemic on suicide attempts and suicide deaths across age and sex strata in South Korea. These findings highlight the need for more targeted mental health interventions, given the observed trends in suicide attempts and suicide deaths during the pandemic.

Objectives: We incorporated the Korean Electronic Data Interchange (EDI) vocabulary into Observational Medical Outcomes Partnership (OMOP) vocabulary using a semi-automated process. The goal of this study was to improve the Korean EDI as a standard medical ontology in Korea. Methods: We incorporated the EDI vocabulary into OMOP vocabulary through four main steps. First, we improved the current classification of EDI domains and separated medical services into procedures and measurements. Second, each EDI concept was assigned a unique identifier and validity dates. Third, we built a vertical hierarchy between EDI concepts, fully describing child concepts through relationships and attributes and linking them to parent terms. Finally, we added an English definition for each EDI concept. We translated the Korean definitions of EDI concepts using Google.Cloud.Translation.V3, using a client library and manual translation. We evaluated the EDI using 11 auditing criteria for controlled vocabularies. Results: We incorporated 313,431 concepts from the EDI to the OMOP Standardized Vocabularies. For 10 of the 11 auditing criteria, EDI showed a better quality index within the OMOP vocabulary than in the original EDI vocabulary. Conclusions The incorporation of the EDI vocabulary into the OMOP Standardized Vocabularies allows better standardization to facilitate network research. Our research provides a promising model for mapping Korean medical information into a global standard terminology system, although a comprehensive mapping of official vocabulary remains to be done in the future.