Yonsei medical journal
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Yonsei medical journal · Feb 2019
Machine Learning for the Prediction of New-Onset Diabetes Mellitus during 5-Year Follow-up in Non-Diabetic Patients with Cardiovascular Risks.
Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, these predictive models have several limitations, such as user convenience and reproducibility. The purpose of this study was to develop a T2DM predictive model using electronic medical records (EMRs) and machine learning and to compare the performance of this model with traditional statistical methods. ⋯ We successfully developed and verified a T2DM prediction system using machine learning and an EMR database, and it predicted the 5-year occurrence of T2DM similarly to with a traditional prediction model. In further study, it is necessary to apply and verify the prediction model through clinical research.
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Yonsei medical journal · Feb 2019
Signal Detection for Cardiovascular Adverse Events of DPP-4 Inhibitors Using the Korea Adverse Event Reporting System Database, 2008-2016.
Cardiovascular adverse events (AEs) after use of dipeptidyl peptidase-4 (DPP4) inhibitors have been reported and suspected since the launch of DPP-4 inhibitors in 2006. However, few studies have investigated the association between cardiovascular AEs and DPP-4 inhibitors. The objective of this study is to detect the signals of cardiovascular AEs after use of DPP-4 inhibitors by analyzing the Korea Institute of Drug Safety & Risk Management-Korea Adverse Event Reporting System Database (KIDS-KD). ⋯ Analysis of spontaneous ADR reports data on the use of DPP-4 inhibitors could not showed the association between DPP-4 inhibitors and cardiovascular AEs, due to a small number of cardiovascular AEs reports.
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Yonsei medical journal · Feb 2019
Analysis of Individual Case Safety Reports of Severe Cutaneous Adverse Reactions in Korea.
Despite morbidities and fatalities, nationwide epidemiologic data for severe cutaneous adverse reactions (SCARs), including Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), and drug reaction with eosinophilia and systemic symptoms (DRESS), are not widely available. We aimed to investigate SCAR epidemiology over the last two decades in Korea. ⋯ The number of SCAR ICSRs has increased rapidly with recent active pharmacovigilance programs in Korea. Allopurinol and antiepileptics are the most common individual and categorical causative agents, respectively.