- COVID-19
- Effects of a DPP-4 Inhibitor and RAS Blockade on Clinical Outcomes of Patients with Diabetes and COVID-19
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Sang Youl Rhee, Jeongwoo Lee, Hyewon Nam, Dae-Sung Kyoung, Dong Wook Shin, Dae Jung Kim
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Diabetes Metab J. 2021;45(2):251-259. Published online March 5, 2021
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DOI: https://doi.org/10.4093/dmj.2020.0206
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- Background
Dipeptidyl peptidase-4 inhibitor (DPP-4i) and renin-angiotensin system (RAS) blockade are reported to affect the clinical course of coronavirus disease 2019 (COVID-19) in patients with diabetes mellitus (DM).
Methods As of May 2020, analysis was conducted on all subjects who could confirm their history of claims related to COVID-19 in the National Health Insurance Review and Assessment Service (HIRA) database in Korea. Using this dataset, we compared the short-term prognosis of COVID-19 infection according to the use of DPP-4i and RAS blockade. Additionally, we validated the results using the National Health Insurance Service (NHIS) of Korea dataset.
Results Totally, data of 67,850 subjects were accessible in the HIRA dataset. Of these, 5,080 were confirmed COVID-19. Among these, 832 subjects with DM were selected for analysis in this study. Among the subjects, 263 (31.6%) and 327 (39.3%) were DPP4i and RAS blockade users, respectively. Thirty-four subjects (4.09%) received intensive care or died. The adjusted odds ratio for severe treatment among DPP-4i users was 0.362 (95% confidence interval [CI], 0.135 to 0.971), and that for RAS blockade users was 0.599 (95% CI, 0.251 to 1.431). These findings were consistent with the analysis based on the NHIS data using 704 final subjects. The adjusted odds ratio for severe treatment among DPP-4i users was 0.303 (95% CI, 0.135 to 0.682), and that for RAS blockade users was 0.811 (95% CI, 0.391 to 1.682).
Conclusion This study suggests that DPP-4i is significantly associated with a better clinical outcome of patients with COVID-19.
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- Technology/Device
- Present and Future of Digital Health in Diabetes and Metabolic Disease
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Sang Youl Rhee, Chiweon Kim, Dong Wook Shin, Steven R. Steinhubl
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Diabetes Metab J. 2020;44(6):819-827. Published online December 23, 2020
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DOI: https://doi.org/10.4093/dmj.2020.0088
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- The use of information and communication technology (ICT) in medical and healthcare services goes beyond everyday life. Expectations of a new medical environment, not previously experienced by ICT, exist in the near future. In particular, chronic metabolic diseases such as diabetes and obesity, have a high prevalence and high social and economic burden. In addition, the continuous evaluation and monitoring of daily life is important for effective treatment and management. Therefore, the wide use of ICTbased digital health systems is required for the treatment and management of these diseases. In this article, we compiled a variety of digital health technologies introduced to date in the field of diabetes and metabolic diseases.
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- Clinical Care/Education
- Impact of Continuous Care on Health Outcomes and Cost for Type 2 Diabetes Mellitus: Analysis Using National Health Insurance Cohort Database
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Ji Hyun Nam, Changwoo Lee, Nayoung Kim, Keun Young Park, Jeonghoon Ha, Jaemoon Yun, Dong Wook Shin, Euichul Shin
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Diabetes Metab J. 2019;43(6):776-784. Published online October 21, 2019
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DOI: https://doi.org/10.4093/dmj.2018.0189
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- Background
The objective of the study was to determine the impact of continuous care on health outcomes and cost of type 2 diabetes mellitus (T2DM) in Korea. MethodsA nationwide retrospective, observational case-control study was conducted. Continuity of treatment was measured using Continuity of Care (COC) score. Information of all patients newly diagnosed with T2DM in 2004 was retrieved from the National Health Insurance database for the period of 2002 to 2013. The study examined 2,373 patients after applying exclusion criteria, such as for patients who died from conditions not related to T2DM. Statistical analyses were performed using frequency distribution, simple analysis (t-test and chi-squared test), and multi-method analysis (simple linear regression, logistic regression, and survival analysis). ResultsThe overall COC score was 0.8±0.24. The average incidence of diabetic complications was 0.39 per patient with a higher COC score, whereas it was 0.49 per patient with a lower COC score. In both survival and logistic analyses, patients who had high COC score were significantly less likely to have diabetic complications (hazard ratio, 0.69; 95% confidence interval, 0.54 to 0.88). The average medical cost was approximately 3,496 United States dollar (USD) per patient for patients with a higher COC score, whereas it was 3,973 USD per patient for patients with a lower COC score during the 2006 to 2013 period, with a difference of around 477 USD, which is statistically significant after adjusting for other factors (β=−0.152). ConclusionContinuity of care for diabetes significantly reduced health complications and medical costs from patients with T2DM.
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