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21. Prediction of Daytime Hypoglycemic Events Using Continuous Glucose Monitoring Data and Classification Technique

Author

Jung, Miyeon, Lee, You-Bin, Jin, Sang-Man, and Park, Sung-Min

Subjects
Statistics - Machine Learning
Abstract

Daytime hypoglycemia should be accurately predicted to achieve normoglycemia and to avoid disastrous situations. Hypoglycemia, an abnormally low blood glucose level, is divided into daytime hypoglycemia and nocturnal hypoglycemia. Many studies of hypoglycemia prevention deal with nocturnal hypoglycemia. In this paper, we propose new predictor variables to predict daytime hypoglycemia using continuous glucose monitoring (CGM) data. We apply classification and regression tree (CART) as a prediction method. The independent variables of our prediction model are the rate of decrease from a peak and absolute level of the BG at the decision point. The evaluation results showed that our model was able to detect almost 80% of hypoglycemic events 15 min in advance, which was higher than the existing methods with similar conditions. The proposed method might achieve a real-time prediction as well as can be embedded into BG monitoring device.

Published
2017

28. Clinical Characteristics, Diagnosis, and Treatment of Thyroid Stimulating Hormone-Secreting Pituitary Neuroendocrine Tumor (TSH PitNET): A Single-Center Experience

Author

Heo, Jung, primary, Suh, Yeon-Lim, additional, Kim, Se Hoon, additional, Kong, Doo-Sik, additional, Nam, Do-Hyun, additional, Lee, Won-Jae, additional, Kim, Sung Tae, additional, Hong, Sang Duk, additional, Ryu, Sujin, additional, Lee, You-Bin, additional, Kim, Gyuri, additional, Jin, Sang-Man, additional, Kim, Jae Hyeon, additional, and Hur, Kyu Yeon, additional

Published
2024
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35. 췌도부전당뇨병에 대한 입장 성명서.

Author

Kim, Ji Yoon, Jin, Sang-Man, Kim, Gyuri, Kim, Soo Kyoung, Kim, Won Jun, Moon, Sun Joon, Yoo, Jee Hee, Lee, Da Young, Lee, Seung-Eun, Jun, Ji Eun, and Kim, Jae Hyeon

Abstract

Diabetes mellitus is a heterogeneous disease that encompasses a wide range of conditions, from mild cases to severe conditions where survival depends on insulin therapy. The Korean Diabetes Association Task Force Team for Diabetes with β-Cell Failure has established the term to classify severe refractory disease with β-cell failure. Individuals with β-cell failure are at high risk of diabetes-related complications. We propose that diabetes with β-cell failure can be diagnosed when individuals treated with multiple daily insulin injections or insulin pumps meet at least one of the following criteria: fasting C-peptide ≤ 0.6 ng/mL, non-fasting C-peptide ≤ 1.8 ng/mL, 24-hour urine C-peptide < 30 μg/day, or spot urine C-peptide/creatinine ratio ≤ 0.6 nmol/mmol. Among cases of diabetes with β-cell failure, β-cell failure with absolute insulin deficiency can be diagnosed when at least one of the following criteria is met: fasting C-peptide < 0.24 ng/mL, non-fasting C-peptide < 0.6 ng/mL, or spot urine C-peptide/creatinine ratio < 0.2 nmol/mmol. Multiple daily insulin injections with long-acting insulin analogs and rapid-acting insulin analogs or insulin pumps are required for treatment of diabetes with β-cell failure. Continuous glucose monitoring and an automated insulin delivery system, sensor-augmented pump, or smart insulin pen, along with structured education, are necessary. We call for improvements in the relevant systems to ensure that such treatments can be provided. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Risk of Depression according to Cumulative Exposure to a Low-Household Income Status in Individuals with Type 2 Diabetes Mellitus: A Nationwide Population- Based Study

Author

Park, So Hee, primary, Lee, You-Bin, additional, Lee, Kyu-na, additional, Kim, Bongsung, additional, Cho, So Hyun, additional, Kwon, So Yoon, additional, Park, Jiyun, additional, Kim, Gyuri, additional, Jin, Sang-Man, additional, Hur, Kyu Yeon, additional, Han, Kyungdo, additional, and Kim, Jae Hyeon, additional

Published
2024
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43. Real-World Continuous Glucose Monitoring Data from a Population with Type 1 Diabetes in South Korea: Nationwide Single-System Analysis.

Author

Kim, Ji Yoon, Jin, Sang-Man, Andrade, Sarah B., Chen, Boyang, and Kim, Jae Hyeon

Subjects
*CONTINUOUS glucose monitoring, *TYPE 1 diabetes, *INSTITUTIONAL review boards, *KOREANS
Abstract

Background: We used continuous glucose monitoring (CGM) data to investigate glycemic outcomes in a real-world population with type 1 diabetes (T1D) from South Korea, where the widespread use of CGM and the nationwide education program began almost simultaneously. Methods: Data from Dexcom G6 users with T1D in South Korea were collected between January 2019 and January 2023. Users were included if they provided at least 90 days of glucose data and used CGM at least 70% of the days in the investigational period. The relationship between CGM utilization and glycemic metrics, including the percentage of time in range (TIR), time below range (TBR), and time above range (TAR), was assessed. The study was approved by the Institutional Review Board of Samsung Medical Center (SMC 2023-05-030). Results: A total of 2288 users were included. Mean age was 41.5 years (57% female), with average uploads of 428 days. Mean TIR was 62.4% ± 18.5%, mean TBR <70 mg/dL was 2.6% ± 2.8%, mean TAR >180 mg/dL was 35.0% ± 19.3%, mean glucose was 168.1 ± 35.8 mg/dL, mean glucose management indicator was 7.2% ± 0.9%, and mean coefficient of variation was 36.7% ± 6.0%. Users with higher CGM utilization had higher TIR (67.8% vs. 52.7%), and lower TBR <70 mg/dL (2.3% vs. 4.7%) and TAR >180 mg/dL (30.0% vs. 42.6%) than those with low CGM utilization (P < 0.001 for all). Users whose data were shared with others had higher TIR than those who did not (63.3% vs. 60.8%, P = 0.001). Conclusions: In this South Korean population, higher CGM utilization was associated with a favorably higher mean TIR, which was close to the internationally recommended target. Using its remote data-sharing feature showed beneficial impact on TIR. [ABSTRACT FROM AUTHOR]

Published
2024
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