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논문 기본 정보

자료유형
학술저널
저자정보
박성운 (성균관대학교) 이승현 (포항공과대학교) 차원철 (삼성서울병원) 허규연 (성균관대학교) 김재현 (성균관대학교 의과대학) 이문규 (성균관대학교) 박성민 (포항공과대학교) 진상만 (삼성서울병원)
저널정보
대한당뇨병학회 Diabetes and Metabolism Journal Diabetes and Metabolism Journal Vol.44 No.1
발행연도
2020.1
수록면
56 - 66 (11page)

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Background: We aimed to describe the outcome of a computerized intravenous insulin infusion (CII) protocol integrated to the electronic health record (EHR) system and to improve the CII protocol in silico using the EHR-based predictors of the outcome. Methods: Clinical outcomes of the patients who underwent the CII protocol between July 2016 and February 2017 and their matched controls were evaluated. In the CII protocol group (n=91), multivariable binary logistic regression analysis models were used to determine the independent associates with a delayed response (taking ≥6.0 hours for entering a glucose range of 70 to 180 mg/dL). The CII protocol was adjusted in silico according to the EHR-based parameters obtained in the first 3 hours of CII. Results: Use of the CII protocol was associated with fewer subjects with hypoglycemia alert values (P=0.003), earlier (P=0.002), and more stable (P=0.017) achievement of a glucose range of 70 to 180 mg/dL. Initial glucose level (P=0.001), change in glucose during the first 2 hours (P=0.026), and change in insulin infusion rate during the first 3 hours (P=0.029) were independently associated with delayed responses. Increasing the insulin infusion rate temporarily according to these parameters in silico significantly reduced delayed responses (P<0.0001) without hypoglycemia, especially in refractory patients. Conclusion: Our CII protocol enabled faster and more stable glycemic control than conventional care with minimized risk of hypoglycemia. An EHR-based adjustment was simulated to reduce delayed responses without increased incidence of hypoglycemia.

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