Use of continuous glucose monitoring to improve diabetes mellitus management.

Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, Colorado, USA.
Endocrinology & Metabolism Clinics of North America (Impact Factor: 2.86). 12/2007; 36 Suppl 2:46-68. DOI: 10.1016/S0889-8529(07)80011-9
Source: PubMed
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    ABSTRACT: It has long been established that hyperglycemia with or without a prior diagnosis of diabetes increases both mortality and disease-specific morbidity in hospitalized patients and that goal-directed insulin therapy can improve outcomes. This article reviews the pathophysiology of hyperglycemia during illness, the mechanisms for increased complications and mortality due to hyperglycemia and hypoglycemia, and beneficial mechanistic effects of insulin therapy and provides updated recommendations for the inpatient management of diabetes in the critical care setting and in the general medicine and surgical settings.
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    ABSTRACT: Goal: For conventional modeling methods, the work of model identification has to be repeated with sufficient data for each subject because different subjects may have different response to exogenous inputs. This may cause repetitive cost and burden for patients and clinicians and require a lot of modeling efforts. Here, to overcome the above mentioned problems, a rapid model development strategy for new subjects is proposed using the idea of model migration for online glucose prediction. Methods: First, a base model is obtained which can be empirically identified from any subject or constructed by priori knowledge. Then parameters of inputs in the base model are properly revised based on a small amount of new data from new subjects so that the updated models can reflect the specific glucose dynamics excited by inputs for new subjects. These problems are investigated by developing auto-regressive models with exogenous inputs (ARX) based on thirty in silico subjects using UVA/Padova metabolic simulator. Results: The prediction accuracy of the rapid modeling method is comparable to that for subject-dependent modeling method for some cases. Also, it can present better generalization ability. Conclusion: The proposed method can be regarded as an effective and economic modeling method instead of repetitive subject-dependent modeling method especially for lack of modelling data.
    IEEE transactions on bio-medical engineering 01/2015; 62(5). DOI:10.1109/TBME.2014.2387293 · 2.23 Impact Factor
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    ABSTRACT: Diabetes mellitus is an independent risk factor for cardiovascular disease. To compare the efficacy of devices for continuous glucose monitoring and capillary glucose monitoring in hospitalized patients with acute coronary syndrome using the following parameters: time to achieve normoglycemia, period of time in normoglycemia, and episodes of hypoglycemia. We performed a pilot, non-randomized, unblinded clinical trial that included 16 patients with acute coronary artery syndrome, a capillary or venous blood glucose ≥140mg/dl, and treatment with a continuous infusion of fast acting human insulin. These patients were randomized into 2 groups: a conventional group, in which capillary measurement and recording as well as insulin adjustment were made every 4h, and an intervention group, in which measurement and recording as well as insulin adjustment were made every hour with a subcutaneous continuous monitoring system. Student's t-test was applied for mean differences and the X(2) test for qualitative variables. We observed a statistically significant difference in the mean time for achieving normoglycemia, favoring the conventional group with a P=0.02. Continuous monitoring systems are as useful as capillary monitoring for achieving normoglycemia.
    Archivos de cardiología de México 11/2013; DOI:10.1016/j.acmx.2013.08.001