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With emerging mobile technology, sharing glucose, insulin and sensor data with the clinic for frequent and timely monitoring is now feasible. The investigators propose to leverage this new technology to provide children and families with appropriate interventions to help manage their diabetes.
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The investigators will collect insulin dosing via pump records, blood glucose meter, continuous glucose sensor, activity, heart rate, and sleep data on a weekly basis from 100 children with diabetes. The investigators hypothesize that with the collection and analysis of insulin, blood glucose, sensor, activity, heart rate and sleep data in children with diabetes the investigators can identify glucose patterns and predictors of acute events.
The 100 children will be randomized to either conventional therapy (data upload group) or intensive remote therapy (weekly review group). Conventional therapy will consist of routine quarterly visits to the clinic and as-needed communication with the diabetes staff, initiated by the family, between study visits. Intensive remote therapy will consist of routine quarterly visits to the clinic along with weekly remote review of insulin and blood glucose data by the research staff, and additional communication with the family, initiated by the diabetes staff as needed, between visits. The investigators hypothesize that with weekly, manual review of real-time insulin, glucose, and activity data in children with diabetes, and recommended regimen changes based on the data, the investigators will be able to lower HbA1c values in children in the weekly review group as compared to children in the data upload group.
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113 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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