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The aim of the project is to document the international routine practice in sensor usage in patients treated with sensor-augmented pump therapy and to assess which variables (e.g. training of patients, frequency of sensor usage etc) are associated with an improvement in clinical outcome(s) from the start of the sensor use to the end of the follow-up period.
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Pump therapy has been established as "gold standard" for insulin delivery offering improvements over multiple daily insulin injections, but there is a proportion of patients for whom the Continuous Subcutaneous Insulin Infusion (CSII) has not been completely successful therapy leaving some room for improvement of the glucose level of those patients. Continuous glucose monitoring (CGM) systems represent an important advance in diabetes technology that can facilitate optimal glucose control in type 1 diabetes. Numerous randomized control trials have demonstrated the safety and efficacy of real-time CGM in both sub-optimally and well-controlled type 1 diabetes. In all these trials, the benefits of CGM correlate with frequent sensor wear and more advanced age. In clinical practice, the sensor-augmented pump therapy (SAP therapy) is indicated for patients who cannot achieve good metabolic control on CSII, who have a history of severe hypoglycemia and/or hypoglycemia unawareness, or who desire increased flexibility in their daily lives while maintaining or even improving their HbA1c levels.
This was a post-market release, minimally interventional study. All the study devices and related software were CE-marked and commercially available in the countries participating to the study. The devices were prescribed and reimbursed, if applicable, according to routine practice.
The gathered information during this study may help to define which patient groups benefit the most from the treatment with SAP therapy systems. The real-life results of these descriptive analyses will aid improvement of guidelines helping the medical community to better choose the right patient population and treatment patterns. Moreover, based on these real-life data, hypotheses could be defined when addressing further research questions.
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Data sourced from clinicaltrials.gov
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