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This study aims to produce new evidence on the positive effects of physical activity and certain individual lifestyles in the control of type 2 diabetic disease. The goal is to build and evaluate the effectiveness of a new parsimonious risk prediction model based on the use of classical variables (blood exams), already used in other models for predicting the risk related to the disease, together with measures obtained from the use of wearable devices (steps count, sleep hours, heart rate).
Scientific literature has shown that the use of wearable devices can improve the control of type 2 diabetes mellitus. The aim of the study is to develop a statistical model for the control of type 2 diabetes mellitus (DMT2) based on the use of "conventional" clinical parameters and the use of "unconventional" data from wearable devices. The medical outcome variable that will be used to measure diabetes control and model performance will be the Glycated Hemoglobin (HbA1c). The participant will receive a Samsung smartwatch (Galaxy Watch 3) and a Samsung smartphone (A51), (the latter only in case the participant is not in possession of a compatible smartphone) which he/she must wear during his daily activities and also during the night to measure daily activity, sleep hours and heart rate. Casa Sollievo della Sofferenza Hospital previoulsy developted the ENFORCE calculator, an inexpensive and parsimonious prediction model of 2-year all cause mortality in real life patients with T2D. In this study the investigators aim to elaborate a standardized validated risk scores similar to what has been done for ENFORCE.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| TYPE 2 DIABETES | Patients affected by type 2 diabetes |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Standard care for T2D patients, Smartwatch | Other | No intervention, observational study |
|
| Measure | Description | Time Frame |
|---|---|---|
| Change from Baseline HbA1c at 6 and 12 months | Glycated Hemoglobin | Baseline, 6 months, 12 months |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with type 2 diabetes followed by Casa Sollievo della Sofferenza Hospital
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| Name | Affiliation | Role |
|---|---|---|
| Salvatore De Cosmo, MD | Casa Sollievo della Sofferenza IRCCS | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Casa Sollievo della Sofferenza IRCCS | San Giovanni Rotondo | FG | 71013 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31087060 | Background | Copetti M, Shah H, Fontana A, Scarale MG, Menzaghi C, De Cosmo S, Garofolo M, Sorrentino MR, Lamacchia O, Penno G, Doria A, Trischitta V. Estimation of Mortality Risk in Type 2 Diabetic Patients (ENFORCE): An Inexpensive and Parsimonious Prediction Model. J Clin Endocrinol Metab. 2019 Oct 1;104(10):4900-4908. doi: 10.1210/jc.2019-00215. |
| Label | URL |
|---|---|
| This study is currently in the frame of Horizon2020 GATEKEEPER project, that is a European Multi Centric Large-Scale Pilot on Smart Living Environments. | View source |
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| ID | Term |
|---|---|
| D003924 | Diabetes Mellitus, Type 2 |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| ID | Term |
|---|---|
| D059039 | Standard of Care |
| ID | Term |
|---|---|
| D019984 | Quality Indicators, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
| D017530 | Health Care Quality, Access, and Evaluation |
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| D004700 | Endocrine System Diseases |