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OpenTrials
Completed

NCT Number: NCT03544320

Prediction Using Connected Technologies for Diabetes

In this study, adults with pre-diabetes will be prospectively enrolled for data collection to design prediction models that integrate electronic health record data and patient-generated activity data. Patients will be randomized to receive either a waist-worn or wrist-worn wearable device for 6 months to capture patient-generated activity data.

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Key information

Conditions

Pre-diabetes Diabetes Mellitus Endocrine System Diseases Glucose Intolerance Glucose Metabolism Disorders Hyperglycemia Metabolic Diseases Nutritional and Metabolic Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Penn Medicine

Philadelphia, Pennsylvania, 19103, United States

About this study

Patients with suboptimal glycemic control could be better managed if these higher risk patients could be identified and effective interventions were then targeted towards them. However, most practice settings perform infrequent laboratory testing every 3 to 6 months, if not at longer intervals. Current models to predict change in glycemic control perform poorly and do not take into account the behaviors that occur between these intervals. In this study, we will compare different methods to use data on daily health behaviors collected by wearable devices to enhance risk prediction models. Adults with pre-diabetes will complete a series of surveys and baseline assessments and then will be randomly assigned to use a waist-worn or wrist-worn wearable device for 6 months. Measures of HbA1c and LDL will be obtained at baseline and at 6 months.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Be 18 years or older
  • Be able to provide informed consent
  • Have a smartphone or tablet compatible with the wearable device smartphone application and be willing to use the wearable device for 6 months
  • Baseline hemoglobin A1c of 5.7 to 6.4

Exclusion criteria

Participants will no be eligible if they have any medical condition or other reason that will likely prohibit them from completing the 6-month study

Treatment and study plan

Activity Monitoring-Wrist worn wearable

Device

Participants wear an activity monitor on their wrist.

Activity Monitoring-Waist-worn wearable

Device

Participants wear an activity monitor on their waist.

Primary outcomes

  1. Change in hemoglobin A1c

    Time frame: 6 months

    Change in hemoglobin A1c from baseline to 6 months

Secondary outcomes

  1. Change in low-density lipoprotein (LDL) levels

    Time frame: 6 months

    Change in LDL level from baseline to 6 months

Other outcomes

  1. Hospitalization

    Time frame: 6 months

    Admission to the hospital

Sponsors and collaborators

Lead sponsor

University of Pennsylvania

Other

Registry information

Official study title

Prediction Using a Randomized Evaluation of Data Collection Integrated Through Connected Technologies for Diabetes Management

Acronym: PREDICT-DM

Important dates

Study start
2018
Primary completion
2019
Study completion
2019
First posted
Jun 1, 2018
Registry last updated
Aug 29, 2019

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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