Assess the Impact of Insulclock on Glycemic Variability and Treatment Compliance in Uncontrolled DM1 Patients

Summary

Insulclock® is a small electronic device developed to facilitate the optimal administration of insulin. This device works as an add-on module of commercially available insulin pens and monitors the date, time and dose of injections, the type of insulin injected, the duration of injections and insulin temperature. The Insulclock 360 app allows automatic data logging, report generation and reminder setting, among other functions. In this study, we pretend to show the clinical impact of Insulclock system, both device and mobile application, on glycemic indices, treatment compliance, and quality of life in patients with persistent poorly controlled T1DM.

Material and methods: Randomized open-label multicenter controlled trial to evaluate glycemic control, the number of missed and delayed insulin doses, and quality of life after seven weeks of Insulclock 360 use in participants with uncontrolled DM1. We will also compare these results between patients with or without receiving system reminders and alerts.

This study aims to assess the effect of Insulclock on glycemic control, treatment adherence, and quality of life. As a secondary objective, we will compare the study outcomes between participants in the Active and Masked Insulclock groups (i.e., with or without receiving alerts and reminders and accessing the app).

To assess glycemic control, we will measure HbA1C and glycemic indices. Glycemic variability indices will be monitored with the FreeStyle Libre™ and included glucose coefficient of variation (CV), standard deviation (SD), time in range (TIR), time above range (TAR), and time below range (TBR). Mean glucose levels will be obtained from 48-h time intervals with the FreeStyle Libre.

A late meal bolus (mistimed) will be considered when Insulclock detects the injection at least 30 minutes after the CGM rise. To identify meal glucose excursions, we will use the Glucose Rate Increase Detector (GRID) algorithm, which estimates the rate of change (ROC) of glucose from CGM data.

Participants will complete the ITSQ and the DTSQ, which are validated questionnaires to assess the diabetes treatment satisfaction.

Conditions

• Diabetes Mellitus, Type 1

Interventions

DEVICE

Use of Insulclock system, both Insulclock device and Insulclock 360 app.

Visit 5, during week 4. Randomization will be applied: Active group will use all functionalities of Insulclock 360. They will have reminders, all their information and statistics at the disposition of the patient and healthcare providers, they have the assistance if desired of an ally or caregiver, a bolus calculator and the rest of functionalities described in the protocol.

DEVICE

Use of Insulclock system, both Insulclock device and Insulclock app on masked mode.

Visit 5, during week 4. Randomization will be applied: Masked group will remain with the masked system, without functionalities.

Sponsors & Collaborators

• Insulcloud S.L.

  collaborator INDUSTRY

• Hospital General de Segovia

  lead OTHER

Principal Investigators

• Fernando Gomez Peralta, Physician · Hospital General de Segovia, Segovia, Spain

Study Design

Allocation

RANDOMIZED

Purpose

SUPPORTIVE_CARE

Masking

SINGLE

Model

PARALLEL

Eligibility

Min Age

14 Years

Max Age

80 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2021-03-01

Primary Completion

2021-06-30

Completion

2021-07-31

Countries

• Spain

Study Locations