DIgital Assisted MONitoring for DiabeteS - I

NCT01804803 | Completed DMC

• 1 other identifier: DIAMONDS-I
• Study Type: interventional
• Target: 123
• Locations: 1 country
• Sites: 3

Brief Summary

The study aims to validate the clinical efficacy of a telemedicine- and web-based system platform for Self-monitoring of blood glucose (SMBG) data transmission and analysis in terms of improved metabolic control, assessed by measuring changes in HbA1c, in insulin-treated diabetic patients. The system platform involves (i.) systematic (real-time and anywhere) transmission of SMBG data to a decision supported software (DSS)-assisted server, (ii.) web-based analysis of data, and (iii.) feedback on patients and medical staff to implement metabolic control. The expected outcome is that using this telemedicine-based system with transmission of SMBG data, web-based analysis of data and medical feedback to patients and medical team will improve glucose control in insulin-treated individuals with type 1 or type 2 diabetes mellitus.

Conditions

Diabetes Mellitus

Keywords

glycated hemoglobin; hyperglycemia; hypoglycemia; insulin; self-monitoring of blood glucose; telemedicine

Outcome Measures

Primary Outcomes (1)

• Changes in HbA1c from baseline value

  3-month, 6-month

Secondary Outcomes (13)

• Changes in HbA1c from baseline value in relation to HbA1c value at baseline

  6-month

• Percentages of patients with HbA1c >8.5% at 3 and 6 months

  3-month, 6-month

• Percentages of patients with HbA1c <7.0% at 3 and 6 months

  3-month, 6-month

• Percentages of patients with HbA1c <6.5% at 3 and 6 months

  3-month, 6-month

• Differences in fasting blood glucose levels

  3-month, 6-month

Study Arms (2)

T-SMBG

EXPERIMENTAL

This group will perform SMBG using a smartphone-connected glucometer implemented with a software for real-time collection and transmission of measured glucose values to the remote server. SMBG results will be immediately transmitted to the remote server, which will perform data collection and analysis, and provide feed-back to the patient and the medical staff according to pre-defined specific algorithms (Decision Supported Software, DSS). A specific algorithm incorporated into the DSS will allow the patients to self-calculate the dose of basal insulin to be administered according to the measured fasting blood glucose levels for consecutive periods of three days. Glucose data and analyses will be made accessible to the patients and medical staff anytime and anywhere via the web. Patients will be also assisted by the diabetes medical team located at or connected with a call center 24-hours/day, 7 days/week.

Procedure: Use of software-implemented glucometer for real-time collection and transmission of measured glucose values to remote server.

SMBG

ACTIVE COMPARATOR

This group will perform SMBG using a regular glucometer and will report glucose data on paper charts (or download data from the glucometer onto the PC) at the planned study visits. Patients will not receive feed-back on their glucose levels nor instructions on how to potentially modify their drug therapy except when undergoing medical visits at the planned intervals. Patients, finally, will not be assisted by the diabetes team/call center.

Procedure: Use of regular glucometer

Interventions

Use of software-implemented glucometer for real-time collection and transmission of measured glucose values to remote server. PROCEDURE

Device is a smartphone-connected glucometer. The smartphone will be implemented with a software for real-time collection and transmission of measured glucose values to the remote server. Thus, the glucometer will be made "hot" for real-time and anywhere data transmission. In addition, at the time of blood glucose measuring, the patient will enter information on whether the measurement is being performed in the pre-prandial, post-prandial or absorptive periods, and will indicate which meals the measurement refers to (i.e., breakfast, lunch, dinner, snack). SMBG results will be immediately transmitted to the remote server, which will perform data collection and analysis, and provide feed-back to the patient and the medical staff according to pre-defined specific algorithms (Decision Supported Software, DSS).

T-SMBG

Use of regular glucometer PROCEDURE

SMBG

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• males and females
• age 18-70 yrs;
• insulin-treated diabetes (both type 1 and type 2 diabetes treated with at least 3 injections/day);
• diabetes diagnosis from at least 1 year;
• inadequate glycemic control (HbA1c ranging from 7.0% to 10.0%; local measurements within the last 6 weeks);
• ability and willingness to carry out SMBG;
• informed consent.

You may not qualify if:

• diagnosis of diabetes within less than 1 year;
• impending complications of diabetes: proliferative retinopathy or maculopathy (with significant loss of visual function), severe renal failure (eGFR \<30), severe neuropathy (autonomic dysfunction, peripheral neuropathy, gastroparesis);
• clinically significant, active (over the past 12 months) disease of the cardiovascular, gastrointestinal, neurological, genito-urinary, haematological systems or severe uncontrolled hypertension (SBP \>180 mmHg; DBP \>100 mmHg);
• diagnosis of active neoplasia within the last 5 years (history of chemotherapy or radiation treated malignancy within 5 years prior to study procedure, except for lymphoma);
• pregnancy or intention to become pregnant during the study;
• poor compliance to study procedures.

Sponsors & Collaborators

• University of Bari: lead
• Eli Lilly and Company: collaborator
• LifeScan: collaborator

Study Sites (3)

University of Bari Aldo Moro

Bari, BA, 70124, Italy

Location

IRCSS Casa Sollievo Sofferenza

San Giovanni Rotondo, FG, Italy

Location

University of Foggia

Foggia, Italy

Location

Related Publications (5)

• Bujnowska-Fedak MM, Puchala E, Steciwko A. The impact of telehome care on health status and quality of life among patients with diabetes in a primary care setting in Poland. Telemed J E Health. 2011 Apr;17(3):153-63. doi: 10.1089/tmj.2010.0113. Epub 2011 Mar 5.

  PMID: 21375410 BACKGROUND

• Charpentier G, Benhamou PY, Dardari D, Clergeot A, Franc S, Schaepelynck-Belicar P, Catargi B, Melki V, Chaillous L, Farret A, Bosson JL, Penfornis A; TeleDiab Study Group. The Diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improves HbA1c in poorly controlled type 1 diabetic patients: a 6-month, randomized, open-label, parallel-group, multicenter trial (TeleDiab 1 Study). Diabetes Care. 2011 Mar;34(3):533-9. doi: 10.2337/dc10-1259. Epub 2011 Jan 25.

  PMID: 21266648 BACKGROUND

• Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X, Huang J, Wang L, Gu D. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabet Med. 2011 Apr;28(4):455-63. doi: 10.1111/j.1464-5491.2010.03180.x.

  PMID: 21392066 BACKGROUND

• Shea S, Weinstock RS, Teresi JA, Palmas W, Starren J, Cimino JJ, Lai AM, Field L, Morin PC, Goland R, Izquierdo RE, Ebner S, Silver S, Petkova E, Kong J, Eimicke JP; IDEATel Consortium. A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus: 5 year results of the IDEATel study. J Am Med Inform Assoc. 2009 Jul-Aug;16(4):446-56. doi: 10.1197/jamia.M3157. Epub 2009 Apr 23.

  PMID: 19390093 BACKGROUND

• Di Molfetta S, Patruno P, Cormio S, Cignarelli A, Paleari R, Mosca A, Lamacchia O, De Cosmo S, Massa M, Natalicchio A, Perrini S, Laviola L, Giorgino F. A telemedicine-based approach with real-time transmission of blood glucose data improves metabolic control in insulin-treated diabetes: the DIAMONDS randomized clinical trial. J Endocrinol Invest. 2022 Sep;45(9):1663-1671. doi: 10.1007/s40618-022-01802-w. Epub 2022 Apr 27.

  PMID: 35476320 DERIVED

MeSH Terms

Conditions

Diabetes Mellitus; Hyperglycemia; Hypoglycemia; Insulin Resistance

Condition Hierarchy (Ancestors)

Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Hyperinsulinism

Study Officials

• Francesco Giorgino, M.D., Ph.D.

  University of Bari Aldo Moro

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Endocrinology

Study Record Dates

• First Submitted: February 25, 2013
• First Posted: March 5, 2013
• Study Start: September 9, 2013
• Primary Completion: November 30, 2017
• Study Completion: November 30, 2017
• Last Updated: June 4, 2020

Record last verified: 2020-06

Locations

IT (3)