Study Results
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Basic Information
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COMPLETED
NA
123 participants
INTERVENTIONAL
2013-09-09
2017-11-30
Brief Summary
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Detailed Description
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There is a growing body of evidence to suggest that telemedicine is an effective intervention for improving glucose control. Use of telephone contacts, video-conferencing, personal digital assistants and web-based systems offer new opportunities to bridge the gap in support for patients with diabetes between face to face visits with their health care providers. Several small-scale and non-randomized studies have found that patients exposed to telemonitoring interventions had lower HbA1c values than those without. Moreover, larger randomized controlled studies have also shown promising results. In the most comprehensive randomized comparison of telemonitoring interventions yet completed, the IDEATel study, 1,665 participants were randomized to a telemedicine unit or conventional care. At 1 year, patients in intervention group showed significantly lower HbA1c (-0.38 % p\<0.01), systolic and diastolic blood pressure, (respectively, -3.4 mmHg, p= 0.001; -1.9 mmHg, p\<0.001), and low density lipoprotein (LDL) cholesterol (-9.5 mg/dL, p\< 0.001). In patients blindly assessed annually over a period of five years, it was found that the telemedicine group scored better than the standard care group on virtually all outcome measures at each annual evaluation. Mortality was not different between the groups, although power was limited \[Shea S, 2009\]. More recently, Charpentier et al., in a six-month multicenter study, enrolled 180 adult patients with type 1 diabetes on a basal-bolus insulin regimen, with baseline HbA1c ≥8%. Patients were randomized to either usual quarterly follow-up, or home use of a smartphone recommending insulin doses with quarterly visits, or use of the smartphone with short teleconsultations every two weeks but no visit until endpoint (Diabeo system). Use of the Diabeo system yielded a 0.91% decrease in HbA1c over controls and a 0.67% decrease in HbA1c when used without teleconsultation. There was no difference in the frequency of hypoglycemic episodes or in medical time spent for hospital or telephone consultations. However, patients using the Diabeo system spent nearly 5 h less than patients in other groups in attending hospital visits \[Charpentier G, 2011\]. Similarly, Bujnowska-Fedak et al enrolled a total of 100 adult patients with type 2 diabetes, divided between insulin- and non-insulin-requiring, in a randomized, controlled trial aimed at investigating the effects of telehome monitoring. The experimental group (n = 50) received an in-home wireless glucose monitor and transmitter, whereas the control group (n = 50) was instructed to follow the conventional arrangement. There was an overall reduction in HbA1c values in both experimental and control groups after 6 months. A significant difference in HbA1c values between the groups was observed only among the noninsulin-requiring patients. The experimental group reported considerably less hyperglycemic and hypoglycemic events. The profile of the patient who benefited the most from telemonitoring consisted of older, more educated patients, who had acquired the disease relatively recently, and who spent most of the time at home. The experimental group had higher overall scores on quality of life measures and sense of control over diabetes \[Bujnowska-Fedak MM, 2011\]. A recent meta-analysis of 22 trials and a total of 1,657 participants showed that mobile phone interventions for diabetes self-management reduced HbA1c values by a mean of 0.5% over a median of 6-month follow-up duration. Interestingly, type 2 diabetes patients reported significantly greater reductions in HbA1c than type 1 diabetes patients (0.8 vs. 0.3%; P = 0.02) \[Liang X, 2011\]. In conclusion, telemedicine case management intervention and tele-home care may potentially assist in daily diabetes management via the establishment of an active interaction between diabetic patients and healthcare professionals. However, further evidence is warranted, particularly when considering new innovative systems with a potential for implementation of patient's assistance and of diabetes drug therapy remotely.
We have recently developed a telemedicine system \[Glucoonline®, 2011\], which consists of a smartphone-connected glucometer, a software-implemented smartphone for real-time and anywhere BG data collection and transmission to a remote server, and a Decision Supported Software (DSS)-assisted server capable of performing data collection and analysis, and providing feed-back to the patient and the medical staff according to pre-defined specific algorithms. A pilot study showing the feasibility of using this system in 10 individuals with type 1 diabetes treated with a multiple daily injection (MDI) regimen over a 3-month period has been already carried out \[Giorgino F, data on file\]. We believe that this system could be now utilized in a prospective randomized controlled trial to investigate its suitability to enable improved glucose control in insulin-treated individuals with type 1 or type 2 diabetes mellitus.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
TREATMENT
NONE
Study Groups
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T-SMBG
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.
Use of software-implemented glucometer for real-time collection and transmission of measured glucose values to remote server.
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).
SMBG
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.
Use of regular glucometer
Interventions
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Use of software-implemented glucometer for real-time collection and transmission of measured glucose values to remote server.
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).
Use of regular glucometer
Eligibility Criteria
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Inclusion Criteria
* 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.
Exclusion Criteria
* 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.
18 Years
70 Years
ALL
No
Sponsors
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Eli Lilly and Company
INDUSTRY
LifeScan
INDUSTRY
University of Bari
OTHER
Responsible Party
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Francesco Giorgino, M.D., Ph.D.
Professor of Endocrinology
Principal Investigators
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Francesco Giorgino, M.D., Ph.D.
Role: PRINCIPAL_INVESTIGATOR
University of Bari Aldo Moro
Locations
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University of Bari Aldo Moro
Bari, BA, Italy
IRCSS Casa Sollievo Sofferenza
San Giovanni Rotondo, FG, Italy
University of Foggia
Foggia, , Italy
Countries
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References
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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.
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.
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.
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.
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.
Other Identifiers
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DIAMONDS-I
Identifier Type: -
Identifier Source: org_study_id
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