OBJECTIVE: To determine whether a system of telemedicine support can improve glycemic control in type 1 diabetes. RESEARCH DESIGN AND METHODS: A 9-month randomized trial compared glucose self-monitoring real-time result transmission and feedback of results for the previous 24 h in the control group with real-time graphical phone-based feedback for the previous 2 weeks together with nurse-initiated support using a web-based graphical analysis of glucose self-monitoring results in the intervention group. All patients aged 18-30 years with HbA(1c) (A1C) levels of 8-11% were eligible for inclusion. RESULTS: A total of 93 patients (55 men) with mean diabetes duration (means +/- SD) 12.1 +/- 6.7 years were recruited from a young adult clinic. In total, the intervention and control groups transmitted 29,765 and 21,400 results, respectively. The corresponding median blood glucose levels were 8.9 mmol/l (interquartile range 5.4-13.5) and 10.3 mmol/l (6.5-14.4) (P < 0.0001). There was a reduction in A1C in the intervention group after 9 months from 9.2 +/- 1.1 to 8.6 +/- 1.4% (difference 0.6% [95% CI 0.3-1.0]) and a reduction in A1C in the control group from 9.3 +/- 1.5 to 8.9 +/- 1.4% (difference 0.4% [0.03-0.7]). This difference in change in A1C between groups was not statistically significant (0.2% [-0.2 to 0.7, P = 0.3). CONCLUSIONS: Real-time telemedicine transmission and feedback of information about blood glucose results with nurse support is feasible and acceptable to patients, but to significantly improve glycemic control, access to real-time decision support for medication dosing and changes in diet and exercise may be required.
RCT Entities:
OBJECTIVE: To determine whether a system of telemedicine support can improve glycemic control in type 1 diabetes. RESEARCH DESIGN AND METHODS: A 9-month randomized trial compared glucose self-monitoring real-time result transmission and feedback of results for the previous 24 h in the control group with real-time graphical phone-based feedback for the previous 2 weeks together with nurse-initiated support using a web-based graphical analysis of glucose self-monitoring results in the intervention group. All patients aged 18-30 years with HbA(1c) (A1C) levels of 8-11% were eligible for inclusion. RESULTS: A total of 93 patients (55 men) with mean diabetes duration (means +/- SD) 12.1 +/- 6.7 years were recruited from a young adult clinic. In total, the intervention and control groups transmitted 29,765 and 21,400 results, respectively. The corresponding median blood glucose levels were 8.9 mmol/l (interquartile range 5.4-13.5) and 10.3 mmol/l (6.5-14.4) (P < 0.0001). There was a reduction in A1C in the intervention group after 9 months from 9.2 +/- 1.1 to 8.6 +/- 1.4% (difference 0.6% [95% CI 0.3-1.0]) and a reduction in A1C in the control group from 9.3 +/- 1.5 to 8.9 +/- 1.4% (difference 0.4% [0.03-0.7]). This difference in change in A1C between groups was not statistically significant (0.2% [-0.2 to 0.7, P = 0.3). CONCLUSIONS: Real-time telemedicine transmission and feedback of information about blood glucose results with nurse support is feasible and acceptable to patients, but to significantly improve glycemic control, access to real-time decision support for medication dosing and changes in diet and exercise may be required.
Authors: Lynne T Harris; Keren Lehavot; David Huh; Samantha Yard; Michele P Andrasik; Peter J Dunbar; Jane M Simoni Journal: Telemed J E Health Date: 2010-11-18 Impact factor: 3.536
Authors: M Elena Hernando; Mario Pascual; Carlos H Salvador; Gema García-Sáez; Agustín Rodríguez-Herrero; Iñaki Martínez-Sarriegui; Enrique J Gómez Journal: J Diabetes Sci Technol Date: 2008-09
Authors: Francis C Cordova; David Ciccolella; Carla Grabianowski; John Gaughan; Kathleen Brennan; Frederick Goldstein; Michael R Jacobs; Gerard J Criner Journal: Telemed J E Health Date: 2015-08-10 Impact factor: 3.536