BACKGROUND: Advancements in diabetes technology now allow insulin pump and continuous glucose monitor (CGM) technology to be a part of usual US Department Veterans Affairs (VA) clinical care. The automated insulin pump (AIP) delivers insulin automatically based on CGM readings. In randomized clinical trials the closed-loop system has shown to improve glycemic control in children and younger adults with type 1 diabetes mellitus (T1DM) while preventing hypoglycemia. However, its safety and efficacy is less well known in older veterans with T1DM. In this VA pilot study, we aimed to assess AIP technology in the real world of an older population of veterans with T1DM followed in the outpatient setting. METHODS: Thirty-seven patients with T1DM new to AIP seen at the Malcom Randall VA Medical Center in Gainesville, Florida, were evaluated between March and December of 2018 on an Medtronic Minimed 670G Insulin Pump System. We collected demographic as well as clinical data before and after the initiation of AIP, including standard insulin pump/CGM information (sensor wear, time in target glucose range, time in automated mode, other). RESULTS: At the time of the initiation of AIP, the mean (SD) age of patients was 59.1 (14.4) years; 35 identified as male and 2 as female. The mean (SD) duration of T1DM was 25.3 (12.0) years. Patients transitioned from either insulin injections or other non-AIP pump to AIP safely-there was no increase in hypoglycemia, and the mean (SD) hemoglobin A1c decreased from 7.6% (0.8) to 7.3% (0.8) by the second follow-up visit. CONCLUSION: In this real-world study, AIP use was both safe and viable as a tool for T1DM management with older veterans. This technology further engaged veterans in monitoring their blood sugars and achieving more optimal glycemic control. Future long-term, larger studies are much needed in this setting.
BACKGROUND: Advancements in diabetes technology now allow insulin pump and continuous glucose monitor (CGM) technology to be a part of usual US Department Veterans Affairs (VA) clinical care. The automated insulin pump (AIP) delivers insulin automatically based on CGM readings. In randomized clinical trials the closed-loop system has shown to improve glycemic control in children and younger adults with type 1 diabetes mellitus (T1DM) while preventing hypoglycemia. However, its safety and efficacy is less well known in older veterans with T1DM. In this VA pilot study, we aimed to assess AIP technology in the real world of an older population of veterans with T1DM followed in the outpatient setting. METHODS: Thirty-seven patients with T1DM new to AIP seen at the Malcom Randall VA Medical Center in Gainesville, Florida, were evaluated between March and December of 2018 on an Medtronic Minimed 670G Insulin Pump System. We collected demographic as well as clinical data before and after the initiation of AIP, including standard insulin pump/CGM information (sensor wear, time in target glucose range, time in automated mode, other). RESULTS: At the time of the initiation of AIP, the mean (SD) age of patients was 59.1 (14.4) years; 35 identified as male and 2 as female. The mean (SD) duration of T1DM was 25.3 (12.0) years. Patients transitioned from either insulin injections or other non-AIP pump to AIP safely-there was no increase in hypoglycemia, and the mean (SD) hemoglobin A1c decreased from 7.6% (0.8) to 7.3% (0.8) by the second follow-up visit. CONCLUSION: In this real-world study, AIP use was both safe and viable as a tool for T1DM management with older veterans. This technology further engaged veterans in monitoring their blood sugars and achieving more optimal glycemic control. Future long-term, larger studies are much needed in this setting.
Authors: Sue A Brown; Boris P Kovatchev; Dan Raghinaru; John W Lum; Bruce A Buckingham; Yogish C Kudva; Lori M Laffel; Carol J Levy; Jordan E Pinsker; R Paul Wadwa; Eyal Dassau; Francis J Doyle; Stacey M Anderson; Mei Mei Church; Vikash Dadlani; Laya Ekhlaspour; Gregory P Forlenza; Elvira Isganaitis; David W Lam; Craig Kollman; Roy W Beck Journal: N Engl J Med Date: 2019-10-16 Impact factor: 91.245
Authors: Araz Rawshani; Naveed Sattar; Stefan Franzén; Aidin Rawshani; Andrew T Hattersley; Ann-Marie Svensson; Björn Eliasson; Soffia Gudbjörnsdottir Journal: Lancet Date: 2018-08-09 Impact factor: 79.321