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Automated insulin delivery decreased hypoglycemia compared with sensor-augmented pump delivery in elderly with type 1 diabetes: NEJM
A new study published in the NEJM Evidence journal showed that automated insulin delivery reduced hypoglycemia in older persons with type 1 diabetes when compared to sensor-augmented pump administration.
Under the general heading of automated insulin delivery (AID) systems, a "technical" approach to managing diabetes has emerged. To automate subcutaneous insulin administration, these AID systems combine information from an insulin pump, a control algorithm, and a continuous glucose monitoring (CGM) device.
Due to the paucity of clinical research and the lack of consistency in the diagnosis of hypoglycemia, it is challenging to quantify the incidence of hypoglycemia in older adults (>75 years) with diabetes. A lot of hypoglycemia episodes are not likely to be recorded since they are mild or even asymptomatic. The effectiveness of AID in treating hypoglycemia in older persons was examined in this study.
A randomized, multicenter crossover study was carried out on persons with type 1 diabetes who were 65 years of age or older. In a randomized sequence, participants used sensor-augmented pump insulin administration, predictive low-glucose suspend, and hybrid closed loop insulin delivery for three 12-week periods. The proportion of time with continuous glucose monitoring glucose levels below 70 mg/dl was the main result.
The study included a total of 82 randomly assigned patients aged 65 to 86 years, of whom 45% were female, had a baseline mean (±SD) glycated hemoglobin level of 7.2±0.9%, and a baseline percentage of time with glucose readings below 70 mg/dl of 2.49±1.78%.
The percentages of time with glucose below 70 mg/dl were 2.57±1.54%, 1.58±0.95%, and 1.67±0.96% in the hybrid closed-loop, sensor-augmented pump, and predictive low-glucose suspend periods, respectively. The mean difference of hybrid closed-loop system from the sensor-augmented pump results was −1.05 percentage points, while the predictive low-glucose suspend system's was −0.93 percentage points.
Time in the range of 70 to 180 mg/dl increased by 8.9 percentage points and the glycated hemoglobin level changed by 0.2 percentage points when compared to a hybrid closed-loop system with a sensor-augmented pump. Also, 2 hospitalizations for diabetic ketoacidosis were reported, while 4% or fewer of subjects experienced severe hypoglycemia. Overall, in older persons with type 1 diabetes, automated insulin administration was less likely to cause hypoglycemia than sensor-augmented pump delivery.
Source:
Kudva, Y. C., Henderson, R. J., Kanapka, L. G., Weinstock, R. S., Rickels, M. R., Pratley, R. E., Chaytor, N., Janess, K., Desjardins, D., Pattan, V., Peleckis, A. J., Casu, A., Rizvi, S. R., Bzdick, S., Whitaker, K. J., Jo Kamimoto, J. L., Miller, K., Kollman, C., & Beck, R. W. (2025). Automated Insulin Delivery in Older Adults with Type 1 Diabetes. In NEJM Evidence (Vol. 4, Issue 1). Massachusetts Medical Society. https://doi.org/10.1056/evidoa2400200
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Jacinthlyn Sylvia, a Neuroscience Master's graduate from Chennai has worked extensively in deciphering the neurobiology of cognition and motor control in aging. She also has spread-out exposure to Neurosurgery from her Bachelor’s. She is currently involved in active Neuro-Oncology research. She is an upcoming neuroscientist with a fiery passion for writing. Her news cover at Medical Dialogues feature recent discoveries and updates from the healthcare and biomedical research fields. She can be reached at editorial@medicaldialogues.in
Dr Kamal Kant Kohli-MBBS, DTCD- a chest specialist with more than 30 years of practice and a flair for writing clinical articles, Dr Kamal Kant Kohli joined Medical Dialogues as a Chief Editor of Medical News. Besides writing articles, as an editor, he proofreads and verifies all the medical content published on Medical Dialogues including those coming from journals, studies,medical conferences,guidelines etc. Email: drkohli@medicaldialogues.in. Contact no. 011-43720751