Real-world outcomes of two different sensor-augmented insulin pumps with predictive low glucose suspend function in type 1 diabetes patients

Published:October 12, 2021DOI:https://doi.org/10.1016/j.diabres.2021.109093

      Highlights

      • Medtronic 640G and Tandem T Slim X2 with PLGS improve diabetes control in people living with T1D.
      • Up to the moment, there has not been performed a direct comparison between these two systems.
      • In the present study we demonstrate similar real-world clinical benefits of both devices.

      Abstract

      Aim

      To analyse the real-life outcomes of two sensor-augmented pumps (SAP) with predictive low glucose suspend (PLGS) function, Medtronic Minimed 640G™ with SmartGuard (MM640G) and Tandem T Slim X2™ with Basal-IQ™ (TTSX2), in Type 1 Diabetes Mellitus (T1DM) patients.

      Methods

      Observational cross-sectional study using data obtained from computerized clinical records. All T1DM patients on TTSX2 therapy were compared (1:1) with MM640G treated patients selected through stratified sampling. Primary efficacy outcome was to describe time in rage (TIR, 70–180 mg/dL, 3.9–10 mmol/L) interstitial glucose differences according to a non-inferiority hypothesis with TTSX2 compared to MM640G.

      Results

      Forty-four patients were analyzed (female 66%). Mean age was 38.9 yrs. (range 23–59 yrs.) and mean diabetes duration was 23.4 ± 9.2 yrs. Patients treated with TTSX2 showed a numerically slightly lower, but non-statistically significantly different, TIR from the MM640G pump group (64.9 ± 16.4% vs. 72.4 ± 17.0%, P = 0.108). Similarly, we did no find differences in HbA1c between T1D patients treated with TTSX2 and MM640G (6.8 ± 1.0% vs. 7.0 ± 0.9%, 51 ± 11 mmol/mol vs. 53 ± 10 mmol/mol, P = 0.312). Moreover, rest of evaluated glycemic outcomes were similar between both treatment groups.

      Conclusions

      Patients using two different SAP with PLGS automatic function showed similar glycaemic control in a real-world scenario. NCT04741685.

      Keywords

      Abbreviations:

      CGM (continuous glucose monitoring), CV (coefficient of variation), CONGA (continuous overall net glycemic action), CSII (continuous subcutaneous insulin infusion), DKA (diabetic ketoacidosis), DQOL (diabetes quality of life), EsDQOL (diabetes quality of life questionnaire, Spanish version), EsHFS (hypoglycemia fear survey, Spanish version), GMI (glucose management indicator, GRADE: glycemia risk assessment diabetes equation), HbA1c (glycated haemoglobin A1c), MAGE (mean amplitude of glucose excursion), MIG (mean interstitial glucose), MODD (mean of daily differences), M100 (weighted average of glucose values at 100 mg/dL), PLGS (predictive low glucose suspend), RT-CGM (real-time continuous glucose monitoring), SAP (sensor augmented pump), SD (standard deviation), SMBG (self-monitoring of blood glucose), TAR (time above range), TBR (time bellow range), TIR (time in range), T1D (type 1 diabetes)
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      References

      1. Diabetes Control and Complications Trial Research Group, Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O, et al. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep 30;329(14):977–86.

        • Lachin J.M.
        • Genuth S.
        • Nathan D.M.
        • Zinman B.
        • Rutledge B.N.
        DCCT/EDIC Research Group. Effect of glycemic exposure on the risk of microvascular complications in the diabetes control and complications trial–revisited.
        Diabetes. 2008; 57: 995-1001
      2. Writing Group for the DCCT/EDIC Research Group, Orchard TJ, Nathan DM, Zinman B, Cleary P, Brillon D, et al. Association between 7 years of intensive treatment of type 1 diabetes and long-term mortality. JAMA. 2015 Jan 6;313(1):45–53.

      3. Gubitosi-Klug RA, Braffett BH, White NH, Sherwin RS, Service FJ, Lachin JM, et al. Risk of Severe Hypoglycemia in Type 1 Diabetes Over 30 Years of Follow-up in the DCCT/EDIC Study. Diabetes Care. 2017 Aug;40(8):1010–6.

      4. Raccah D, Sulmont V, Reznik Y, Guerci B, Renard E, Hanaire H, et al. Incremental value of continuous glucose monitoring when starting pump therapy in patients with poorly controlled type 1 diabetes: the RealTrend study. Diabetes Care. 2009 Dec;32(12):2245–50.

        • Bergenstal R.M.
        • Tamborlane W.V.
        • Ahmann A.
        • Buse J.B.
        • Dailey G.
        • Davis S.N.
        • et al.
        Effectiveness of sensor-augmented insulin-pump therapy in type 1 diabetes.
        N Engl J Med. 2010; 363: 311-320
        • Hermanides J.
        • Nørgaard K.
        • Bruttomesso D.
        • Mathieu C.
        • Frid A.
        • Dayan C.M.
        • et al.
        Sensor-augmented pump therapy lowers HbA(1c) in suboptimally controlled Type 1 diabetes; a randomized controlled trial.
        Diabet Med J Br Diabet Assoc. 2011 Oct; 28: 1158-1167
        • Battelino T.
        • Conget I.
        • Olsen B.
        • Schütz-Fuhrmann I.
        • Hommel E.
        • Hoogma R.
        • et al.
        The use and efficacy of continuous glucose monitoring in type 1 diabetes treated with insulin pump therapy: a randomised controlled trial.
        Diabetologia. 2012; 55: 3155-3162
        • Bergenstal R.M.
        • Klonoff D.C.
        • Garg S.K.
        • Bode B.W.
        • Meredith M.
        • Slover R.H.
        • et al.
        Threshold-based insulin-pump interruption for reduction of hypoglycemia.
        N Engl J Med. 2013; 369: 224-232
        • Ly T.T.
        • Nicholas J.A.
        • Retterath A.
        • Lim E.M.
        • Davis E.A.
        • Jones T.W.
        Effect of sensor-augmented insulin pump therapy and automated insulin suspension vs standard insulin pump therapy on hypoglycemia in patients with type 1 diabetes: a randomized clinical trial.
        JAMA. 2013 Sep 25; 310: 1240-1247
        • Garg S.
        • Brazg R.L.
        • Bailey T.S.
        • Buckingham B.A.
        • Slover R.H.
        • Klonoff D.C.
        • et al.
        Reduction in duration of hypoglycemia by automatic suspension of insulin delivery: the in-clinic ASPIRE study.
        Diabetes Technol Ther. 2012; 14: 205-209
        • Bosi E.
        • Choudhary P.
        • de Valk H.W.
        • Lablanche S.
        • Castañeda J.
        • de Portu S.
        • et al.
        Efficacy and safety of suspend-before-low insulin pump technology in hypoglycaemia-prone adults with type 1 diabetes (SMILE): an open-label randomised controlled trial.
        Lancet Diabetes Endocrinol. 2019 Jun; 7: 462-472
        • Abraham M.B.
        • Nicholas J.A.
        • Smith G.J.
        • Fairchild J.M.
        • King B.R.
        • Ambler G.R.
        • et al.
        Reduction in Hypoglycemia With the Predictive Low-Glucose Management System: A Long-term Randomized Controlled Trial in Adolescents With Type 1 Diabetes.
        Diabetes Care. 2018 Feb; 41: 303-310
        • Beato-Víbora P.I.
        • Quirós-López C.
        • Lázaro-Martín L.
        • Martín-Frías M.
        • Barrio-Castellanos R.
        • Gil-Poch E.
        • et al.
        Impact of Sensor-Augmented Pump Therapy with Predictive Low-Glucose Suspend Function on Glycemic Control and Patient Satisfaction in Adults and Children with Type 1 Diabetes.
        Diabetes Technol Ther. 2018; 20: 738-743
        • Katayama A.
        • Tone A.
        • Watanabe M.
        • Teshigawara S.
        • Miyamoto S.
        • Eguchi J.
        • et al.
        The hypoglycemia-prevention effect of sensor-augmented pump therapy with predictive low glucose management in Japanese patients with type 1 diabetes mellitus: a short-term study.
        Diabetol Int. 2020; 11: 97-104
        • Choudhary P.
        • de Portu S.
        • Arrieta A.
        • Castañeda J.
        • Campbell F.M.
        Use of sensor-integrated pump therapy to reduce hypoglycaemia in people with Type 1 diabetes: a real-world study in the UK.
        Diabet Med J Br Diabet Assoc. 2019 Sep; 36: 1100-1108
        • Gómez A.M.
        • Henao D.C.
        • Imitola A.
        • Muñoz O.M.
        • Sepúlveda M.A.R.
        • Kattah L.
        • et al.
        Efficacy and safety of sensor-augmented pump therapy (SAPT) with predictive low-glucose management in patients diagnosed with type 1 diabetes mellitus previously treated with SAPT and low glucose suspend.
        Endocrinol Diabetes Nutr. 2018; 65: 451-457
        • Forlenza G.P.
        • Li Z.
        • Buckingham B.A.
        • Pinsker J.E.
        • Cengiz E.
        • Wadwa R.P.
        • et al.
        Predictive Low-Glucose Suspend Reduces Hypoglycemia in Adults, Adolescents, and Children With Type 1 Diabetes in an At-Home Randomized Crossover Study: Results of the PROLOG Trial.
        Diabetes Care. 2018; 41: 2155-2161
        • Müller L.
        • Habif S.
        • Leas S.
        • Aronoff-Spencer E.
        Reducing Hypoglycemia in the Real World: A Retrospective Analysis of Predictive Low-Glucose Suspend Technology in an Ambulatory Insulin-Dependent Cohort.
        Diabetes Technol Ther. 2019; 21: 478-484
        • Pinsker J.E.
        • Leas S.
        • Müller L.
        • Habif S.
        Real world improvements in hypoglycemia in an insulin-dependent cohort with diabetes mellitus pre/post tandem basal-iq technology remote software update.
        Endocr Pract Off J Am Coll Endocrinol Am Assoc Clin Endocrinol. 2020; 26: 714-721
        • Beck R.W.
        • Bergenstal R.M.
        • Cheng P.
        • Kollman C.
        • Carlson A.L.
        • Johnson M.L.
        • et al.
        The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c.
        J Diabetes Sci Technol. 2019; 13: 614-626
        • Millan M.
        Quality-of-life questionnaire designed for diabetes mellitus (EsDQOL).
        Aten Primaria. 2002 May 15; 29: 517-521
        • Tasende C.
        • Rubio J.A.
        • Álvarez J.
        Spanish translation, adaptation and validation of the Hypoglycemia Fear Survey in adults with type 1 diabetes in the Community of Madrid.
        Endocrinol Diabetes Nutr. 2018; 65: 287-296
        • Czerwoniuk D.
        • Fendler W.
        • Walenciak L.
        • Mlynarski W.
        GlyCulator: a glycemic variability calculation tool for continuous glucose monitoring data.
        J Diabetes Sci Technol. 2011; 5: 447-451