Nocturnal Glucose Control with an Artificial Pancreas at a Diabetes Camp

Phillip, Moshe; Battelino, Tadej; Atlas, Eran; Kordonouri, Olga; Bratina, Nataša; Miller, Shahar; Biester, Torben; Stefanija, Magdalena Avbelj; Muller, Ido; Nimri, Revital; Danne, Thomas

doi:10.1056/nejmoa1206881

Cited by 401 publications

(300 citation statements)

References 32 publications

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“…[40][41][42][43][44][45] The results from these investigations were summarized in a 2011 review of the artificial pancreas field, 46 pointing out the superiority of closed-loop control over insulin pump therapy in terms of (1) increased time within target glucose range, (2) reduced incidence of hypoglycemia, and (3) better overnight control. Subsequent studies confirmed these findings in outpatient setting, 47 at diabetes camps for children, 48 and at patients' homes. 49 The superior glucose control achieved by these trials suggests that when CGM information is processed appropriately by advanced algorithms, the clinical outcomes are better, even than those achieved by state-of-the art sensoraugmented insulin pump therapy.…”

Section: Utility Of Cgm Informationmentioning

confidence: 66%

Assessing Sensor Accuracy for Non-Adjunct Use of Continuous Glucose Monitoring

Kovatchev

Patek

Ortiz

et al. 2015

Diabetes Technology & Therapeutics

191

154

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Background: The level of continuous glucose monitoring (CGM) accuracy needed for insulin dosing using sensor values (i.e., the level of accuracy permitting non-adjunct CGM use) is a topic of ongoing debate. Assessment of this level in clinical experiments is virtually impossible because the magnitude of CGM errors cannot be manipulated and related prospectively to clinical outcomes. Materials and Methods: A combination of archival data (parallel CGM, insulin pump, self-monitoring of blood glucose [SMBG] records, and meals for 56 pump users with type 1 diabetes) and in silico experiments was used to ''replay'' real-life treatment scenarios and relate sensor error to glycemic outcomes. Nominal blood glucose (BG) traces were extracted using a mathematical model, yielding 2,082 BG segments each initiated by insulin bolus and confirmed by SMBG. These segments were replayed at seven sensor accuracy levels (mean absolute relative differences [MARDs] of 3-22%) testing six scenarios: insulin dosing using sensor values, threshold, and predictive alarms, each without or with considering CGM trend arrows. Results: In all six scenarios, the occurrence of hypoglycemia (frequency of BG levels £ 50 mg/dL and BG levels £ 39 mg/dL) increased with sensor error, displaying an abrupt slope change at MARD = 10%. Similarly, hyperglycemia (frequency of BG levels ‡ 250 mg/dL and BG levels ‡ 400 mg/dL) increased and displayed an abrupt slope change at MARD = 10%. When added to insulin dosing decisions, information from CGM trend arrows, threshold, and predictive alarms resulted in improvement in average glycemia by 1.86, 8.17, and 8.88 mg/dL, respectively. Conclusions: Using CGM for insulin dosing decisions is feasible below a certain level of sensor error, estimated in silico at MARD = 10%. In our experiments, further accuracy improvement did not contribute substantively to better glycemic outcomes.

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Section: Utility Of Cgm Informationmentioning

confidence: 66%

Assessing Sensor Accuracy for Non-Adjunct Use of Continuous Glucose Monitoring

Kovatchev

Patek

Ortiz

et al. 2015

Diabetes Technology & Therapeutics

191

154

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“…[12][13][14] This new study confirms the previous findings and adds two unique features: (1) a portable platform using a consumer electronics device (smartphone) to run the CLC system and all CGM, pump, and remote communications and (2) a control algorithm specifically designed to ''slide'' the patients' glucose levels to a target of 120 mg/dL at wakeup, thereby resetting their metabolic state overnight to near-normoglycemic morning BG levels, on consecutive nights. As a result, this study demonstrated not only significant improvement in overnight glucose control on CLC, but also significant improvement of patients' control on the next day.…”

Section: Discussionmentioning

confidence: 99%

“…9 The transition of CLC to a wearable outpatient system began in 2012 with the introduction of the Diabetes Assistant (DiAs)-the first wearable CLC system using a smartphone as a computational platform for its control algorithm. 10,11 Other recent trials confirmed the effectiveness of overnight CLC at diabetes camps for children 12 and at patients' homes, 13,14 placing laptop computers equipped with control algorithms at their patients' bedside.…”

mentioning

confidence: 90%

Multinight “Bedside” Closed-Loop Control for Patients with Type 1 Diabetes

BrownSue

KovatchevBoris²,

BretonMarc³

et al. 2015

Diabetes Technology & Therapeutics

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Background: Studies of closed-loop control (CLC) systems have improved glucose levels in patients with type 1 diabetes. In this study we test a new CLC concept aiming to ''reset'' the patient overnight to nearnormoglycemia each morning, for several consecutive nights. Subjects and Methods: Ten insulin pump users with type 1 diabetes (mean age, 46.4 -8.5 years) were enrolled in a two-center (in the United States and Italy) randomized crossover trial comparing 5 consecutive nights of CLC (23:00-07:00 h) in an outpatient setting versus sensor-augmented insulin pump therapy of the same duration at home. Primary end points included time spent in 80-140 mg/dL as measured by continuous glucose monitoring overnight and fasting blood glucose distribution at 7:00 h. Results: Compared with sensor-augmented pump therapy, CLC improved significantly time spent between 80 and 140 mg/dL (54.5% vs. 32.2%; P < 0.001) and between 70 and 180 mg/dL (85.4% vs. 59.1%; P < 0.001); CLC reduced the mean glucose level at 07:00 h (119.3 vs. 152.9 mg/dL; P < 0.001) and overnight mean glucose level (139.0 vs. 170.3 mg/dL; P < 0.001) using a marginally lower amount of insulin (6.1 vs. 6.8 units; P = 0.1). Tighter overnight control led to improved daytime control on the next day: the overnight/next-day control correlation was r = 0.52, P < 0.01. Conclusions: Multinight CLC of insulin delivery (artificial pancreas) results in significant improvement in morning and overnight glucose levels and time in target range, with the potential to improve daytime control when glucose levels were ''reset'' to near-normoglycemia each morning.

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“…Closed-loop insulin delivery systems have recently been demonstrated to be safe and efficient in summer camps [11] and free-living conditions [12][13][14][15][16]. Data on closed-loop insulin delivery during physical activity is scarce [17,18], particularly in children and adolescents.…”

Section: Introductionmentioning

confidence: 99%

Closed-loop glucose control in young people with type 1 diabetes during and after unannounced physical activity: a randomised controlled crossover trial

et al. 2017

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Aims/hypothesis Hypoglycaemia during and after exercise remains a challenge. The present study evaluated the safety and efficacy of closed-loop insulin delivery during unannounced (to the closed-loop algorithm) afternoon physical activity and during the following night in young people with type 1 diabetes. Methods A randomised, two-arm, open-label, in-hospital, crossover clinical trial was performed at a single site in Slovenia. The order was randomly determined using an automated web-based programme with randomly permuted blocks of four. Allocation assignment was not masked. Children and adolescents with type 1 diabetes who were experienced insulin pump users were eligible for the trial. During four separate in-hospital visits, the participants performed two unannounced exercise protocols: moderate intensity (55% of V Á O 2max ) and moderate intensity with integrated highintensity sprints (55/80% of V Á O 2max ), using the same study device either for closed-loop or open-loop insulin delivery. We investigated glycaemic control during the exercise period and the following night. The closed-loop insulin delivery was applied from 15:00 h on the day of the exercise to 13:00 h on the following day.Results Between 20 January and 16 June 2016, 20 eligible participants (9 female, mean age 14.2 ± 2.0 years, HbA 1c 7.7 ± 0.6% [60.0 ± 6.6 mmol/mol]) were included in the trial and performed all trial-mandated activities. The median proportion of time spent in hypoglycaemia below 3.3 mmol/l was 0.00% for both treatment modalities (p = 0.7910). Use of the closed-loop insulin delivery system increased the proportion of time spent within the target glucose range of 3.9-10 mmol/l when compared with open-loop delivery: 84.1% (interquartile range 70.0-85.5) vs 68.7% (59.0-77.7), respectively (p = 0.0057), over the entire study period. This was achieved with significantly less insulin delivered via the closed-loop (p = 0.0123). Conclusions/interpretation Closed-loop insulin delivery was safe both during and after unannounced exercise protocols in the in-hospital environment, maintaining glucose values mostly within the target range without an increased risk of hypoglycaemia.Trial registration Clinicaltrials.gov NCT02657083 Funding

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Nocturnal Glucose Control with an Artificial Pancreas at a Diabetes Camp

Abstract: Patients at a diabetes camp who were treated with an artificial-pancreas system had less nocturnal hypoglycemia and tighter glucose control than when they were treated with a sensor-augmented insulin pump. (Funded by Sanofi and others; ClinicalTrials.gov number, NCT01238406.).

Cited by 401 publications

References 32 publications

Assessing Sensor Accuracy for Non-Adjunct Use of Continuous Glucose Monitoring

Assessing Sensor Accuracy for Non-Adjunct Use of Continuous Glucose Monitoring

Multinight “Bedside” Closed-Loop Control for Patients with Type 1 Diabetes

Closed-loop glucose control in young people with type 1 diabetes during and after unannounced physical activity: a randomised controlled crossover trial

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