Sara Hartnell ; Sara Hartnell. Rama Lakshman ; Rama Lakshman. Munachiso Nwokolo ; Munachiso Nwokolo. Malgorzata E. Wilinska ; Malgorzata E. Julia Ware ; Julia Ware. Janet M. Allen ; Janet M. Mark L. Evans ; Mark L. Roman Hovorka Roman Hovorka. Diabetes Care ;46 11 — Article history Received:.

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Sign in Don't already have an account? Sign in via ADA Individual Sign In. Sign in via your Institution Sign in via your Institution. The t:slim X2 pump is indicated for use in individuals six years of age and greater.

Control-IQ technology: Control-IQ technology is intended for use with a compatible integrated continuous glucose monitor iCGM, sold separately and ACE pump to automatically increase, decrease, and suspend delivery of basal insulin based on iCGM readings and predicted glucose values.

It can also deliver correction boluses when the glucose value is predicted to exceed a predefined threshold. Control-IQ technology is intended for the management of Type 1 diabetes mellitus in persons six years of age and greater. Warning: Control-IQ technology should not be used by anyone under the age of six years old.

It should also not be used in patients who require less than 10 units of insulin per day or who weigh less than 55 pounds. Control-IQ technology is not indicated for use in pregnant women, people on dialysis, or critically ill patients.

Do not use Control-IQ technology if using hydroxyurea. The t:slim X2 pump, and the CGM transmitter and sensor must be removed before MRI, CT, or diathermy treatment.

Visit tandemdiabetes. Now Available: The impressively small Tandem Mobi system offers greater discretion and wearability. Order Today.

Home Support Diabetes Education. Managing Diabetes. Other Categories Type 1 Diabetes Type 2 Diabetes Managing Diabetes Nutrition Recipes View All Categories. By Tandem Cares Apr 22, What is a Closed-Loop System?

This translated into an interval between sensor calibrations of to and to minutes during the first and second 24 hours, respectively. Sensor performance was good, with the median absolute deviation of 0. Overall, sensor unavailability for the entire hour study period during closed-loop therapy was 25 0 to minutes.

This translated to 5. Excluding the mandatory first-hour sensor warm-up period, 3. This occurred mostly during the first 10 hours of sensor use. Two subjects required replacement of sensor because of MRI scanning.

We documented that automated closed-loop glucose control, based on continuous subcutaneous glucose levels, is feasible and may significantly improve glucose levels without increasing the risk of hypoglycemia in critically ill adults. Compared with local intravenous sliding-scale therapy, closed-loop therapy increased up to fourfold the time spent in the target glucose range and reduced the time spent at higher glucose levels.

Subjects treated with closed-loop therapy achieved consistent results, with a trend toward reduced glucose variability without requiring nurse interventions or decision making on insulin delivery. Reflecting the current practice recommendations for glucose control in the intensive care unit [ 33 , 34 ], we adopted a moderate glucose target of 6.

Based on our simulation work, we were confident of achieving a target between 6. Subjects in the local-treatment protocol were treated with an intravenous sliding-scale protocol intended to maintain glucose in a safe target range of 7 to 10 m M without increasing the risk of hypoglycemia.

We did not change the target range of the usual treatment for two reasons. First, we aimed to compare current local practice with a novel treatment; second, we could not guarantee patient safety by changing the target range of the sliding-scale protocol.

The mean glucose level achieved during closed-loop control was 7. Importantly, during the present study, closed-loop therapy achieved safe glucose levels without increasing the risk of hypoglycemia. Glucose variability, as measured by the standard deviation, tended to be lower during closed-loop without reaching statistical significance.

Because both hypoglycemia and glucose variability have been associated with adverse outcomes, beneficial effects, apart from glucose lowering, may be achieved with closed-loop therapy.

Since the introduction of intensive insulin therapy, different algorithms and control systems aiming at effective and safe glucose control have been proposed [ 19 ]. These can range from written guidelines [ 12 , 13 ] and protocols [ 37 — 40 ] to elementary [ 41 , 42 ] and advanced computerized algorithms [ 43 — 48 ].

We used an advanced computer algorithm belonging to the family of model predictive control. The control algorithm and calibration strategy was optimized on a validated computer simulation environment for the critically ill [ 31 ] before study commencement to ensure favorable outcomes.

Our study is the first randomized controlled trial to evaluate fully automated closed-loop glucose control based on subcutaneous continuous glucose monitoring in critically ill patients. However, this was a retrospective observational study and used the STG system Nikkiso, Tokyo, Japan , which relies on continuous intravenous glucose measurements drawing 2 ml of blood per hour and is expensive [ 51 ], limiting its prolonged and wider use.

We initialized the closed-loop system by using approximate body weight and a reference glucose level. The system did not require information about nutritional intake and was able to respond to rapid changes in caloric and carbohydrate intake, even though a minute lag exists between blood and Navigator sensor glucose levels [ 52 ].

We increased accuracy of the subcutaneous continuous glucose monitor by calibrating with arterial blood glucose at a frequency higher than recommended by the manufacturer. During the first 24 hours, calibration occurred on average every 2. This is comparable with the present nurse workload.

Benefits of subcutaneous glucose monitoring compared with intravenous measurements include reduced invasiveness, obviating the need for dedicated venous placement and a risk of contamination from dextrose or other medications that may interfere with glucose measurements.

The risk of infection and thrombosis is lower with the subcutaneous route. The subcutaneous sensor placement was not associated with any complications.

The strengths of our study include the randomized controlled study design, the use of hourly arterial blood glucose to assess outcomes, comparability of the patient groups, and comparable nutrition and treatment modalities. Study limitations include a small sample size, a single-center study design involving a subspecialized patient population, and short study duration, which limits generalizability but does not affect the main study outcomes.

The control achieved by using the sliding-scale protocol appears suboptimal and reflects the fear of hypoglycemia in the post-NICE-SUGAR era. Comparisons with other standard insulin-infusion protocols would be beneficial.

In conclusion, automated closed-loop therapy, based on subcutaneous continuous glucose measurements, is a safe and efficacious approach for glucose control in critically ill adults.

Larger and longer-duration studies are warranted to assess system performance. Apart from providing a tangible treatment option, closed-loop systems may contribute important insights into the ongoing debate about glucose targets by providing the means to achieve uniform and safe outcomes in comparability studies.

Closed-loop treatment provided safe, effective, and consistent glucose control without increasing the risk of hypoglycemia in a small group of patients over a hour period.

Nurse intervention is not required during closed-loop treatment, apart from calibrating a subcutaneous glucose monitor. Automated administration of dextrose augmented the ability of closed-loop treatment to avoid low glucose levels.

Kavanagh BP, McCowen KC: Clinical practice: glycemic control in the ICU. N Engl J Med. Article PubMed CAS Google Scholar. Krinsley JS: Understanding glycemic control in the critically ill: three domains are better than one.

Intensive Care Med. Article PubMed Google Scholar. Krinsley JS: Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients. Mayo Clin Proc. Bochicchio GV, Joshi M, Bochicchio KM, Pyle A, Johnson SB, Meyer W, Lumpkins K, Scalea TM: Early hyperglycemic control is important in critically injured trauma patients.

J Trauma. discussion, Bagshaw SM, Egi M, George C, Bellomo R, Australia New Zealand Intensive Care Society Database Management C: Early blood glucose control and mortality in critically ill patients in Australia.

Crit Care Med. NICE-SUGAR Study Investigators, Finfer S, Liu B, Chittock DR, Norton R, Myburgh JA, McArthur C, Mitchell I, Foster D, Dhingra V, Henderson WR, Ronco JJ, Bellomo R, Cook D, McDonald E, Dodek P, Hebert PC, Heyland DK, Robinson BG: Hypoglycemia and risk of death in critically ill patients.

Article Google Scholar. Hermanides J, Bosman RJ, Vriesendorp TM, Dotsch R, Rosendaal FR, Zandstra DF, Hoekstra JB, DeVries JH: Hypoglycemia is associated with intensive care unit mortality.

Egi M, Bellomo R, Stachowski E, French CJ, Hart G: Variability of blood glucose concentration and short-term mortality in critically ill patients. Krinsley JS: Glycemic variability: a strong independent predictor of mortality in critically ill patients.

Badawi O, Waite MD, Fuhrman SA, Zuckerman IH: Association between intensive care unit-acquired dysglycemia and in-hospital mortality. Dungan KM, Braithwaite SS, Preiser JC: Stress hyperglycaemia.

Article PubMed CAS PubMed Central Google Scholar. Van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R: Intensive insulin therapy in critically ill patients. Van den Berghe G, Wilmer A, Hermans G, Meersseman W, Wouters PJ, Milants I, Van Wijngaerden E, Bobbaers H, Bouillon R: Intensive insulin therapy in the medical ICU.

NICE-SUGAR Study Investigators, Finfer S, Chittock DR, Su SY, Blair D, Foster D, Dhingra V, Bellomo R, Cook D, Dodek P, Henderson WR, Hebert PC, Heritier S, Heyland DK, McArthur C, McDonald E, Mitchell I, Myburgh JA, Norton R, Potter J, Robinson BG, Ronco JJ: Intensive versus conventional glucose control in critically ill patients.

Preiser JC, Devos P, Ruiz-Santana S, Melot C, Annane D, Groeneveld J, Iapichino G, Leverve X, Nitenberg G, Singer P, Wernerman J, Joannidis M, Stecher A, Chiolero R: A prospective randomised multi-centre controlled trial on tight glucose control by intensive insulin therapy in adult intensive care units: The Glucontrol Study.

Griesdale DE, de Souza RJ, van Dam RM, Heyland DK, Cook DJ, Malhotra A, Dhaliwal R, Henderson WR, Chittock DR, Finfer S, Talmor D: Intensive insulin therapy and mortality among critically ill patients: a meta-analysis including NICE-SUGAR study data.

Article PubMed PubMed Central Google Scholar. Van den Berghe G: Intensive insulin therapy in the ICU: reconciling the evidence. Nature Rev Endocrinol. CAS Google Scholar. Van den Berghe G, Schetz M, Vlasselaers D, Hermans G, Wilmer A, Bouillon R, Mesotten D: Clinical review: intensive insulin therapy in critically ill patients: NICE-SUGAR or Leuven blood glucose target?.

J Clin Endocrinol Metab. Van Herpe T, De Moor B, Van den Berghe G: Towards closed-loop glycaemic control. Best Pract Res Clin Anaesthesiol. Aragon D: Evaluation of nursing work effort and perceptions about blood glucose testing in tight glycemic control.

Am J Crit Care. PubMed Google Scholar. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group, Tamborlane WV, Beck RW, Bode BW, Buckingham B, Chase HP, Clemons R, Fiallo-Scharer R, Fox LA, Gilliam LK, Hirsch IB, Huang ES, Kollman C, Kowalski AJ, Laffel L, Lawrence JM, Lee J, Mauras N, O'Grady M, Ruedy KJ, Tansey M, Tsalikian E, Weinzimer S, Wilson DM, Wolpert H, Wysocki T, Xing D: Continuous glucose monitoring and intensive treatment of type 1 diabetes.

Pickup JC, Freeman SC, Sutton AJ: Glycaemic control in type 1 diabetes during real time continuous glucose monitoring compared with self monitoring of blood glucose: meta-analysis of randomised controlled trials using individual patient data. Corstjens AM, Ligtenberg JJ, van der Horst IC, Spanjersberg R, Lind JS, Tulleken JE, Meertens JH, Zijlstra JG: Accuracy and feasibility of point-of-care and continuous blood glucose analysis in critically ill ICU patients.

Crit Care. Siegelaar SE, Barwari T, Hermanides J, Stooker W, van der Voort PH, DeVries JH: Accuracy and reliability of continuous glucose monitoring in the intensive care unit: a head-to-head comparison of two subcutaneous glucose sensors in cardiac surgery patients.

Diabetes Care. Holzinger U, Warszawska J, Kitzberger R, Herkner H, Metnitz PG, Madl C: Impact of shock requiring norepinephrine on the accuracy and reliability of subcutaneous continuous glucose monitoring.

Hovorka R: Closed-loop insulin delivery: from bench to clinical practice. Article CAS Google Scholar. Scott NW, McPherson GC, Ramsay CR, Campbell MK: The method of minimization for allocation to clinical trials.

a review. Control Clin Trials. htm ]. Geoffrey M, Brazg R, Richard W: FreeStyle Navigator Continuous Glucose Monitoring System with TRUstart algorithm, a 1-hour warm-up time. J Diabetes Sci Technol. Bequette B: A critical assessment of algorithms and challenges in the development of a closed-loop artificial pancreas.

Diabetes Technol Ther. Wilinska ME, Blaha J, Chassin LJ, Cordingley JJ, Dormand NC, Ellmerer M, Haluzik M, Plank J, Vlasselaers D, Wouters PJ, Hovorka R: Evaluating glycemic control algorithms by computer simulations.

Am J Physiol Endocrinol Metab. Qaseem A, Humphrey LL, Chou R, Snow V, Shekelle P, Clinical Guidelines Committee of the American College of P: Use of intensive insulin therapy for the management of glycemic control in hospitalized patients: a clinical practice guideline from the American College of Physicians.

Ann Intern Med. American Diabetes A: Standards of medical care in diabetes: Google Scholar. Jacobi J, Bircher N, Krinsley J, Agus M, Braithwaite SS, Deutschman C, Freire AX, Geehan D, Kohl B, Nasraway SA, Rigby M, Sands K, Schallom L, Taylor B, Umpierrez G, Mazuski J, Schunemann H: Guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients.

Siegelaar SE, Hermanides J, Oudemans-van Straaten HM, van der Voort PH, Bosman RJ, Zandstra DF, DeVries JH: Mean glucose during ICU admission is related to mortality by a U-shaped curve in surgical and medical patients: a retrospective cohort study. Critical Care. Balkin M, Mascioli C, Smith V, Alnachawati H, Mehrishi S, Saydain G, Slone H, Alessandrini J, Brown L: Achieving durable glucose control in the intensive care unit without hypoglycaemia: a new practical IV insulin protocol.

Diabetes Metab Res Rev. Goldberg PA, Siegel MD, Sherwin RS, Halickman JI, Lee M, Bailey VA, Lee SL, Dziura JD, Inzucchi SE: Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit. Kanji S, Singh A, Tierney M, Meggison H, McIntyre L, Hebert PC: Standardization of intravenous insulin therapy improves the efficiency and safety of blood glucose control in critically ill adults.

Chase JG, Shaw G, Le Compte A, Lonergan T, Willacy M, Wong XW, Lin J, Lotz T, Lee D, Hann C: Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change. Davidson PC, Steed RD, Bode BW: Glucommander: a computer-directed intravenous insulin system shown to be safe, simple, and effective in , h of operation.

Vogelzang M, Zijlstra F, Nijsten MW: Design and implementation of GRIP: a computerized glucose control system at a surgical intensive care unit. BMC Med Informat Decision Making.

Plank J, Blaha J, Cordingley J, Wilinska M, Chassin L, Morgan C, Squire S, Haluzik M, Kremen J, Svacina S, Toller W, Plasnik A, Ellmerer M, Hovorka R: Pieber T Multicentric, randomized, controlled trial to evaluate blood glucose control by the model predictive control algorithm versus routine glucose management protocols in intensive care unit patients.

Posted By. Recent Posts. Speaking of Health. Topics in this Post. Insulin pumps An insulin pump is a small, computerized device worn outside of the body that delivers insulin under the skin. Benefits Research has shown that hybrid closed loop insulin pumps provide many benefits for people living with diabetes, including: Reduced risk of low blood sugars Clinical trials have shown that hybrid closed loop insulin pumps reduce the risk of low blood sugar.

When used with a continuous glucose monitor, an insulin pump can turn itself off or adjust the amount of insulin that it's giving the person depending on the trend in the blood sugar.

If the pump starts to notice that blood sugar is trending downward, it'll turn itself off or reduce the insulin. This reduces the risk of having low blood sugar, which can be a detrimental event. Reduced disease burden One of the reasons why living with diabetes can be tiring is the number of decisions that need to be made each day.

How much insulin should you give yourself? How do you modify your insulin based on what you're going to eat? Will exercising longer affect your blood sugar? Should you inject insulin now or later?

An insulin pump is not going to answer all those questions or solve all problems, but it significantly reduces some of the decision-making needed. By automatically adjusting background or basal insulin for people with diabetes, it can reduce decision fatigue and improve quality of life.

It's also useful for people who have an unpredictable activity schedule or work hours, since it releases a constant flow of insulin into the body, preventing the effects on blood sugar that can occur when occasionally forgetting to inject a long-acting insulin shot.

Improved monitoring and response to trends All hybrid closed loop insulin pumps will monitor blood sugar trends over time. Many display the information on a mobile app that can be shared with family, friends and health care professionals. This information helps make treatment decisions and identify triggers to spikes or drops in blood sugar levels.

It also helps from a safety perspective, particularly in children with diabetes. People with either type 1 or type 2 diabetes can benefit from the use of an insulin pump with advanced hybrid closed-loop technology.

Read more about insulin pumps and how they can help with diabetes management. A closed-loop system combines a continuous glucose monitoring CGM sensor with an insulin pump to automate the delivery of insulin. If the blood sugar glucose is rising, the closed-loop system would work to recognize the change and increase insulin delivery.

Conversely, if blood sugar levels are falling the system would recognize the trend and reduce and suspend insulin delivery. This is called automated insulin dosing. Jordan Pinsker, Vice President and Medical Director at Tandem Diabetes Care.

An advanced hybrid closed-loop system combines a predictive algorithm with user control. This automatic insulin dosing is the predictive algorithm and insulin pump working in unison with CGM to help minimize the frequent decisions needed to manage type 1 diabetes.

Molly McElwee Malloy, Senior Medical Science Liaison Manager for Tandem Diabetes Care, has spent years working on clinical trials for predictive algorithms. McElwee Malloy, who is also living with type 1 diabetes, said the advancement of predictive algorithms and closed-loop systems have been game-changers for diabetes management.

McElwee Malloy. Using an advanced hybrid closed-loop system offers a number of benefits over other diabetes management methods. For example, an advanced hybrid closed-loop system can:. For example, before advanced hybrid closed-loop systems existed, a lot of planning went into exercise and eating.

These activities can now occur more spontaneously because the amount of time needed to prepare for them is greatly reduced. This additionally reduces the burden of management.

Badawi O, Waite MD, Fuhrman SA, Zuckerman IH: Association between intensive care unit-acquired dysglycemia and in-hospital mortality.

Dungan KM, Braithwaite SS, Preiser JC: Stress hyperglycaemia. Article PubMed CAS PubMed Central Google Scholar. Van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R: Intensive insulin therapy in critically ill patients.

Van den Berghe G, Wilmer A, Hermans G, Meersseman W, Wouters PJ, Milants I, Van Wijngaerden E, Bobbaers H, Bouillon R: Intensive insulin therapy in the medical ICU.

NICE-SUGAR Study Investigators, Finfer S, Chittock DR, Su SY, Blair D, Foster D, Dhingra V, Bellomo R, Cook D, Dodek P, Henderson WR, Hebert PC, Heritier S, Heyland DK, McArthur C, McDonald E, Mitchell I, Myburgh JA, Norton R, Potter J, Robinson BG, Ronco JJ: Intensive versus conventional glucose control in critically ill patients.

Preiser JC, Devos P, Ruiz-Santana S, Melot C, Annane D, Groeneveld J, Iapichino G, Leverve X, Nitenberg G, Singer P, Wernerman J, Joannidis M, Stecher A, Chiolero R: A prospective randomised multi-centre controlled trial on tight glucose control by intensive insulin therapy in adult intensive care units: The Glucontrol Study.

Griesdale DE, de Souza RJ, van Dam RM, Heyland DK, Cook DJ, Malhotra A, Dhaliwal R, Henderson WR, Chittock DR, Finfer S, Talmor D: Intensive insulin therapy and mortality among critically ill patients: a meta-analysis including NICE-SUGAR study data.

Article PubMed PubMed Central Google Scholar. Van den Berghe G: Intensive insulin therapy in the ICU: reconciling the evidence. Nature Rev Endocrinol. CAS Google Scholar. Van den Berghe G, Schetz M, Vlasselaers D, Hermans G, Wilmer A, Bouillon R, Mesotten D: Clinical review: intensive insulin therapy in critically ill patients: NICE-SUGAR or Leuven blood glucose target?.

J Clin Endocrinol Metab. Van Herpe T, De Moor B, Van den Berghe G: Towards closed-loop glycaemic control. Best Pract Res Clin Anaesthesiol. Aragon D: Evaluation of nursing work effort and perceptions about blood glucose testing in tight glycemic control.

Am J Crit Care. PubMed Google Scholar. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group, Tamborlane WV, Beck RW, Bode BW, Buckingham B, Chase HP, Clemons R, Fiallo-Scharer R, Fox LA, Gilliam LK, Hirsch IB, Huang ES, Kollman C, Kowalski AJ, Laffel L, Lawrence JM, Lee J, Mauras N, O'Grady M, Ruedy KJ, Tansey M, Tsalikian E, Weinzimer S, Wilson DM, Wolpert H, Wysocki T, Xing D: Continuous glucose monitoring and intensive treatment of type 1 diabetes.

Pickup JC, Freeman SC, Sutton AJ: Glycaemic control in type 1 diabetes during real time continuous glucose monitoring compared with self monitoring of blood glucose: meta-analysis of randomised controlled trials using individual patient data. Corstjens AM, Ligtenberg JJ, van der Horst IC, Spanjersberg R, Lind JS, Tulleken JE, Meertens JH, Zijlstra JG: Accuracy and feasibility of point-of-care and continuous blood glucose analysis in critically ill ICU patients.

Crit Care. Siegelaar SE, Barwari T, Hermanides J, Stooker W, van der Voort PH, DeVries JH: Accuracy and reliability of continuous glucose monitoring in the intensive care unit: a head-to-head comparison of two subcutaneous glucose sensors in cardiac surgery patients.

Diabetes Care. Holzinger U, Warszawska J, Kitzberger R, Herkner H, Metnitz PG, Madl C: Impact of shock requiring norepinephrine on the accuracy and reliability of subcutaneous continuous glucose monitoring. Hovorka R: Closed-loop insulin delivery: from bench to clinical practice.

Article CAS Google Scholar. Scott NW, McPherson GC, Ramsay CR, Campbell MK: The method of minimization for allocation to clinical trials. a review. Control Clin Trials.

htm ]. Geoffrey M, Brazg R, Richard W: FreeStyle Navigator Continuous Glucose Monitoring System with TRUstart algorithm, a 1-hour warm-up time. J Diabetes Sci Technol. Bequette B: A critical assessment of algorithms and challenges in the development of a closed-loop artificial pancreas.

Diabetes Technol Ther. Wilinska ME, Blaha J, Chassin LJ, Cordingley JJ, Dormand NC, Ellmerer M, Haluzik M, Plank J, Vlasselaers D, Wouters PJ, Hovorka R: Evaluating glycemic control algorithms by computer simulations. Am J Physiol Endocrinol Metab.

Qaseem A, Humphrey LL, Chou R, Snow V, Shekelle P, Clinical Guidelines Committee of the American College of P: Use of intensive insulin therapy for the management of glycemic control in hospitalized patients: a clinical practice guideline from the American College of Physicians. Ann Intern Med.

American Diabetes A: Standards of medical care in diabetes: Google Scholar. Jacobi J, Bircher N, Krinsley J, Agus M, Braithwaite SS, Deutschman C, Freire AX, Geehan D, Kohl B, Nasraway SA, Rigby M, Sands K, Schallom L, Taylor B, Umpierrez G, Mazuski J, Schunemann H: Guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients.

Siegelaar SE, Hermanides J, Oudemans-van Straaten HM, van der Voort PH, Bosman RJ, Zandstra DF, DeVries JH: Mean glucose during ICU admission is related to mortality by a U-shaped curve in surgical and medical patients: a retrospective cohort study. Critical Care.

Balkin M, Mascioli C, Smith V, Alnachawati H, Mehrishi S, Saydain G, Slone H, Alessandrini J, Brown L: Achieving durable glucose control in the intensive care unit without hypoglycaemia: a new practical IV insulin protocol.

Diabetes Metab Res Rev. Goldberg PA, Siegel MD, Sherwin RS, Halickman JI, Lee M, Bailey VA, Lee SL, Dziura JD, Inzucchi SE: Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit.

Kanji S, Singh A, Tierney M, Meggison H, McIntyre L, Hebert PC: Standardization of intravenous insulin therapy improves the efficiency and safety of blood glucose control in critically ill adults.

Chase JG, Shaw G, Le Compte A, Lonergan T, Willacy M, Wong XW, Lin J, Lotz T, Lee D, Hann C: Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change. Davidson PC, Steed RD, Bode BW: Glucommander: a computer-directed intravenous insulin system shown to be safe, simple, and effective in , h of operation.

Vogelzang M, Zijlstra F, Nijsten MW: Design and implementation of GRIP: a computerized glucose control system at a surgical intensive care unit. BMC Med Informat Decision Making. Plank J, Blaha J, Cordingley J, Wilinska M, Chassin L, Morgan C, Squire S, Haluzik M, Kremen J, Svacina S, Toller W, Plasnik A, Ellmerer M, Hovorka R: Pieber T Multicentric, randomized, controlled trial to evaluate blood glucose control by the model predictive control algorithm versus routine glucose management protocols in intensive care unit patients.

Pachler C, Plank J, Weinhandl H, Chassin LJ, Wilinska ME, Kulnik R, Kaufmann P, Smolle KH, Pilger E, Pieber TR, Ellmerer M, Hovorka R: Tight glycaemic control by an automated algorithm with time-variant sampling in medical ICU patients.

Blaha J, Kopecky P, Matias M, Hovorka R, Kunstyr J, Kotulak T, Lips M, Rubes D, Stritesky M, Lindner J, Semrad M, Haluzik M: Comparison of three protocols for tight glycemic control in cardiac surgery patients.

Cordingley J, Vlasselaers D, Dormand N, Wouters P, Squire S, Chassin L, Wilinska M, Morgan C, Hovorka R, Van den Berghe G: Intensive insulin therapy: enhanced Model Predictive Control algorithm versus standard care. Hovorka R, Kremen J, Blaha J, Matias M, Anderlova K, Bosanska L, Roubicek T, Wilinska ME, Chassin LJ, Svacina S, Haluzik M: Blood glucose control by a model predictive control algorithm with variable sampling rate versus a routine glucose management protocol in cardiac surgery patients: a randomized controlled trial.

Van Herpe T, Mesotten D, Wouters PJ, Herbots J, Voets E, Buyens J, De Moor B, Van den Berghe G: LOGIC-insulin algorithm-guided versus nurse-directed blood glucose control during critical illness: the LOGIC-1 single-center, randomized, controlled clinical trial.

Chee F, Fernando T, van Heerden PV: Closed-loop glucose control in critically ill patients using continuous glucose monitoring system CGMS in real time. IEEE Trans Inf Technol Biomed.

Yatabe T, Yamazaki R, Kitagawa H, Okabayashi T, Yamashita K, Hanazaki K, Yokoyama M: The evaluation of the ability of closed-loop glycemic control device to maintain the blood glucose concentration in intensive care unit patients. Okabayashi T, Kozuki A, Sumiyoshi T, Shima Y: Technical challenges and clinical outcomes of using a closed-loop glycemic control system in the hospital.

Garg SK, Voelmle M, Gottlieb PA: Time lag characterization of two continuous glucose monitoring systems. Diabetes Res Clin Pract. Download references. We are indebted to patients and family members for participating in and consenting to the study. We thank all staff at the Neurosciences Critical Care Unit NCCU at Addenbrooke's Hospital, Cambridge, UK.

We thank Drs Tonny Veenith and Ari Ercole for their help with participant recruitment. Abbott Diabetes Care provided technical support but did not play any role in clinical studies or data analysis.

Wellcome Trust-MRC Institute of Metabolic Science, Metabolic Research Laboratories, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK.

Neurosciences Critical Care Unit, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK. You can also search for this author in PubMed Google Scholar.

Correspondence to Roman Hovorka. LL, SWE, HT, KC, JMA, KK, MEW, MN, JM, and RB have no conflicts of interest. RH reports having received speaker honoraria from Minimed Medtronic, Lifescan, Eli Lilly, and Novo Nordisk, serving on advisory panel for Animas and Minimed Medtronic, receiving license fees from BBraun; and having served as a consultant to BBraun and Profil.

RH conceptualized the study, is the guarantor, and had full access to all the data in the study. RH, LL, RB, SWE, and MLE codesigned the study. LL, HT, SWE, KC, and JMA were responsible for patient screening and enrolment and informed consent.

LL, HT, KC, JMA, and KK provided patient care and contributed to acquisition of data. RH designed and implemented the algorithm. RH, MN, MEW, and JM developed and validated the closed-loop system including the conduct of simulation studies.

LL and MN carried out the data and statistical analyses. LL and RH drafted the manuscript. All authors critically revised the manuscript and approved the final version of the report. Reprints and permissions.

Leelarathna, L. et al. Feasibility of fully automated closed-loop glucose control using continuous subcutaneous glucose measurements in critical illness: a randomized controlled trial. Crit Care 17 , R Download citation. Received : 08 April Revised : 20 May Accepted : 24 July Published : 24 July Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Abstract Introduction Closed-loop CL systems modulate insulin delivery according to glucose levels without nurse input.

Results The time when glucose was in the target range was significantly increased during closed-loop therapy Conclusions Fully automated closed-loop control based on subcutaneous glucose measurements is feasible and may provide efficacious and hypoglycemia-free glucose control in critically ill adults.

Trial Registration ClinicalTrials. Introduction Abnormalities of glucose metabolism are common in critically ill patients [ 1 , 2 ] and are characterized by hyperglycemia [ 3 — 5 ], hypoglycemia [ 6 , 7 ], and increased glucose variability [ 8 , 9 ], each independently and additively associated with higher adjusted mortality rates [ 10 ].

Common study procedures Apart from glucose control, all other aspects of patient care, including nutritional management and treatment of hypoglycemia and hyperglycemia, were carried out according to local treatment protocols and were identical between treatment arms.

The study was terminated if the subject was moved out of NCCU for more than 2 hours. Automated closed-loop therapy Subjects randomized to closed-loop therapy were treated by using an automated closed-loop system comprising a FreeStyle Navigator subcutaneous continuous glucose-monitoring system Abbott Diabetes Care, Alameda, CA, USA , b a laptop computer running a model predictive control MPC algorithm, and c two Alaris CC Plus syringe pumps CareFusion, Basingstoke, UK Figure 1.

Figure 1. Components of the closed-loop glucose-control system. Full size image. Figure 2. User interface of the closed-loop system. Table 1 Local intravenous insulin titration protocol Full size table.