Closed-loop glucose monitoring -
Health Technology Assessment Committee Findings A systematic review and a series of network meta-analyses were conducted on the comparative clinical effectiveness of fingerprick glucose tests, continuous glucose monitors, flash glucose monitors, and hybrid insulin delivery systems for the management of insulin-dependent diabetes.
For children and adults with type 1 diabetes, no significant differences were found between glucose monitoring methods for HbA1c or number of hypoglycemic events requiring assistance. Due to limited evidence, no conclusions about efficacy could be drawn for type 2 diabetes and for type 1 diabetes in a pregnant population.
Some significant differences were found for time-in-range in both adults and children with type 1 diabetes. However, based on a systematic review of the validity of time-in-range, the literature to date suggests time-in-range should not be considered a validated surrogate for clinical outcomes and differences should be interpreted cautiously.
Patients found continuous glucose monitors to be an effective tool in managing their glucose levels. Benefits noted include increased comfort in not having to perform multiple fingerpricks a day, improvements in sleep, and increased confidence and reassurance to make informed life decisions such as vacation and exercise.
No de novo cost-effectiveness analysis was performed because no difference in HbA1C or number of hypoglycemic events requiring assistance was identified in the clinical effectiveness review. An economic analysis by Health Quality Ontario found continuous glucose monitors were not cost-effective compared to usual care i.
Budget impact analysis suggests cost outcomes are sensitive to size of the population eligible for public funding of glucose monitors, the costs of the glucose monitors, and the size of the predicted market share of each glucose monitoring technology. Reports Glucose Monitoring PDF, This loop between the pancreas and blood sugar isn't working correctly in people with diabetes.
Instead, people who have diabetes frequently must check their blood sugar and determine how much insulin medication to take. An insulin pump is a small, computerized device worn outside of the body that delivers insulin under the skin.
A hybrid closed loop insulin pump attempts to mimic the body's natural communication loop by linking with a secondary device called a continuous glucose monitor, or CGM, sensor and automatically adjusting some of the insulin delivered based on continually monitored blood sugar levels.
The term "hybrid" is used because it is not a full closed loop. Although the system can monitor blood sugars and adjust insulin based on the data, it needs to be adjusted manually when a person eats a meal or if there is a sudden rise in blood sugar.
It has been approved for use by people with Type 1 and Type 2 diabetes. In contrast to this, open loop insulin delivery systems rely on people checking blood sugars frequently often by pricking their finger multiple times daily and using that information to determine how much insulin to take.
Hybrid closed loop insulin pumps are exciting new tools that can significantly improve into the health and wellness of people living with diabetes. Talk with your health care professional about if a hybrid closed loop insulin pump is right for you. Omar El Kawkgi, M. Skip to main content.
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.
Mojitoring Closed-loop glucose monitoring. Gkucose Service acknowledges Muscle definition exercises for abs territories of Closed-loop glucose monitoring Nations around Gkucose. and is grateful glucosse carry out our work on these lands. We acknowledge the rights, interests, priorities, Closed-loop glucose monitoring concerns of all Indigenous Peoples - First Nations, Métis, and Inuit - respecting and acknowledging their distinct cultures, histories, rights, laws, and governments. More topics Health Technology Assessments. Glucose Monitoring. Health Technology Assessment Committee Recommendations As the current evidence suggests glucose monitoring technologies, including continuous glucose monitors, flash glucose monitors, and hybrid closed loop insulin delivery systems, provide no additional clinical benefits compared to fingerprick blood glucose tests but provide non-clinical benefits such as added comfort, convenience, and flexibility in diabetes management, HTAC recommends funding for flash glucose monitors, the most cost-effective option assessed.BMC Glucoxe volume 9Article number: Cite this article. Metrics details. Type 1 diabetes is one of glucoee most common endocrine problems in childhood and adolescence, and remains a Closed-loop glucose monitoring chronic disorder with increased morbidity and mortality, and reduced quality of life.
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Insulin delivery is modulated at intervals of 1 to 15 minutes, depending on interstitial glucose levels, in contrast to the pre-programmed insulin delivery that takes place during conventional insulin pump treatment.
The key component of the artificial pancreas is the control algorithm, which directs insulin delivery according to glucose levels while accounting for inherent measurement errors and kinetic delays.
Various algorithms have been developed [ 13 ], but two main categories are the most relevant: the proportional-integral-derivative control PID [ 1415 ] and the model-predictive control MPC [ 16 — 18 ]. PID algorithms adjust insulin delivery by considering deviations from a target glucose level proportional componentthe area under the curve between the measured and the target glucose level integral componentand the rate of change in the measured glucose levels derivative component [ 15 ].
MPC algorithms, by contrast, employ a mathematical model of human glucose regulation to link insulin delivery and glucose excursions as described in numerous theoretical, animal, and computer-simulation studies [ 1618 — 22 ].
Insulin delivery is calculated by minimizing the difference between forecasted glucose concentrations and the target glucose levels over a prediction window of 1. MPC algorithms can be regarded as proactive; they forecast glucose levels in anticipation of the glucose-lowering effect of administered insulin and of announced disturbances such as meals and physical activity.
PID algorithms, by contrast, can be considered reactive, as they respond to observed glucose levels and are less equipped to handle announced meals and patient-directed insulin boluses. The safety of control algorithms can be enhanced by a supervisory module, which constrains insulin delivery by limiting the maximum insulin rate or by suspending insulin delivery when glucose levels are low or decreasing rapidly [ 2324 ].
The MPC method is well suited to compensate for time delays associated with the subcutaneous route of insulin administration and interstitial glucose measurements.
Other algorithms have been tested clinically, such as fuzzy logic, which is developed from qualitative approximations of clinical judgment by diabetes practitioners [ 25 ], a combination of MPC and PID algorithms for insulin and glucagon delivery [ 19 ], or a PID with insulin feedback [ 26 ].
One of the objectives of the current research is to integrate existing control algorithms within increasingly sophisticated insulin pumps and continuous glucose monitors.
It is anticipated that the artificial pancreas will evolve with increasing technology sophistication and more comprehensive treatment objectives [ 27 ] Table 1. Early generations of the artificial pancreas are likely to provide benefits in terms of reduced incidence of hypoglycemia.
Benefits may be population-specific; for example, compliant, motivated subjects may benefit from a reduced risk of hypoglycemia whereas less compliant subjects, including adolescents, may benefit from reduced glucose levels.
Follow-up closed-loop applications may address hyperglycemia, postprandial control and other lifestyle changes, including exercise.
Meals and exercise can be 'announced' to the control algorithm, and prandial insulin boluses can be delivered in the conventional way simplifying closed-loop operation.
In a more challenging 'fully closed-loop' configuration, the control algorithm is not aware of meals and exercise, and delivers insulin solely based on sensor glucose levels. Glucagon coadministration can be used to counteract peripheral overinsulization following insulin boluses or delayed insulin absorption.
Apart from the low glucose suspend LGS approach described below, which has entered postmarketing stage, all other approaches are under investigation in controlled laboratory conditions with realistic plans to perform studies under free-living conditions.
Table 2 outlines the status and achievements of various closed-loop approaches. Hypoglycemia associated with low sensor-measured glucose levels sustained for 2 to 4 hours may lead to seizures [ 28 ]. The body's defensive mechanisms against hypoglycemia are impaired during the night in people with type 1 diabetes, who have lost the ability to release the appropriate counter-regulatory hormones [ 29 — 32 ].
The simplest approach to reduce severity of hypoglycemia is to interrupt insulin delivery. The LGS function was the first example of a commercial application of closed-loop insulin delivery. An insulin pump with an integrated continuous glucose monitoring CGM Paradigm ® Veo; Medtronic Diabetes, Northridge, CA, USA automatically suspends insulin delivery for up to 2 hours when hypoglycemia is detected and the hypoglycemia alarm is not acknowledged by the patient [ 33 ].
Patients may be unconscious during hypoglycemia, and their ability to respond to alarms is reduced. Thus, a considerable safety benefit may be obtained from the LGS function. However, concerns have been raised about the attendant hyperglycemia that can result, especially from false-positive hypoglycemia detection.
The hyperglycemia risk is not negligible, but thus far only mild rebound hyperglycemia and minimal ketonaemia have been reported after a temporary suspension of insulin administration [ 34 — 38 ]. The LGS function aims to reduce the severity of hypoglycemia, but does not prevent it, which was the objective of work by Buckingham et al.
This approach was investigated in adults in a clinical setting. Using a pump shut-off time of 90 minutes and a glucose threshold of 4.
This approach was then tested overnight in young people, in whom hypoglycemia was induced by gradually increasing the subcutaneous insulin delivery [ 40 ]. All these prediction algorithms used a minute prediction horizon to allow time for the pump suspension to be effective in lowering insulin levels once basal infusion was suspended.
Most severe hypoglycemic episodes occur during sleep between midnight and 8 am [ 41 ]. As overnight glucose control is not complicated by meals or physical activity, closed-loop could help prevent nocturnal hypoglycemia. This is a common clinical problem of great concern to parents and carers of children with type 1 diabetes [ 42 ].
Over the past 4 years, diabetes research at Cambridge University has focused on the development and testing of overnight closed-loop insulin delivery systems.
Clinical studies have been performed in children, adults and pregnant women [ 244344 ], evaluating various scenarios to reproduce real-life challenges for overnight glucose control, which could potentially predispose to nocturnal hypoglycemia, such as afternoon exercise or the consumption of alcohol.
Evening meals of different sizes and compositions were also tested. An MPC algorithm was used to determine basal insulin delivery according to sensor glucose readings, whereas prandial insulin boluses were administered based on the subjects' standard practice.
Most of those clinical studies adopted a randomized crossover design comparing closed-loop insulin delivery with the conventional insulin pump therapy. In these randomized crossover studies, the overnight closed-loop system significantly increased the percentage of time that plasma glucose levels were within a target range of 3.
The effectiveness of the closed-loop system was most pronounced after midnight, when the system became fully effective. Combined results of both young and adult patients after midnight during closed-loop and the conventional pump therapy are summarized in Figure 2.
Notably, these results indicate that the closed-loop system resulted in a significantly reduced time spent with glucose below the target range of 3. Distribution of plasma glucose levels after midnight in young people and adults during top panel closed-loop and bottom panel conventional insulin-pump therapy continuous subcutaneous insulin infusion CSII.
Vertical dashed lines indicate the threshold of significant hypoglycemia 3. Values at the top denote the percentage of plasma glucose values within the respective glucose ranges reproduced with permission from Kumareswaran et al.
Two main closed-loop approaches have been adopted in the clinical studies for prandial insulin delivery: 'fully closed-loop' and 'closed-loop with meal announcement' [ 9 ].
A fully closed-loop system delivers insulin without information about the size or time of meals, whereas information about meals together with information about manually administered prandial insulin boluses is provided to closed-loop systems adopting the 'meal announcement' approach.
In a hybrid system, the delivery of pre-meal insulin boluses remains one of the tasks for which patients are responsible, with the closed-loop system automatically determining the insulin delivery between meals [ 27 ].
The hybrid system with meal-time priming boluses has been shown to reduce postprandial hyperglycemia compared to a fully closed-loop system [ 45 ]. As delays in insulin absorption of the order of 30 to minutes are a major challenge for safe and effective postprandial glucose control, this hybrid approach may be considered a transition step from 'closed-loop with meal announcement'.
The feasibility and efficacy of MPC-based closed-loop insulin delivery was also recently demonstrated in women with type 1 diabetes throughout different stages of pregnancy [ 44 ].
Near-optimal nocturnal glycemic control was obtained with the closed-loop system both in early and late pregnancy, coping well with both the longitudinal changes in insulin requirements and the insulin sensitivity associated with pregnancy.
Studies of a well-controlled cohort of pregnant women suggested a reduced risk of very low glucose levels with closed-loop insulin delivery, but otherwise similar glucose control [ 46 ]. Glucagon coadministration has also been investigated with the fully closed-loop approach [ 4748 ].
: Closed-loop glucose monitoring| Hybrid closed loop technology (artificial pancreas) | JDRF | The trial registration number is NCT Article CAS Google Scholar Bally, L. These systems are developed by people in the diabetes community. For this, you need a blood glucose meter, your brain, and an insulin pen. UPDATE, 19 DECEMBER, NICE has published the final guidance and the appraisal has concluded, with plans now being agreed to begin rolling out the tech in J Diabetes Sci Technol. |
| NICE recommends hybrid closed loop systems for poorly controlled type 1 diabetes | Momitoring : Closed-loop glucose monitoring Green coffee detox The Closed-loop glucose monitoring endpoint, the proportion of moonitoring sensor glucose was in the target glucose range between monltoring. Recruitment was stopped early due to Brexit-related sponsorship issues that prevented the Switzerland site from recruiting any further participants after 31 Decemberand UK study personnel were working clinically in high-risk COVID environments that could have put study participants at increased risk. and R. Intern Med. |
| Closed-loop insulin delivery for treatment of type 1 diabetes | Nina Willer Living with type 1. Download references. Kidney Int. Munachiso Nwokolo ; Munachiso Nwokolo. McElwee Malloy. Fully automated closed-loop glucose control compared with standard insulin therapy in adults with type 2 diabetes requiring dialysis: an open-label, randomized crossover trial. |
| Powerful System | Fully Closed-Loop Glucose Control Compared With Insulin Pump Therapy With Continuous Glucose Monitoring in Adults With Type 1 Diabetes and Suboptimal Glycemic Control: A Single-Center, Randomized, Crossover Study Charlotte K. Boughton Corresponding author: Charlotte K. Boughton, cb medschl. This Site. Google Scholar. 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:. Get Permissions. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Graphical Abstract View large Download slide. View large Download slide. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. You do not currently have access to this content. View full article. 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. Pay-Per-View Access. Buy This Article. View Metrics. Email alerts Article Activity Alert. Online Ahead of Print Alert. Latest Issue Alert. Online ISSN Print ISSN You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. A Publisher Correction to this article was published on 16 September We evaluated the safety and efficacy of fully closed-loop insulin therapy compared with standard insulin therapy in adults with type 2 diabetes requiring dialysis. The primary endpoint was time in target glucose range 5. Thirteen participants received closed-loop first and thirteen received control therapy first. The proportion of time in target glucose range 5. Mean glucose was lower with closed-loop than control No severe hypoglycemia events occurred during the control period, whereas one severe hypoglycemic event occurred during the closed-loop period, but not during closed-loop operation. Fully closed-loop improved glucose control and reduced hypoglycemia compared with standard insulin therapy in adult outpatients with type 2 diabetes requiring dialysis. The trial registration number is NCT As the prevalence of type 2 diabetes increases, the number of people with diabetes and ESRD requiring renal replacement therapy is also rising 1. A scarcity of organs for transplantation as well as cardiovascular comorbidities associated with diabetes that preclude transplantation mean that hemodialysis or peritoneal dialysis are the only available treatment options for many. ESRD and dialysis itself increase the risk of hypoglycemia and hyperglycemia, which are associated with adverse outcomes 3 , 4 , 5. Management of diabetes in this population is challenging for both patients and healthcare professionals. Many aspects of diabetes care of patients on dialysis are poorly understood, including targets for glycemic control and treatment algorithms 6 , 7. Most oral diabetes medications are contraindicated in people with ESRD, so insulin is the most commonly used diabetes therapy. Optimal insulin dosing regimens are difficult to establish with the altered glucose and insulin metabolism associated with ESRD and dialysis 5 , and concerns regarding hypoglycemia often result in sub-optimal glycemic control. There is an unmet need for novel approaches to the safe and effective management of diabetes for people requiring dialysis. Closed-loop insulin delivery systems comprise a continuous glucose monitor, an insulin pump and a control algorithm that continuously and automatically modulates subcutaneous insulin delivery in response to real-time interstitial glucose concentrations 8. Closed-loop systems are increasingly being applied to the management of type 1 diabetes. However, use of this technology in people with type 2 diabetes has been limited to the inpatient setting including those on hemodialysis 9 , 10 , 11 , Safety and efficacy in outpatient settings, a precursor for wider clinical acceptance, is to be determined. In the present study, we address this issue and hypothesize that fully closed-loop insulin delivery may improve glycemic control compared to standard insulin therapy without increasing the risk of hypoglycemia in people with type 2 diabetes and ESRD undergoing maintenance dialysis in the outpatient setting. Baseline diabetes regimen details are shown in Supplementary Table 1. Thirteen participants were randomized to receive closed-loop first Extended Data Fig. Recruitment stopped early due to Brexit-related sponsorship issues and delays and constraints caused by COVID Methods. The flow of participants through the trial is shown in Fig. Of 27 randomized participants, one participant was withdrawn from the study post-randomization as they required hospital admission and died before the start of the first intervention period control. Two participants stopped a study period early, one during the second period control due to bereavement and one during the first period closed-loop due to local COVID restrictions. a , Overview of the participant flow. b , Baseline characteristics of the study participants. The primary endpoint, the proportion of time sensor glucose was in the target glucose range between 5. The time in range with closed-loop in period 1 was The time in range with standard insulin therapy in period 1 was Figure 2 shows the h sensor glucose profiles. a , Median and IQR of sensor glucose during the closed-loop period solid red line and pink shaded area and control period solid gray line and gray shaded area from midnight to midnight. The lower and upper limits of the glucose target range, 5. The standard deviation of glucose was lower during closed-loop than during the control period 3. Total daily insulin doses were similar between interventions. Closed-loop performance improved from days 1—7 to days 8—20, as shown by an increase in the time spent in the target glucose range by 8. There was no difference in key glycemic outcomes between days 1—7 and days 8—20 during the control period, but measures of glycemic variability increased during days 8—20 compared with days 1—7 inclusive Supplementary Table 2. Daily trend of the proportion of time when sensor glucose was in the target range between 5. Mean and s. are shown. There were no differences in any glycemic outcomes, including measures of variability between dialysis days and non-dialysis days during either intervention period Table 2. Closed-loop driven insulin delivery was lower on dialysis days than on non-dialysis days 0. There was no difference in the mean inter-dialytic weight gain between interventions closed-loop 1. The closed-loop algorithm glucose target was set at 7. The proportion of time spent in the target glucose range decreased as the glucose target setting increased Extended Data Fig. Six other serious adverse events were reported Table 3. Two of these occurred during the closed-loop period reduced responsiveness on dialysis requiring hospital admission and COVID infection requiring hospital admission , two events occurred during washout or pre-study start one hospital admission for bowel obstruction resulting in death and one hospital admission for diabetic foot-related cellulitis requiring intravenous antibiotics , and two events occurred during the control period one below-knee amputation due to diabetic foot ulceration, and one hospital admission with an ischemic stroke. None of the serious adverse events were deemed related to study devices or study procedures. Nine other adverse events were reported Table 3 , five of which occurred during closed-loop, two during the control period and two during washout or pre-study arm start. Three of these events were deemed related to study devices or study procedures two skin reactions from the infusion sets and one infusion set failure causing hyperglycemia. The hypoglycemia confidence score was higher with the closed-loop system than with standard insulin therapy 3. The PAID score in both periods of the study was low 7. Benefits of the closed-loop system reported by study participants included a reduced need for finger-prick glucose checks, less time required to manage diabetes, resulting in more personal time and freedom, and improved peace of mind and reassurance. Device burden and discomfort wearing the insulin pump and carrying the smartphone were the most common limitations reported by participants Supplementary Table 4. This study provides evidence that fully closed-loop insulin delivery can improve glucose control and reduce hypoglycemia compared to standard insulin therapy in adults with type 2 diabetes and ESRD requiring dialysis, in an unrestricted home setting. We have shown that the fully closed-loop system has the potential to safely and effectively manage glucose levels in one of the most vulnerable subpopulations with type 2 diabetes where the risk of glycemic complications and diabetes-related adverse events is greatest. Compared with control therapy, fully closed-loop insulin delivery was associated with over 3. This pattern of incremental improvements in time in range with increasing duration of wear time has been reported previously with this fully closed-loop system in the inpatient setting It is reasonable to postulate that time in target range could improve further with a longer duration of use. It has previously been reported that 26 days of closed-loop use are required for the proportion of time in target glucose range to plateau, although this is likely to be population-dependent 13 , A higher glucose target was applied in the present study median 7. Higher glucose target settings were associated with less time in target glucose range Extended Data Fig. However, time spent in hypoglycemia did not increase with lower personal glucose targets, suggesting that the glucose target does not need to be unnecessarily elevated. The reduction in time in hypoglycemia observed with closed-loop is clinically important in this highly vulnerable population with a high burden of comorbidities. Closed-loop was associated with very low time in hypoglycemia 0. Hypoglycemia exposure during the control period was also low, in contrast with the high frequency of hypoglycemia reported in other studies 15 , The greatest reductions in hypoglycemia with closed-loop were observed in participants with the highest levels of hypoglycemia during the standard insulin therapy period Fig. Hypoglycemia is a considerable barrier to optimization of insulin therapy. The risk of hypoglycemia is high in this population, and people on dialysis often have impaired awareness of hypoglycemia Hypoglycemia has been associated with an increased risk of all-cause mortality in those with diabetes on dialysis, but causation has not been established The improved time in target glucose range observed with closed-loop was predominantly due to the reduced time spent in hyperglycemia. This degree of hyperglycemia is associated with both acute and chronic complications. The closed-loop algorithm was able to manage fluctuations in glucose and insulin kinetics between dialysis and non-dialysis days effectively. There was no difference in glucose outcomes between dialysis and non-dialysis days, but closed-loop insulin delivery was lower on dialysis days than non-dialysis days, an effect that is probably related to the impact of the dialysate glucose concentration on blood glucose concentrations. Closed-loop insulin delivery was safe in this vulnerable population. No study-related serious adverse events occurred during the closed-loop intervention period, and the commonest study-related adverse events were self-limiting skin reactions. Closed-loop and sensor glucose usage were high in the study, supporting acceptability of this approach in this population. All study participants were happy to have glucose levels managed with an automated insulin delivery system and would recommend its use to others. Participants felt more confident in managing hypoglycemia with the closed-loop system, although this could be due to the availability of real-time glucose levels and alarms for hypoglycemia. Device burden was reported as the main perceived drawback to this approach. The strengths of this study include the multinational randomized crossover design, the fully closed-loop approach adopted and the unrestricted and unsupervised home setting, including dialysis sessions. Limitations include the smaller sample size than planned due to Brexit-related study sponsorship issues and the COVID pandemic. Device management was performed by the study team to minimize training burden and therefore we cannot comment on the competency of this population to self-manage this treatment modality. Diabetes therapies during the control period were not standardized or optimized during the trial. We did not evaluate the accuracy of the glucose sensor in the present study; however, because the same sensor was used during both study arms, we believe this is unlikely to have impacted the results. As this was an exploratory study, no adjustment was made for multiple comparisons in the statistical analysis. We included only one participant receiving peritoneal dialysis, thus limiting interpretation of efficacy and safety in this specific cohort. Our study evaluated the performance of a fully closed-loop system in an unrestricted outpatient setting in a highly vulnerable population with type 2 diabetes and end-stage renal failure requiring dialysis. Having demonstrated safety and efficacy in this at-risk population in this exploratory study, larger studies are now required to confirm these findings and to determine if the glycemic improvements observed with closed-loop are associated with a reduction in complications and improved quality of life, as well as whether closed-loop should be targeted towards specific subpopulations for example, those with high hypoglycemic burden or peri-transplant. We suggest that the fully closed-loop approach may also be beneficial in the wider population of people with type 2 diabetes, and further studies are warranted. Each intervention period lasted 20 days, separated by two to four weeks of washout using pre-study treatment. The order of the two interventions was random. Exclusion criteria included type 1 diabetes, pregnancy or breast-feeding, severe visual or hearing impairment and any physical or psychological disease, or the use of medication s likely to interfere with the conduct of the trial or interpretation of the results. Written informed consent was obtained from all participants prior to the start of study-related procedures. The study protocol was approved by the local research ethics committees London—Stanmore Ethics Committee, UK; Ethics Committee Bern, Switzerland and regulatory authorities MHRA and Swissmedic. The full trial protocol is available in the Supplementary Note. The safety aspects of the trial were overseen by an independent Data and Safety Monitoring Board. The study was registered 19 July with ClinicalTrials. gov NCT There were 25 protocol deviations during the study period, including seven COVIDrelated deviations delay to starting or premature finishing of a study period , seven home visits to replenish insulin supplies and 11 visits to replace infusion sets, sensors or batteries. Recruitment was stopped early due to Brexit-related sponsorship issues that prevented the Switzerland site from recruiting any further participants after 31 December , and UK study personnel were working clinically in high-risk COVID environments that could have put study participants at increased risk. Eligible participants were randomly assigned to either initial use of fully closed-loop glucose control with faster-acting insulin aspart for 20 days followed by standard multiple daily insulin injection therapy for 20 days, or vice versa. Randomization was done using a computer-generated sequence with a permuted block design block size 4 and stratified by center. Participants and investigators were not masked to the intervention being used during each period due to the nature of the interventions precluding the ability to mask. Participant demographics and medical history, body weight and height, glycated hemoglobin HbA1c and total daily insulin dose were recorded at enrollment. Body weight pre- and post-dialysis was recorded at each dialysis session or daily if on peritoneal dialysis as per usual clinical practice. All participants dialyzed with 5. Fingerstick capillary glucose measurements were performed by dialysis staff according to usual clinical practice. The CamAPS HX closed-loop app CamDiab resides on an unlocked Android phone, receives sensor glucose data from a Dexcom G6 transmitter Dexcom and uses the Cambridge adaptive model predictive control algorithm version 0. The nominal glucose target is 5. In the present study, given the vulnerable population, the glucose target was set at 7. Low glucose alarms were customized at a threshold to suit the participant. All other medications were continued. Closed-loop insulin delivery was continued for 20 days, including during dialysis sessions. Faster-acting insulin aspart Fiasp was delivered via the insulin pump throughout the closed-loop study period. Fiasp was used for its properties of faster onset and offset of action, and its potential to enhance closed-loop performance. No prandial insulin boluses were delivered and the control algorithm was not aware of timing or carbohydrate content of meals. Infusion sets were changed at each dialysis session by the study team. Participants were unrestricted in relation to their usual activity and dietary intake. The study did not interfere with or specify the medications prescribed by the local clinical team. All participants were provided with a h telephone helpline to contact the local study team in the event of study-related issues. Fingerstick capillary glucose measurements were performed by participants as per usual clinical practice. Glycemic management was performed by the clinical team according to local practice. A continuous glucose sensor, Dexcom G6 Dexcom , was inserted by the study team on the first day of the study arm. The continuous glucose monitor receiver was modified to mask the sensor glucose concentration to the participant and investigators. At the end of the standard insulin therapy period, the glucose sensor was removed. Participants were invited to complete the validated questionnaires at the end of each study period: the PAID questionnaire to assess diabetes distress, the Hypoglycaemia Confidence Survey to evaluate perceptions of ability to self-manage hypoglycemia and the Hypoglycaemia Fear Survey-II Worry Scale HFS-W to estimate hypoglycemia-related fear and anxiety Cambridge only 18 , 19 , Additionally, participants filled in a closed-loop experience questionnaire collecting feedback on satisfaction with closed-loop therapy, acceptance of wearing study devices and recommending closed-loop to others. Because previous studies using closed-loop in an inpatient setting may not provide reliable information about the standard deviation of the primary endpoint in this particular population outpatients receiving maintenance dialysis , no formal power calculation was applied. The sample size corresponds to the sample size of previous feasibility closed-loop randomized trials 9 , The primary endpoint was the percentage of time the sensor glucose measurement was in the target glucose range of 5. This target glucose range was selected in line with recommendations for less stringent glucose control in this population due to their high risk for hypoglycemia and related adverse events 5 , 6 , 21 , 22 , Other key endpoints are the percentage of time spent with sensor glucose above Secondary efficacy endpoints included time spent with sensor glucose below 5. Glucose variability was evaluated by the standard deviation and the coefficient of variation of sensor glucose utilizing data collected from the whole study period. The between-day coefficient of variation of sensor glucose was calculated from daily mean glucose values — Variability of glucose and insulin requirements between dialysis and non-dialysis days was assessed using the coefficient of variation of sensor glucose and insulin requirements between dialysis days — and non-dialysis days — Mean inter-dialytic weight gain was calculated for each study period. The statistical analysis plan was agreed by the investigators in advance. All analyses were carried out on an intention-to-treat basis. The respective values obtained during the day randomized interventions were compared. for normally distributed values or median interquartile range for non-normally distributed values. A two-sample t -test on paired differences was used to compare normally distributed variables 24 and the Mann—Whitney—Wilcoxon rank-sum test for data that are not normally distributed. No allowance was made for multiplicity. Outcomes were calculated using GStat software, version 2. All P values are two-tailed, and P values of less than 0. Further information on research design is available in the Nature Research Reporting Summary linked to this Article. The data that support the findings of this study are available from the corresponding author for the purposes of advancing the management and treatment of diabetes. All data shared will be de-identified. The study protocol is available with this paper. The control algorithm cannot be made publicly available because it is proprietary intellectual property. The control algorithm cannot be used in routine practice in the outpatient setting as regulatory approval has not yet been granted. Abe, M. Haemodialysis-induced hypoglycaemia and glycaemic disarrays. Article CAS Google Scholar. Copur, S. et al. Serum glycated albumin predicts all-cause mortality in dialysis patients with diabetes mellitus: meta-analysis and systematic review of a predictive biomarker. Acta Diabetol. Hill, C. Glycated hemoglobin and risk of death in diabetic patients treated with hemodialysis: a meta-analysis. Kidney Dis. Galindo, R. Glycemic monitoring and management in advanced chronic kidney disease. |
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