Multiple Daily Injection Therapy Research Articles

Continuous subcutaneous insulin infusion versus multiple daily injection therapy in pregnant women with type 1 diabetes.

The study aimed to compare glycemic control and pregnancy outcomes in women with type 1 diabetes mellitus (T1DM) using multiple daily injection therapy (MDI) and continuous subcutaneous insulin infusion (CSII) and to compare outcomes of women treated with long-acting insulin or neutral protamine Hagedorn (NPH). This multicenter prospective cohort study involved women with pregestational T1DM treated with MDI and CSII. Primary outcome was glycated hemoglobin (HbA1c) before and during pregnancy. Secondary outcomes included maternal and neonatal outcomes and quality of life. Of the 121 studied women, the average age was 28.48 years, and the average body mass index was 21.29 kg/m2 at conception and 26.32 kg/m2 at delivery. Of the studied women, 78.51% had planned pregnancy. Women treated with MDI and CSII had comparable HbA1c before pregnancy or in the first and second trimesters. In the third trimester, women on CSII therapy had significantly lower HbA1c (6.07 ± 0.62 vs 6.20 ± 0.88%, p = .017), higher HbA1c on-target rate (71.43% vs 64.62%, p = .030), and greater decline of HbA1c from preconception to the third trimester (-0.65 vs -0.30%, p = .047). Fewer daily insulin requirements were observed in those used CSII compared with MDI-treated women (0.60 ± 0.22 vs 0.73 ± 0.25 U/kg/day, p = .004). Newborns born of mothers treated with the CSII method were more likely to have neonatal jaundice (adjusted odds ratio [OR] 2.76, 95% confidence interval [CI] 1.16-6.57) and neonatal intensive care unit (adjusted OR 3.73, 95%CI 1.24-11.16), and women on CSII had lower scores in patient-reported quality of life (p = .045). In the MDI group, those receiving long-acting insulin had nonsignificant lower HbA1c and higher HbA1c on-target rate in the second and third trimesters, compared with those treated with NPH. Insulin pump users may achieve better glycemic control than multiple daily insulin injections, which did not substantially improve pregnancy outcome.

Predictive value of postprandial C-peptide for utilizing multiple daily injection therapy in type 2 diabetes.

Multiple daily injection (MDI) insulin therapy is an effective method of glycemic control and appropriate assignment to MDI therapy could minimize the risks of hypoglycemia and weight gain. The aim of the present study was to identify factors associated with indication for MDI therapy in type 2 diabetes (T2DM). We recruited 360 participants with T2DM that were admitted to the Endocrinology Department of Peking University People's Hospital between August 2017 and July 2018. They first underwent intensive insulin therapy, then were switched to an optimized, simpler insulin treatment that aimed to maintain fasting blood glucose between 4.4 and 7.2 mmol/L, without episodes of hypoglycemia. The baseline characteristics of groups administering either MDI or basal/premix insulin were compared and multivariable logistic regression analysis was used to determine the odds ratios (ORs) for factors associated with MDI therapy. Receiver operating characteristic (ROC) curves were then used to identify independent predictors of MDI insulin regimen efficacy. The mean age of the participants was 57.6 ± 12.9 years, and diabetes duration was 14.2 ± 8.2 years. Two hundred and sixty-seven participants administered basal/premix insulin and 93 underwent MDI therapy, of whom 61.8% and 46.2% were male, respectively (p = 0.01). The duration of diabetes was significantly longer in the MDI group (13.1 ± 7.7 years vs. 17.3 ± 8.7 years; p < 0.01). Fasting plasma glucose (FPG) was higher in the MDI group than in the basal/premix group (8.3 [6.7, 11.3] mmol/L vs. 7.2 [5.7, 9.3] mmol/L; p < 0.01), while the postprandial C-peptide concentration (PCP) was significantly lower in the MDI group (2.6 [1.8, 3.5] ng/mL) compared to the basal/premix group (3.6 [2.5, 6.2] ng/mL, p < 0.01. Multivariable logistic regression analysis suggested that diabetes duration and FPG were positively associated with MDI therapy: OR (95% confidence interval [CI]) 1.06 (1.02, 1.10) and 1.12 (1.02, 1.24), respectively. In addition, PCP was negatively associated with MDI therapy (0.72 [0.60, 0.86]). ROC analysis suggested that a PCP of < 3.1 ng/mL predicted MDI therapy with 59.6% sensitivity and 72.1% specificity. The results of our study suggest that longer diabetes duration, higher FPG, and lower PCP were associated with necessity for MDI insulin regimen. These findings should assist with the personalization of insulin treatment.

A Relationship Between Human Microbiota and Diabetes and Effective Strategies Influencing the Features of Gut Microbiota

: The human body provides an environment in which trillions of microorganisms called “microbiome” exist. The diversity, composition, and function of these organisms depend on their body sites. The gut microbiota, a dense microbial community in the gastrointestinal (GI) tract, is thought to contain 100 times more genes than the human genome. Therefore, there should be a significant bidirectional relationship between gut microbiota and the human body. Normal gut microbiota performs several functions, keeping our body in a balanced situation, including immune system training, well-digesting nutrients, modulating the gut barrier, and producing essential molecules, such as neurotransmitters, hormones, and vitamins. Diabetes mellitus, a growing crisis, has involved many individuals in different age groups all around the world and has been significantly affected by these GI inhabitants' dysbiosis. Since some determining factors causing changes in the profile of gut microbiota are prebiotics, probiotics, and synbiotics, there have been considered a novel strategy for balancing these microorganisms and yet preventing metabolic diseases, one of which is diabetes. Scrutinizing the pathophysiology of diabetes mellitus, old methods of treating diabetes, such as acarbose, repaglinide, insulin pump therapy (IPT), and multiple daily injections (MDI) therapy, have been studied and optimized to be patient-based, resulting in a better yet effective treatment. In this review, key elements affecting the profile of gut microbiota, the etiology of diabetes, and the connection between human microbiota and diabetes, different indications of old and new strategies, and a few clinical types of research on changes occurring in diabetic patients in comparison to non-diabetic individuals have been elucidated.

A Three-Arm Randomized Controlled Study Comparing Patient-Reported Outcomes in People With Type 1 Diabetes Using Continuous Subcutaneous Insulin Infusion or Multiple Daily Injections.

The aim of this study was to compare patient-reported outcomes (PROs) in people with type 1 diabetes using either continuous subcutaneous insulin infusion (CSII) with two different insulin patch pumps or multiple daily injections (MDIs). In this randomized three-arm study, people with type 1 diabetes on MDI therapy were included and used either MDI, the Accu-Chek Solo micropump system (Solo) or Omnipod for 26 weeks. From weeks 26 to 39, all participants used CSII with Solo. Patient-reported outcomes were assessed using the diabetes technology questionnaire (DTQ); in addition, HbA1c values were measured. Overall, 181 participants were randomized (61 MDI arm, 62 Solo arm, 58 Omnipod arm) and 142 completed the study. After 26 weeks in the study, the DTQ "change" score in the Solo group (105.9 [100.6-111.2]; baseline-adjusted mean [95% confidence interval]) was significantly higher than in the MDI group (94.8 [89.6-100.0]) (P = .001). The comparison between the Solo group (105.1 [99.1-111.1]) and the Omnipod group (108.7 [103.1-114.4]) showed no significant differences (P = .382). HbA1c increased by 0.2% ± 0.7% in the MDI group and decreased in both pump groups (Solo group -0.2% ± 0.8% and Omnipod group -0.1% ± 0.8%). Differences in HbA1c between the Solo group and the MDI group were significant (P = .009), but not between the Solo group and the Omnipod group (P = .896). This study showed that switching from MDI to CSII improves both psychosocial well-being and physiological outcomes. Furthermore, there were no substantial differences between the established and the recently released patch pump. Trial registration at www.clinicaltrials.gov is NCT03478969.

Safety and Feasibility Evaluation of Automated User Profile Settings Initialization and Adaptation With Control-IQ Technology.

Optimization of automated insulin delivery (AID) settings is required to achieve desirable glycemic outcomes. We evaluated safety and efficacy of a computerized system to initialize and adjust insulin delivery settings for the t:slim X2 insulin pump with Control-IQ technology in adults with type 1 diabetes (T1D). After a 2-week continuous glucose monitoring (CGM) run-in period, adults with T1D using multiple daily injections (MDI) (N = 33, mean age 36.1 years, 57.6% female, diabetes duration 19.7 years) were transitioned to 13 weeks of Control-IQ technology usage. A computerized algorithm generated recommendations for initial pump settings (basal rate, insulin-to-carbohydrate ratio, and correction factor) and weekly follow-up settings to optimize glycemic outcomes. Physicians could override the automated settings changes for safety concerns. Time in range 70 to 180 mg/dL improved from 45.7% during run-in to 69.1% during the last 30 days of Control-IQ use, a median improvement of 18.8% (95% confidence interval [CI]: 13.6-23.9, P < .001). This improvement was evident early in the study and was sustained over 13 weeks. Time <70 mg/dL showed a gradual decreasing trend over time. Percentage of participants achieving HbA1c <7% went from zero at baseline to 55% at study end (P < .001). Only six of the 318 automated settings adaptations (1.9%) were overridden by study investigators. Computerized initiation and adaptation of Control-IQ technology settings from baseline MDI therapy was safe in adults with T1D. The use of this simplified system for onboarding and optimizing Control-IQ technology may be useful to increase uptake of AID and reduce staff and patient burden in clinical care.

Advanced decision support system for individuals with diabetes on multiple daily injections therapy using reinforcement learning and nearest-neighbors: In-silico and clinical results

Many individuals with diabetes on multiple daily insulin injections therapy use carbohydrate ratios (CRs) and correction factors (CFs) to determine mealtime and correction insulin boluses. The CRs and CFs vary over time due to physiological changes in individuals' response to insulin. Errors in insulin dosing can lead to life-threatening abnormal glucose levels, increasing the risk of retinopathy, neuropathy, and nephropathy. Here, we present a novel learning algorithm that uses Q-learning to track optimal CRs and uses nearest-neighbors based Q-learning to track optimal CFs. The learning algorithm was compared with the run-to-run algorithm A and the run-to-run algorithm B, both proposed in the literature, over an 8-week period using a validated simulator with a realistic scenario created with suboptimal CRs and CFs values, carbohydrate counting errors, and random meals sizes at random ingestion times. From Week 1 to Week 8, the learning algorithm increased the percentage of time spent in target glucose range (4.0 to 10.0 mmol/L) from 51 % to 64 % compared to 61 % and 58 % with the run-to-run algorithm A and the run-to-run algorithm B, respectively. The learning algorithm decreased the percentage of time spent below 4.0 mmol/L from 9 % to 1.9 % compared to 3.4 % and 2.3 % with the run-to-run algorithm A and the run-to-run algorithm B, respectively. The algorithm was also assessed by comparing its recommendations with (i) the endocrinologist's recommendations on two type 1 diabetes individuals over a 16-week period and (ii) real-world individuals' therapy settings changes of 23 individuals (19 type 2 and 4 type 1) over an 8-week period using the commercial Bigfoot Unity Diabetes Management System. The full agreements (i) were 89 % and 76 % for CRs and CFs for the type 1 diabetes individuals and (ii) was 62 % for mealtime doses for the individuals on the commercial Bigfoot system. Therefore, the proposed algorithm has the potential to improve glucose control in individuals with type 1 and type 2 diabetes.

Shining the Spotlight on Multiple Daily Insulin Therapy: Real-World Evidence of the InPen Smart Insulin Pen.

Objective: Connected insulin pens are creating opportunities for the millions of individuals with diabetes using multiple daily injections (MDI) therapy across the globe. Continuous glucose monitoring (CGM) data from connected insulin pens are revealing gaps and opportunities to significantly improve care for this population. In this article, we report real-world findings of the InPen™ smart insulin pen paired with CGM (InPen system), used by persons with type 1 diabetes (T1D) and type 2 diabetes (T2D). Methods: A retrospective cohort analysis was conducted with the real-world data collected from the InPen system of individuals (N = 3793 with T1D, N = 552 with T2D, and N = 808 unidentified) who used the system from January 01, 2020, to December 31, 2021. Diabetes management (e.g., missed and mistimed insulin dosing, mismatched food intake, and correction dose delivery) and glycemic outcomes were assessed. Results: In the overall and T1D populations, a dosing frequency of ≥3 doses per day and a missed dose frequency of <20% was associated with improved glycemia. In adults with T2D, missing <20% of doses was the significant factor determining improved glycemia. Conclusion: This analysis, integrating data from a smart insulin pen and CGM, provides insights into the impact of dosing behavior on glycemic outcomes and informs counseling strategies for the diabetes care team, through technologically advanced insulin management for those using MDI therapy.

Using stories to explore the lived experience of alcohol consumption in people with diabetes mellitus

Abstract Background: Evidence supports the risks of dangerous episodes of hypoglycaemia, hyperglycaemia, or extreme glucose variability in type 1 diabetes during and after alcohol consumption. Minimal evidence regarding preventative self‐care strategies exists, and people with type 1 diabetes can develop personal tactics to overcome risks. Combining the lived experience of managing alcohol consumption while living with diabetes will enrich new patient and health care professional education.Methods: Participants were recruited from social media, and attended between one and three online storytelling workshops. Demographic data were collected by questionnaire, and qualitative data were collected by note‐taking during the online sessions and evaluated by thematic analysis.Results: Nine participants aged 18–36 years (type 1 diabetes = seven [three female], and type 2 diabetes = two [both male]) were recruited. Insulin administration was by multiple daily injection therapy (n=5 including one type 2 diabetes), continuous subcutaneous insulin infusion (n=3) without hybrid closed loop, and sulphonylurea plus morning long‐acting analogue insulin (n=1 type 2 diabetes). From the nine participant stories three diabetic ketoacidosis, three hypoglycaemia, and one extreme glucose variability episodes occurred. Four clustered themes were found: living with diabetes, managing alcohol, app development suggestions, and future development suggestions.Discussion: New insights discovered were: distressing glucose risks including diabetic ketoacidosis episodes, misinterpretation of glucose and intoxication symptoms, trial and error approaches, and non‐disclosure to health care professionals regarding severe glucose situations. Copyright © 2023 John Wiley &amp; Sons.

Assessing Time in Range with Postprandial Glucose-Focused Titration of Ultra Rapid Lispro (URLi) in People with Type1 Diabetes.

To assess time in range (TIR) (70-180mg/dL) with postprandial glucose (PPG)-focused titration of ultra rapid lispro (URLi; Lyumjev®) in combination with insulin degludec in people with type1 diabetes (T1D). This phase2, single-group, open-label, exploratory study was conducted in 31 participants with T1D on multiple daily injection therapy. Participants were treated with insulin degludec and Lispro for an 11-day lead-in and then URLi for a 46-day treatment period consisting of 35-day titration and 11-day endpoint maintenance period. Glucose targets for the titration period were PPG < 140mg/dL or < 20% increase from premeal, fasting glucose 80-110mg/dL, and overnight excursion ± 30mg/dL or less. Participants used the InPen™ bolus calculator and Dexcom G6 continuous glucose monitoring (CGM). Primary endpoint mean TIR (70-180mg/dL) with URLi during the maintenance period was 70.2%. TIR (70-180mg/dL) and times below/above range were not significantly different with URLi (maintenance) versus lispro (lead-in). HbA1c decreased from 7.1% at screening to 6.8% at endpoint (least squares mean [LSM] change from baseline, - 0.36%; P < 0.001). Fructosamine and 1,5-anhydroglucitol improved (P < 0.001). Mean hourly glucose using CGM was reduced from 8:00AM to 4:00PM with URLi. Overall highest PPG excursion across meals was significantly reduced at URLi endpoint compared with lispro lead-in (mean 56.5 vs 72.4mg/dL; P < 0.001). Insulin-to-carbohydrate ratio (U/Xg) was reduced (more insulin given) at breakfast at URLi endpoint vs lead-in (LSM 9.0 vs 9.7g; P = 0.002) and numerically decreased at other meals. Total daily insulin dose (TDD) was higher at URLi endpoint compared with lispro lead-in (mean 50.2 vs 47.0U; P = 0.046) with similar prandial/TDD ratio (mean 52.1% vs 51.2%). There were no severe hypoglycemia events during the study. URLi in a basal-bolus regimen focusing on PPG targets demonstrated improved overall glycemic control and reduced PPG excursions without increased hypoglycemia in participants with T1D. ClinicalTrial.gov, NCT04585776.

Newly diagnosed type 1 diabetes mellitus in a human immunodeficiency virus-infected patient with antiretroviral therapy-induced immune reconstitution inflammatory syndrome: a case report

BackgroundDiabetes that develops in human immunodeficiency virus (HIV)-infected patients who receive antiretroviral therapy (ART) is usually type 2 diabetes mellitus (T2DM); however, autoimmune diabetes, such as type 1 diabetes mellitus (T1DM) can also develop in this population. After treatment with ART, patients might experience clinical deterioration following an increase in the CD4 cell count, which is termed immune reconstitution inflammatory syndrome (IRIS). Here, we describe an HIV-infected patient on ART who developed T1DMat due to IRIS, highlighting the clinical complexity in diagnosis and treatment.Case presentationA 36-year-old man infected with HIV had a nadir CD4 cell count of 15.53/μL before medication, which increased to 429.09/μL after 9 months of regular ART. The fasting serum glucose at 9 months was between 96 mg/dL and 117 mg/dL. After 11 months of ART, the patient was admitted to hospital for diabetic ketoacidosis (DKA) and Graves’ disease (GD). Noninsulin antidiabetics (NIADs) were prescribed following the resolution of DKA. However, poor glycemic control was noted despite well-titrated NIADs. Further investigation demonstrated poor pancreatic beta cell function and elevated anti-glutamic acid decarboxylase (anti-GAD) and anti-tyrosine phosphatase-like insulinoma antigen 2 (anti-IA2) titers. According to the results, he was diagnosed with T1DM and received multiple daily injections(MDI) of insulin. The regimen of MDI was insulin degludec as basal insulin and insulin aspart as prandial insulin. After MDI therapy, his glycemic control was improved.ConclusionIn this case, T1DM was ascribed to IRIS. Although this phenomenon has been demonstrated in previous case reports, further study is necessary to realize the mechanism of this association. Therefore, we emphasize that when HIV-infected patients on ART experience an unstable blood glucose level and abnormal thyroid function, physicians should consider T1DM and GD associated with ART-induced IRIS to reduce the subsequent complications and more serious endocrine dysfunction.

Association between different modalities of insulin administration and metabolic dysfunction-associated fatty liver disease in adults with type 1 diabetes mellitus

AimWe examined whether different insulin administration modalities, i.e., multiple daily injections (MDI) or continuous subcutaneous insulin infusion (CSII by insulin pumps), are differently associated with the risk of having metabolic dysfunction-associated fatty liver disease (MAFLD), with or without coexisting significant liver fibrosis (assessed by validated non-invasive biomarkers), in adults with type 1 diabetes mellitus (T1DM). MethodsWe conducted a retrospective, multicenter, cross-sectional study involving 1,417 adult individuals with established T1DM treated with MDI or CSII. We calculated hepatic steatosis index (HSI) and fibrosis (FIB)-4 index for non-invasively detecting MAFLD (defined by HSI >36), with or without coexisting significant fibrosis (defined by FIB-4 index ≥ 1.3 or <1.3, respectively). ResultsCompared to the MDI group (n = 1,161), insulin-pump users (n = 256; 18.1%) were more likely to be younger (mean age: 40 vs. 48 years, P < 0.001), had better glycemic control (mean hemoglobin A1c: 7.7% vs. 7.9%, P = 0.025) and a markedly lower prevalence of MAFLD with coexisting significant fibrosis (2.7% vs. 8.1%, P = 0.010), but a comparable prevalence of MAFLD without fibrosis. In multinomial logistic regression analysis, CSII therapy was associated with a ∼70%-lower risk of MAFLD with significant fibrosis (unadjusted odds ratio 0.32, 95% confidence interval 0.14–0.70; P = 0.004), but this association was no longer significant after adjustment for age, hemoglobin A1c and other potential confounders. ConclusionThe lower prevalence of MAFLD with coexisting significant fibrosis we observed in adults with T1DM using CSII therapy, compared to those using MDI therapy, is primarily mediated by inter-group differences in age.

Close intervention sessions complement intensive insulin therapy in paediatric diabetes: a longitudinal study

ObjectiveTo examine the impact of multidisciplinary team input and intensive insulin therapy on glycaemic control in children and adolescents with diabetes over a 13-year period.DesignTwo statistical approaches were used to...

58-OR: Glycemic Impact of Meal-Dosing Behavior in Users of the InPen Smart Insulin Pen (SIP) Paired with Continuous Glucose Monitoring (CGM)

Background: Data from connected insulin pen therapies are revealing both gaps and opportunities to significantly improve care for people on multiple daily insulin injections therapy. This real-world (RW) data analysis reports on the impact of meal-dosing behavior (missed and late) on glycemia in adult and pediatric InPen users with type 1 (T1D) or type 2 diabetes (T2D). Method: The RW data from 5,153 deidentified individuals who used the InPen SIP and CGM for at least 30 days between January 2020 and December 2021, and who had dosing and CGM data between 30 and 59 days since first bolus date, were analyzed using a meal detection algorithm. Users with &amp;lt;14 days of bolus data or inadequate CGM data (&amp;lt;14 days of 70% or more SG data/day) were excluded. Results: The impact of dosing behavior (≤2 versus &amp;gt;3 doses/day) and missed dose frequency (&amp;lt;20% versus ≥20%) on glycemia was analyzed (Table). A dosing frequency of &amp;gt;3 (including correction-only doses) and a missed dose frequency of &amp;lt;20% were associated with improved glycemic metrics. Overall, the frequency of on-time dosing was significantly correlated with user TIR (r=0.59, p&amp;lt;0.001). Conclusion: Real-world InPen with CGM use data provide insights into the impact of meal-dosing behavior on glycemic outcomes, which may inform counseling strategies for care teams and open the door to precision insulin injection management. Disclosure J.Macleod: Employee; Medtronic. M.Smith: Employee; Medtronic. G.Im: Employee; Medtronic. T.L.Cordero: Employee; Medtronic. R.A.Vigersky: Employee; Medtronic.

911-P: Changes in Metrics of Continuous Glucose Monitoring during COVID-19 in Children and Adolescents with Type 1 Diabetes

Background: Data on the changes in glucose control in pediatric patients with type 1 diabetes (T1D) affected by COVID-19 is lacking. We aimed to evaluate changes in metrics of continuous glucose monitoring (CGM) system during COVID-19 infection in children and adolescents with T1D. Methods: We included 21 children and adolescents with T1D, aged younger than 20 years, with at least 70% of CGM readings during COVID-19. Symptoms of COVID-19 infection were investigated through a questionnaire. The effects of COVID-19 on metrics of CGM were assessed at five different time points [2 weeks before-COVID-19 (Time 1), 1 week before-COVID-19 (Time 2), 1 week during COVID-19 (Time 3), 1 week after COVID-19 (Time 4), and 2 weeks after COVID-19 (Time 5)]. Results: Of 21 patients (6 males and 15 females), mean age was 11.4 ± 4.7 years, and mean disease duration was 5.1 ± 4.8 years. All had at least one related symptoms (mean duration of symptoms of 5.2 ± 3.7 days); no one required hospitalization. Glucose management indicator (GMI) and the percentage of time spent above range (&amp;gt; 250 mg/dL) were significantly higher at Time 3 compared to Time 5 (7.8 ± 1.4 % vs 7.2 ± 1.4 %; P = 0.001 and 18.3 ± 18.5 % vs 13.0 ± 15.7 %; P = 0.016, respectively). According to the insulin delivery methods, GMI at Time 2 was significantly higher compared to Time 5 in patients treated with multiple daily injection (MDI) (n = 13) but not in those using continuous subcutaneous insulin infusion (CSII) (n = 6). Conclusion: Pediatric patients with T1D experience mild COVID-19 infection with worsening glycemic control during COVID-19. The use of CSII is more effective in maintaining stable glycemic control during COVID-19 infection compared to MDI therapy. Disclosure H.Kim: None. S.Shin: None. S.Kim: None. J.Kim: None.

Reinforcement Learning for Multiple Daily Injection (MDI) Therapy in Type 1 Diabetes (T1D)

In this study, we propose a closed-loop insulin administration framework for multiple daily injection (MDI) treatment using a reinforcement learning (RL) agent for insulin bolus therapy. The RL agent, based on the soft actor–critic (SAC) algorithm, dynamically adjusts insulin dosages based on real-time glucose readings, meal intakes, and previous actions. We evaluated the proposed strategy on ten in silico patients with type 1 diabetes undergoing MDI therapy, considering three meal scenarios. The results show that, compared to an open-loop conventional therapy, our proposed closed-loop control strategy significantly reduces glucose variability and increases the percentage of time the glucose levels remained within the target range. In particular, the weekly mean glucose level reduced from 145.34 ± 57.26 mg/dL to 115.18 ± 7.93 mg/dL, 143.62 ± 55.72 mg/dL to 115.28 ± 8.11 mg/dL, and 171.63 ± 49.30 mg/dL to 143.94 ± 23.81 mg/dL for Scenarios A, B and C, respectively. Furthermore, the percent time in range (70–180 mg/dL) significantly improved from 63.77 ± 27.90% to 91.72 ± 9.27% (p = 0.01) in Scenario A, 64.82 ± 28.06% to 92.29 ± 9.15% (p = 0.01) in Scenario B, and 58.45 ± 27.53% to 81.45 ± 26.40% (p = 0.05) in Scenario C. The model also demonstrated robustness against meal disturbances and insulin sensitivity disturbances, achieving mean glucose levels within the target range and maintaining a low risk of hypoglycemia, which were statistically significant for Scenarios B and C. The proposed model outperformed open-loop conventional therapy in all scenarios, highlighting the potential of RL-based closed-loop insulin administration models in improving diabetes management.

Intermittent closed-loop blood glucose control for people with type 1 diabetes on multiple daily injections

Background and objectives: Recent advances in Automated Insulin Delivery systems have been shown to dramatically improve glycaemic control and reduce the risk of hypoglycemia in people with type 1 diabetes. However, they are complex systems that require specific training and are not affordable for most. Attempts to reduce the gap with closed-loop therapies using advanced dosing advisors have so far failed, mainly because they require too much human intervention. With the advent of smart insulin pens, one of the main constraints (having reliable bolus and meal information) disappears and new strategies can be employed. This is our starting hypothesis, which we have validated in a very demanding simulator. In this paper, we propose an intermittent closed-loop control system specifically intended for multiple daily injection therapy to bring the benefits of artificial pancreas to the application of multiple daily injections.Methods: The proposed control algorithm is based on model predictive control and integrates two patient-driven control actions. Correction insulin boluses are automatically computed and recommended to the patient to minimize the duration of hyperglycemia. Rescue carbohydrates are also triggered to avoid hypoglycemia episodes. The algorithm can adapt to different patient lifestyles with customizable triggering conditions, closing the gap between practicality and performance. The proposed algorithm is compared with conventional open-loop therapy, and its superiority is demonstrated through extensive in silico evaluations using realistic cohorts and scenarios. The evaluations were conducted in a cohort of 47 virtual patients. We also provide detailed explanations of the implementation, imposed constraints, triggering conditions, cost functions, and penalties for the algorithm.Results: The in-silico outcomes combining the proposed closed-loop strategy with slow-acting insulin analog injections at 09:00 h resulted in percentages of time in range (TIR) (70–180 mg/dL) of 69.5%, 70.6%, and 70.4% for glargine-100, glargine-300, and degludec-100, respectively, and injections at 20:00 h resulted in percentages of TIR of 70.5%, 70.3%, and 71.6%, respectively. In all the cases, the percentages of TIR were considerably higher than those obtained from the open-loop strategy, being only 50.7%, 53.9%, and 52.2% for daytime injection and 55.5%, 54.1%, and 56.9% for nighttime injection. Overall, the occurrence of hypoglycemia and hyperglycemia was notably reduced using our approach.Conclusions: Event-triggering model predictive control in the proposed algorithm is feasible and may meet clinical targets for people with type 1 diabetes.

Increased Time in Range with Ultra Rapid Lispro Treatment in Participants with Type 2 Diabetes: PRONTO-Time in Range.

To evaluate time in range metrics and HbA1c in people with type 2 diabetes (T2D) treated with ultra rapid lispro (URLi) using continuous glucose monitoring (CGM) for the first time in this population. This was a Phase 3b, 12-week, single-treatment study in adults with T2D on basal-bolus multiple daily injection (MDI) therapy using basal insulin glargine U-100 along with a rapid-acting insulin analog. Following a 4-week baseline period, 176 participants were newly treated with prandial URLi. Participants used unblinded CGM (Freestyle Libre). Primary endpoint was time in range (TIR) (70-180mg/dl) during the daytime period at Week 12 compared to baseline with gated secondary endpoints of HbA1c change from baseline and 24-h TIR (70-180mg/dl). Improved glycemic control was observed at Week 12 versus baseline including mean daytime TIR (change from baseline [Δ] 3.8%; P = 0.007), HbA1c (Δ - 0.44%; P < 0.001), and 24-h TIR (Δ 3.3%; P = 0.016) with no significant difference in time below range (TBR). After 12weeks, there was a statistically significant decrease in postprandial glucose incremental area under curve, overall, across all meals, within 1h (P = 0.005) or 2h (P < 0.001) after the start of a meal. Basal, bolus, and total insulin dose were intensified with increased bolus/total dose ratio at Week 12 (50.7%) versus baseline (44.5%; P < 0.001). There were no severe hypoglycemia events during the treatment period. In people with T2D, URLi in an MDI regimen was efficacious with improved glycemic control including TIR, HbA1c, and postprandial glucose without increased hypoglycemia/TBR. CLINICALTRIAL REGISTRATION NUMBER: NCT04605991.

Impact of Advanced Hybrid Closed Loop on Youth With High-Risk Type 1 Diabetes Using Multiple Daily Injections.

To evaluate glycemic outcomes in youth (aged 13-25 years) with type 1 diabetes and high-risk glycemic control (HbA1c ≥8.5% [69 mmol/mol]) on multiple daily injection (MDI) therapy after transitioning to advanced hybrid closed loop (AHCL) therapy. This prospective, 3-month, single-arm, dual-center study enrolled 20 participants, and all completed the study. HbA1c decreased from 10.5 ± 2.1% (91.2 ± 22.8 mmol/mol) at baseline to 7.6 ± 1.1% (59.7 ± 11.9 mmol/mol), and time spent in target range 70-180 mg/dL (3.9-10.0 mmol/L) increased from 27.6 ± 13.2% at baseline to 66.5 ± 9.8% after 3 months of AHCL. Two episodes of diabetic ketoacidosis attributed to infusion set failure occurred. AHCL has the potential to improve suboptimal glycemia in youth with type 1 diabetes previously on MDI therapy.

Using Reinforcement Learning to Simplify Mealtime Insulin Dosing for People with Type 1 Diabetes: In-Silico Experiments

People with type 1 diabetes (T1D) struggle to calculate the optimal insulin dose at mealtime, especially when under multiple daily injections (MDI) therapy. Effectively, they will not always perform rigorous and precise calculations; but occasionally, they might rely on intuition and previous experience. Reinforcement learning (RL) has shown outstanding results in outperforming humans on tasks requiring intuition and learning from experience. In this work, we propose an RL agent that recommends the optimal meal-accompanying insulin dose corresponding to a qualitative meal (QM) strategy that does not require precise carbohydrate counting (CC) (e.g., a usual meal at noon.). The agent is trained using the soft actor-critic approach and comprises long short-term memory (LSTM) neurons. For training, eighty virtual subjects (VS) of the FDA-accepted UVA/Padova T1D adult population were simulated using MDI therapy and QM strategy. For validation, the remaining twenty VS were examined in 26-week scenarios, including intra- and inter-day variabilities in glucose. In-silico results showed that the proposed RL approach outperforms a baseline run-to-run approach and can replace the standard CC approach. Specifically, after 26 weeks, the time-in-range (70 - 180mg/dL) and time-in-hypoglycemia (< 70mg/dL) were 73.1 ± 11.6% and 2.0 ± 1.8% using the RL-optimized QM strategy compared to 70.6± 14.8% and 1.5± 1.5% using CC. Such an approach can simplify diabetes treatment resulting in improved quality of life and glycemic outcomes.

Efficacy of insulin dosing algorithms for high-fat high-protein mixed meals to control postprandial glycemic excursions in people living with type 1 diabetes: A systematic review and meta-analysis.

Optimizing postprandial blood glucose (PPG) levels after mixed meals that contain high fat and protein remains a challenge in the treatment of type 1 diabetes. This study evaluated the efficacy of different algorithms used for dosing insulin based on counting units of high fat and high protein (HFHP) meals with the current conventional method of counting carbohydrates alone to control PPG excursions. The MEDLINE, EMBASE, and Cochrane electronic databases were searched, with the analysis restricted to randomized control trials (RCTs). The primary outcome was the PPG (mean and standard deviation) at 240 min. The pooled final estimate was the mean difference (MD) of the PPGs at 240 min using random effect models to account for heterogeneity. In total, 15 studies were identified and included in the systemic review, of which 12 were RCTs, and three studies were non-randomized trials. The pooled MD of the PPG at 240 min was in favor of additional insulin doses in HFHP meals compared to the carbohydrate counting alone. The statistically significant results favored the combined bolus (30:70) that split over 2h in insulin pump therapy with pooled MD of the PPG, 240 min of -24.65; 95% CI: -36.59, -8.41; and heterogeneity, 0%. Other statistically significant results favored the additional insulin added to insulin to carb ratio (ICR) of meal bolus (25-60% ICR) in multiple daily injections therapy with the pooled MD of PPG at 240 min, -21.71; 95% CI: -38.45, -4.73; and heterogeneity, 18%. Insulin treatment based on fat and protein content, in addition to carbohydrate counting, is more effective than the carbohydrate counting method alone; however, further research is warranted to determine the best equation for fat and protein counting, particularly in people with multiple daily injections.