Titration of Long-Acting Insulin Using Continuous Glucose Monitoring and Smart Insulin Pens in Type 1 Diabetes: A Model-Based Carbohydrate-Free Approach

ObjectiveMultiple daily injections (MDI) therapy is the most common treatment for type 1 diabetes (T1D), consisting of long-acting insulin to cover fasting conditions and rapid-acting insulin to cover meals. Titration of long-acting insulin is needed to achieve satisfactory glycemia but is challenging due to inter-and intra-individual metabolic variability. In this work, a novel titration algorithm for long-acting insulin leveraging continuous glucose monitoring (CGM) and smart insulin pens (SIP) data is proposed.MethodsThe algorithm is based on a glucoregulatory model that describes insulin and meal effects on blood glucose fluctuations. The model is individualized on patient’s data and used to extract the theoretical glucose curve in fasting conditions; the individualization step does not require any carbohydrate records. A cost function is employed to search for the optimal long-acting insulin dose to achieve the desired glycemic target in the fasting state. The algorithm was tested in two virtual studies performed within a validated T1D simulation platform, deploying different levels of metabolic variability (nominal and variance). The performance of the method was compared to that achieved with two published titration algorithms based on self-measured blood glucose (SMBG) records. The sensitivity of the algorithm to carbohydrate records was also analyzed.ResultsThe proposed method outperformed SMBG-based methods in terms of reduction of exposure to hypoglycemia, especially during the night period (0 am–6 am). In the variance scenario, during the night, an improvement in the time in the target glycemic range (70–180 mg/dL) from 69.0% to 86.4% and a decrease in the time in hypoglycemia (<70 mg/dL) from 10.7% to 2.6% was observed. Robustness analysis showed that the method performance is non-sensitive to carbohydrate records.ConclusionThe use of CGM and SIP in people with T1D using MDI therapy has the potential to inform smart insulin titration algorithms that improve glycemic control. Clinical studies in real-world settings are warranted to further test the proposed titration algorithm.SignificanceThis algorithm is a step towards a decision support system that improves glycemic control and potentially the quality of life, in a population of individuals with T1D who cannot benefit from the artificial pancreas system.

Effect of Digital-Tool-Supported Basal Insulin Titration Algorithm in Reaching Glycemic Control in Patients with Type 2 Diabetes in Mexico

Background: My Dose Coach (MDC) is a mobile application combined with a web portal that can suggest optimized basal insulin (BI) injection doses using Self-Measured Plasma Glucose (SMPG) and hypoglycemia data. This study aimed to evaluate its efficacy on patients reaching SMPG and Fasting blood glucose (FBG) target range 90-130 mg/dl (5-7.2 mmol/L) goals without severe hypoglycemic episodes. We also addressed the mean reduction in glycated hemoglobin (A1C), FBG, and SMPG and the improvement in the WHO’s Five Well Being Index (WBI). Methods: This prospective pilot study involved the use of MDC in outpatients with type 2 diabetes (T2DM) from a Hospital in Northern Mexico. Patients on treatment with any BI were included in the study. The follow-up was of 16 weeks. Student t-tests or McNemar test were used for effect comparisons. Results: We included 158 patients (46.8% women), mean (SD) age 51 (10.3) years. We achieved SMPG target range in 58.9% [mean (95CI) reduction of 30.9 mg/dl (22.5-37.7; P < .001)] of the patients [66(28) days], with no severe hypoglycemia events. FBG goal was reached in 55.7% [mean (95CI) reduction of 63.4 mg/dl (49.6-77.2; P < .001)]. The mean (95CI) reduction of A1C was 1.78% (1.47-2, P < .01) with the last observation carried forward. There was a mean (95CI) increase of 2.23 (−3, −1.4, P < .01) points in WBI scale. Conclusions: MDC successfully helped to achieve FBG and SMPG goals, reduced A1C, and increased WBI with no severe hypoglycemia events.

Are there gender differences in delay discounting of monetary losses?

We investigate gender differences in delay discounting of monetary losses. 203 participants solved a discounting task based on the titration algorithm. The individual rates of delay discounting of losses were calculated with the use of AUC (Area Under the Curve) method. The results show that there is no statistically significant impact of gender on delay discounting of monetary losses. We briefly discuss possible biological and social explanations of the above finding.

Characteristics, Management, and Outcomes of Elderly Patients with Diabetes in a Covid-19 Unit: Lessons Learned from a Pilot Study

Background and objectives: Diabetes may affect in-hospital mortality of patients with Coronavirus disease 2019 (COVID-19). We have retrospectively evaluated clinical characteristics, diabetes management, and outcomes in a sample of COVID-19 patients with diabetes admitted to our hospital. Materials and Methods: All patients admitted to the Infectious Diseases Unit from 28 March 2020, to 16 June 2020, were enrolled. Clinical information and biochemical parameters were collected at the time of admission. Patients were ranked according to diabetes and death. Results: Sixty-one patients with COVID-19 were analyzed. Most of them were from a long-term health care facility. Mean age was 77 ± 16 years, and 19 had type 2 diabetes (T2D). Eighteen patients died, including 8 with T2D and 10 without T2D (p = 0.15). Patients with diabetes were significantly older, had a higher prevalence of cardiovascular diseases, and a significantly lower lymphocyte count. No significant relationship was found between diabetes and in-hospital mortality (Odds Ratio OR 2.3; Confidence Interval CI 0.73–7.38, p = 0.15). Patients with diabetes were treated with insulin titration algorithm. Severe hypoglycemic events, ketoacidosis and hyperosmolar hyperglycemias did not occur during hospitalization. Mean pre-meal capillary blood glucose was 157 ± 45 mg/dL, and the coefficient of variation of glycaemia was 29%. Conclusions: Our study, albeit limited by the small number of subjects, did not describe any significant association between T2D diabetes and mortality. Clinical characteristics of patients, and acceptable glucose control prior and during hospitalization may have influenced the result. The use of an insulin titration algorithm should be pursued during hospitalization.

Characteristics, Management, and Outcomes of Elderly Patients With Diabetes in a COVID-19 Unit: Lessons Learned.

BackgroundDiabetes may affect in-hospital mortality of patients with Coronavirus disease 2019 (COVID-19). We have retrospectively evaluated clinical characteristics, diabetes management, and outcomes in a sample of COVID-19 patients with diabetes admitted to our hospital. MethodsAll patients admitted to the Infectious Diseases Unit from March 28th, 2020, to June 16th, 2020, were enrolled. Clinical information and biochemical parameters were collected at the time of admission. Patients were ranked according to diabetes and death. ResultsSixty-one patients with COVID-19 were analyzed. Most of them were from a long-term health care facility. Mean age was 77±16 years, and 19 had type 2 diabetes (T2D). Eighteen patients died, including 8 with T2D and 10 without T2D (p=0.15). Patients with diabetes were significantly older, had a higher prevalence of cardiovascular diseases, and a significantly lower lymphocyte count. No significant relationship was found between diabetes and in-hospital mortality [OR 2.3; CI 0.73-7.38, p=0.15]. Patients with diabetes were treated with insulin algorithm titration algorithm, with no severe hypoglycemic events, ketoacidosis and hyperosmolar hyperglycemias occurring during hospitalization. Mean fasting pre-meal capillary blood glucose was 157±45 mg/dL, and the coefficient of variation of glycaemia was 29%. ConclusionsOur study, albeit limited by the small number of subjects, did not describe any significant association between T2D diabetes and mortality. Clinical characteristics of patients, and acceptable glucose control prior and during hospitalization may have influenced the result, thus suggesting that the insulin algorithm titration algorithm applied should be validated.

Comparison of weight-based insulin titration (WIT) and glucose-based insulin titration using basal-bolus algorithm in hospitalized patients with type 2 diabetes: a multicenter, randomized, clinical study

IntroductionSubcutaneous administration of insulin is the preferred method for achieving glucose control in non-critically ill patients with diabetes. Glucose-based titration protocols were widely applied in clinical practice. However, most of these algorithms are experience-based and there is considerable variability and complexity. This study aimed to compare the effectiveness and safety of a weight-based insulin titration algorithm versus glucose-based algorithm in hospitalized patients with type 2 diabetes mellitus (T2DM).Research design and methodsThis randomized clinical trial was carried out at four centers in the South, Central and North China. Inpatients with T2DM were randomly assigned (1:1) to receive weight-based and glucose-based insulin titration algorithms. The primary outcome was the length of time for reaching blood glucose (BG) targets (fasting BG (FBG) and 2-hour postprandial BG (2hBG) after three meals). The secondary outcome included insulin dose for achieving glycemic control and the incidence of hypoglycemia during hospitalization.ResultsBetween January 2016 and June 2019, 780 patients were screened, and 575 completed the trial (283 in the weight-based group and 292 in the glucose-based group). The lengths of time for reaching BG targets at four time points were comparable between two groups. FBG reached targets within 3 days and 2hBG after three meals within 4 days. There is no significant difference in insulin doses between two groups at the end of the study. The total daily dosage was about 1 unit/kg/day, and the ratio of basal-to-bolus was about 2:3 in both groups. The incidence of hypoglycemia was similar in both groups, and severe hypoglycemia was not detected in either of the groups.ConclusionsWeight-based insulin titration algorithm is equally effective and safe in hospitalized patients with T2DM compared with glucose-based algorithm.Trial registration numberNCT03220919.

Implementation of an Intravenous Fluid Titration Algorithm to Treat Pediatric Diabetic Ketoacidosis

Diabetic ketoacidosis (DKA) is a common cause of admission to the pediatric intensive care unit and many centers utilize the “two-bag system” to treat DKA. We developed an intravenous fluid (IVF) titration algorithm to standardize adjustments of the two bags. A retrospective cohort study was performed comparing 155 patients treated before and 175 patients treated after implementation of the IVF titration algorithm. Postimplementation patients reached the blood glucose target zone faster and had a higher probability of remaining at goal while on insulin infusion. There was no significant difference in incidence of cerebral edema or hypoglycemia between study groups. Overall IVF titration algorithm compliance was 95%. Implementation of an IVF titration algorithm is safe and effective when treating DKA in children.

Abstract 218: Improving Guideline-Directed Medical Therapy Utilization for Heart Failure With Reduced Ejection Fraction Within a Veteran's Affairs Health System

Despite a robust evidence base and well-established clinical guidelines for patients with HFrEF, a significant number of patients with this disease are not currently prescribed ACEI/ARB/ARNI and beta-blocker therapies at or near target doses proven to reduce the risk of cardiovascular events and mortality in randomized clinical trials. Within the VA Palo Alto Health System we found that the minority of patients with HFrEF prescribed these therapies were receiving ACEI/ARB/ARNI (45.2%: 410 of 908) and beta-blockers (45.4%: 458 of 1008) at ≥50% of target doses. Limited general medicine and cardiology appointment availability as well as clinical inertia were identified as root causes of suboptimal dosing of guideline-directed medical therapy (GDMT). We addressed these with implementation of a pharmacist driven Heart Failure Medication Titration Clinic through a shared practice agreement with general medicine physicians, initially at one clinical site with 190 total HFrEF patients. An academic detailing clinical dashboard including medication prescribing and LV ejection fraction data (obtained via natural language processing of imaging reports) is utilized by the on-site clinical pharmacist to identify actionable HFrEF patients on suboptimal GDMT. If felt appropriate for escalation of therapy, a patient’s primary care physician or cardiologist approves a referral to the clinic. The pharmacist then conducts regular clinic or telephone visits (typically every two weeks) with the patient to assess tolerance of therapy and eligibility for further dose escalation per an established titration algorithm that integrates recent symptoms, vital signs, and lab values. In three months, patients referred to the Heart Failure Medication Titration Clinic have had their average ACE/ARB/ARNI dose escalated from 21.9% to 42.7% of target dose and their average beta-blocker dose escalated from 56.3% to 81.3% of target dose. No adverse medication events or hospitalizations have occurred. There has been a corresponding increase in the overall percentage of this clinical site’s HFrEF patients on ACEI/ARB/ARNI (36.4% to 43.7%: 55 of 126) and beta-blockers (39.4% to 43.0%: 55 of 128) that are receiving ≥50% of target dose therapy. These results suggest that clinical pharmacists can play a vital role in identifying and treating patients that are on suboptimal treatment for HFrEF via utilization of an academic detailing dashboard and pharmacist led medication titration clinics. Limitations of this quality improvement initiative include short duration of follow-up to date and performance of these interventions within an integrated health care system, which may not be generalizable to other health care delivery models. Next steps include addition of mineralocorticoid antagonist therapy to our titration algorithm and scaling these interventions to additional clinical sites within our health system.

Feasibility of a New Approach to Initiate Insulin in Type 2 Diabetes

Background: Treatment inertia and prescription complexity are among reasons that people with type 2 diabetes (T2D) do not reach glycemic targets. This study investigated feasibility of a new approach to basal insulin initiation, where the dose needed to reach a glycemic target is estimated from two weeks of insulin and continuous glucose monitoring (CGM) data. Methods: This was an exploratory single arm study with a maximum length of 84 days. Eight insulin naïve people with T2D, planning to initiate basal insulin, wore a CGM throughout the study period. A predetermined regime was followed for the first two weeks after which the end dose was estimated. The clinician decided whether to follow this advice and continued the titration until target was reached using a twice weekly stepwise titration algorithm. The primary outcome was the comparison between the estimated and the actual end doses. Results: Median age of participants was 57 years (range: 50-77 years), duration of diabetes was 16 years (range: 5-29 years), and Bodi Mass Index (BMI) was 30.2 kg/m2 (range: 22.0-36.0 kg/m2). The median study end dose was 37 U (range: 20-123 U). The estimated end dose was smaller than or equal to the study end dose in all cases, with median error of 26.7% (range: 0.0%-75.8% underestimation). No self-monitoring of blood glucose values were below 70 mg/dL and no severe hypoglycemia occurred. Conclusion: While accuracy may be improved, it was found safe to predict the study end dose of insulin degludec from two weeks of data.