Associations of bolus insulin injection frequency and smart pen engagement with glycaemic control in people living with type 1 diabetes.

AIM: To evaluate whether both bolus insulin injection frequency and smart pen engagement were associated with changes in glycaemic control, using real-world data from adults with type 1 diabetes (T1D). MATERIALS AND METHODS: Adults using a smart pen (NovoPen 6) to administer bolus insulin (fast-acting insulin aspart or insulin aspart) alongside continuous glucose monitoring were eligible for inclusion. Smart pen engagement was characterized by number of days with pen data uploads over the previous 14 days. Glycaemic control was evaluated by analysing glucose metrics. RESULTS: Overall, data from 1194 individuals were analysed. The number of daily bolus injections was significantly associated with time in range (TIR; 3.9-10.0 mmol/L [70-180 mg/dL]; P < 0.0001). Individuals administering, on average, three daily bolus insulin injections had an estimated 11% chance of achieving >70% TIR. The probability of achieving >70% TIR increased with the mean number of daily bolus injections. However, the percentage of TIR was lower on days when individuals administered higher-than-average numbers of injections. The observed mean number of daily bolus injections administered across the study population was lower than the optimal number required to reach glycaemic targets (4.8 injections vs. 6-8 injections). Smart pen engagement was significantly associated with improved TIR. CONCLUSIONS: Glycaemic control was associated with daily bolus insulin injection frequency and smart pen engagement. A treatment regimen combining an optimal bolus injection strategy, and effective smart pen engagement, may improve glycaemic control among adults with T1D.

Association between weight loss and health care resource utilization in adults living with obesity: Evidence from a UK primary care database.

AIMS: We investigated the impact of intentional weight loss on health care resource utilization (HCRU) and costs among people with obesity. MATERIALS AND METHODS: This retrospective, observational cohort study used data from the Clinical Practice Research Datalink (CPRD) GOLD database. Adults >18 years at index date [first recorded body mass index (BMI) of 30-50 kg/m2 between 2006 and 2015 with a further BMI record 4 years later] were assigned to an intentional weight loss cohort (-25% to -10% BMI change) or a stable weight cohort (-3% to +3%), based on their BMI change during a 4-year baseline period from index date. Evidence of intention to lose weight during the baseline period was required. Linked Hospital Episode Statistics datasets captured HCRU and costs over an 8-year follow-up period. Mixed effects models adjusted for demographics, total costs during baseline and baseline comorbidities were used. RESULTS: Baseline characteristics were similar between cohorts with weight loss (n = 8676) and stable weight (n = 44 519). Over follow-up, the weight loss cohort experienced a significantly lower mean annual increase in total costs [2.1% (95% confidence interval: 1.3-2.8)] than the stable weight cohort [4.3% (95% confidence interval: 4.0-4.6); p < .0001]. Weight loss was associated with a lower mean annual increase in multiple HCRU and cost components compared with maintaining a stable high weight. CONCLUSIONS: Our findings suggest that intentional weight loss of 10-25% is associated with lower HCRU and costs in the long term among individuals living with obesity, relative to stable weight.

Association Between Treatment Adherence and Continuous Glucose Monitoring Outcomes in People With Diabetes Using Smart Insulin Pens in a Real-World Setting.

OBJECTIVE: To evaluate the association of insulin injection adherence, smart insulin pen engagement, and glycemic control using real-world data from 16 countries from adults self-administering basal insulin degludec and bolus insulin with a smart insulin pen (NovoPen 6 or NovoPen Echo Plus) alongside continuous glucose monitoring (CGM). RESEARCH DESIGN AND METHODS: Data were aggregated over 14-day periods. Treatment adherence was defined according to the number of missed basal and missed bolus insulin doses and smart pen engagement according to the number of days with data uploads. RESULTS: Data from 3,945 adults, including 25,157 14-day periods with ≥70% CGM coverage, were analyzed. On average, 0.2 basal and 6.0 bolus insulin doses were missed over 14 days. The estimated probability of missing at least one basal insulin dose over a 14-day period was 17.6% (95% CI 16.5, 18.7). Missing one basal or bolus insulin dose per 14 days was associated with a significant decrease in percentage of time with glucose levels in range (TIR) (3.9-10.0 mmol/L), of -2.8% (95% CI -3.7, -1.8) and -1.7% (-1.8, -1.6), respectively; therefore, missing two basal or four bolus doses would decrease TIR by >5%. Smart pen engagement was associated positively with glycemic outcomes. CONCLUSIONS: This combined analysis of real-world smart pen and CGM data showed that missing two basal or four bolus insulin doses over a 14-day period would be associated with a clinically relevant decrease in TIR. Smart insulin pens provide valuable insights into treatment injection behaviors.

Smart Pen Exposes Missed Basal Insulin Injections and Reveals the Impact on Glycemic Control in Adults With Type 1 Diabetes.

BACKGROUND: Adherence to basal insulin injections and the effects of missed basal insulin injections in adults with type 1 diabetes (T1D) were investigated using data from continuous glucose monitoring (CGM) and smart insulin pen devices in a real-world study. METHODS: This was a post hoc analysis of a prospective, real-world study conducted in Sweden. Adults with T1D who were using CGM received a smart insulin pen device (NovoPen 6) for insulin injections. Missed basal insulin doses (≥40 hours between doses) were evaluated over 14-day periods, and the probability of missing basal insulin doses was estimated. Associations between missed basal insulin doses and glycemic outcomes were also explored. RESULTS: Thirty-two patients with 4410 acceptable CGM days (315 14-day periods) were included. The number of missed basal insulin doses ranged from 0 to 4 over 315 14-day periods. The estimated probability of missing at least one basal insulin dose over any given 14-day period was 22% (95% confidence interval: 10%-40%). Missed basal insulin doses were significantly associated with higher mean glycemic levels, higher glucose management indicator, and lower time in range (70-180 mg/dL [3.9-10.0 mmol/L]). Similar results were observed when adjusted for missed bolus insulin doses; age and sex had no statistically significant effect on any glycemic parameter. CONCLUSIONS: This is the first study, based on accurate real-world injection data, to demonstrate the challenge of adherence to basal insulin injections in patients with T1D, and document that just one missed basal injection per week can result in clinically significant changes in glycemic control.

Improved Glycemic Control Observed in Children with Type 1 Diabetes Following the Introduction of Smart Insulin Pens: A Real-World Study.

INTRODUCTION: Many challenges are associated with optimizing glycemic control in pediatric patients with type 1 diabetes (T1D); combining data from smart insulin pens and continuous glucose monitoring (CGM) could mitigate some of these obstacles. METHODS: This one-arm, prospective, observational study investigated the effects of introducing a smart pen on glycemic control in pediatric patients with T1D who were using CGM. Children and adolescents with T1D who had been prescribed a smart pen for basal and/or bolus insulin injections were enrolled from three clinics in Sweden. Outcomes compared between baseline and follow-up (≥ 12 months) included: mean numbers of daily (over 24 h) and nocturnal hypoglycemic or hyperglycemic events; time above range (TAR; > 180 mg/dL); time below range (TBR; level 1: 54 to < 70 mg/dL; level 2: < 54 mg/dL); time in range (TIR; 70-180 mg/dL); and missed bolus-dose (MBD) meals. RESULTS: Overall, 39 patients were included. Mean numbers of daily hypoglycemic events (- 31.4%; p = 0.00035) and nocturnal hypoglycemic events (- 24.4%; p = 0.043) were significantly reduced from baseline to follow-up. Mean daily TBR level 2 was reduced from 2.82% at baseline to 2.18% at follow-up (- 0.64 percentage points; p = 0.025). There were no statistically significant changes in number of daily hyperglycemic events, MBD meals, TIR, TAR, or TBR level 1. CONCLUSIONS: Introducing smart insulin pens was associated with a reduced number of hypoglycemic events and decreases in TBR level 2, demonstrating a potential benefit for glycemic control in pediatric patients.

Increased Time in Range and Fewer Missed Bolus Injections After Introduction of a Smart Connected Insulin Pen.

Background: This observational study investigated whether the connected NovoPen® 6 could influence insulin regimen management and glycemic control in people with type 1 diabetes (T1D) using a basal-bolus insulin regimen and continuous glucose monitoring in a real-world setting. Methods: Participants from 12 Swedish diabetes clinics downloaded pen data at each visit (final cohort: n = 94). Outcomes included time in range (TIR; sensor glucose 3.9-10.0 mmol/L), time in hyperglycemia (>10 mmol/L), and hypoglycemia (L1: 3.0- <3.9 mmol/L; L2: <3.0 mmol/L). Missed bolus dose (MBD) injections were meals without bolus injection within -15 and +60 min from the start of a meal. Outcomes were compared between the baseline and follow-up periods (≥5 health care professional visits). Data were analyzed from the first 14 days following each visit. For the TIR and total insulin dose analyses (n = 94), a linear mixed model was used, and for the MBD analysis (n = 81), a mixed Poisson model was used. Results: TIR significantly increased (+1.9 [0.8; 3.0]95% CI h/day; P < 0.001) from baseline to follow-up period, with a corresponding reduction in time in hyperglycemia (-1.8 [-3.0; -0.6]95% CI h/day; P = 0.003) and L2 hypoglycemia (-0.3 [-0.6; -0.1]95% CI h/day; P = 0.005), and no change in time in L1 hypoglycemia. MBD injections decreased by 43% over the study (P = 0.002). Change in MBD injections corresponded to a decrease from 25% to 14% based on the assumption that participants had three main meals per day. Conclusions: Our study highlights the potential benefit on glycemic control and dosing behavior when reliable insulin dose data from a connected pen contribute to insulin management in people with T1D.

Assessment of automated screening for treatment-requiring diabetic retinopathy.

PURPOSE: To evaluate fundus photographic image analysis combining automated detection of red lesions, bright lesions, and image quality as a means of identifying treatment-requiring diabetic retinopathy in a screening population of diabetic patients. METHODS: This was a retrospective cross-sectional study of 106 patients from a diabetic retinopathy screening clinic referred for photocoagulation treatment in the period from January 1996 to May 2002 on the basis of mydriatic 60-degree 35-mm color transparency fundus photography. One fovea-centered fundus photograph and one centered nasal of the optic disk from each of a subject's two eyes was selected for digitization and analyzed using a previously tested computerized red-lesion detection algorithm in combination with a new algorithm for detection of bright lesions and image quality. The algorithm was calibrated on an independent set of fundus photographs. RESULTS: Automated red-lesion detection identified 104 of 106 patients requiring photocoagulation treatment, whereas bright-lesion detection identified only 91 of the 106 patients. Two patients who were not identified by either lesion detection algorithm were automatically detected as having poor image quality in one or both eyes. In the study sample, the risk of missing treatment-requiring retinopathy patients from being detected was 0.0% (estimated CI(95) 0.0-3.4%). CONCLUSIONS: The combination of automated detection of red lesions and poor image quality identified all treatment-requiring diabetic retinopathy patients in the study sample. No additional information was contributed by the automated bright-lesion detection.