Minimizing Glycemic Fluctuations in Patients with Type 2 Diabetes: Approaches and Importance

Dandona, Paresh

doi:10.1089/dia.2016.0372

Cited by 54 publications

(44 citation statements)

References 61 publications

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“…[31][32][33][34][35] As measurements of HbA 1c do not reflect glycemic variability and target HbA 1c values may be achieved while still experiencing marked daily glycemic fluctuations, people with T1D may regard reducing glucose variability and improving TIR to be as important as achieving their target HbA 1c value. 36,37 The study data also confirmed that missing bolus injections can be common for people with T1D, where on average at least 25% of meals had a missed dose, assuming three meals per day. This amounts to five meals with a missed dose per week on average.…”

Section: Discussionsupporting

confidence: 61%

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

Adolfsson

Hartvig

Kaas

et al. 2020

Diabetes Technology & Therapeutics

111

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Background: This observational study investigated whether the connected NovoPen Ò 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.

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Section: Discussionsupporting

confidence: 61%

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

Adolfsson

Hartvig

Kaas

et al. 2020

Diabetes Technology & Therapeutics

111

View full text Add to dashboard Cite

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“…Intermittent high blood glucose spikes, as opposed to constant exposure to high blood glucose, has been shown to promote damaging effects [ 10 , 12 , 38 ]. Daily glucose fluctuations are incompletely expressed by HbA1c alone, particularly in patients considered to have good metabolic control or with prediabetes [ 9 , 13 , 36 , 39 , 40 ]. To date, few studies have examined the effects of RT-CGM on GV.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, evaluation of various drug types on markers of GV or MeS was not performed. Previous studies have demonstrated that an increase in oral hypoglycaemic medications may sometimes result in a drop in MAGE [ 40 ]. To better understand the clinical implications of RT-CGM on GV, future trials should closely monitor and consider medication types, doses and changes in dose over the time course of the intervention.…”

Section: Discussionmentioning

confidence: 99%

Efficacy of Real-Time Continuous Glucose Monitoring to Improve Effects of a Prescriptive Lifestyle Intervention in Type 2 Diabetes: A Pilot Study

et al. 2019

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Introduction Optimising patient adherence to prescribed lifestyle interventions to achieve improved blood glucose control remains a challenge. Combined use of real-time continuous glucose monitoring systems (RT-CGM) may promote improved glycaemic control. This pilot study examines the effects of a prescriptive lifestyle modification programme when combined with RT-CGM on blood glucose control and cardiovascular disease risk markers. Methods Twenty adults (10 men, 10 women) with obesity and type-2 diabetes (T2D) (age 60.55 ± 8.38 years, BMI 34.22 ± 4.67 kg/m 2 ) were randomised to a prescriptive low-carbohydrate diet and lifestyle plan whilst continuously wearing either an RT-CGM or an ‘offline-blinded’ monitor (control) for 12 weeks. Outcomes were glycaemic control (HbA1c, fasting glucose, glycaemic variability [GV]), diabetes medication (MeS), weight, blood pressure and lipids assessed pre- and post-intervention. Results Both groups experienced reductions in body weight (RT-CGM − 7.4 ± 4.5 kg vs. control − 5.5 ± 4.0 kg), HbA1c (− 0.67 ± 0.82% vs. − 0.68 ± 0.74%), fasting blood glucose (− 1.2 ± 1.9 mmol/L vs. − 1.0 ± 2.2 mmol/L), LDL-C (− 0.07 ± 0.34 mmol/L vs. − 0.26 ± 0.42 mmol/L) and triglycerides (− 0.32 ± 0.46 mmol/L vs. − 0.36 ± 0.53 mmol/L); with no differential effect between groups ( P ≥ 0.10). At week 12, GV indices were consistently lower by at least sixfold in RT-CGM compared to control (CONGA-1 − 0.27 ± 0.36 mmol/L vs. 0.06 ± 0.19 mmol/L; CONGA-2 − 0.36 ± 0.54 mmol/L vs. 0.05 ± 2.88 mmol/L; CONGA-4 − 0.44 ± 0.67 mmol/L vs. − 0.02 ± 0.42 mmol/L; CONGA-8 − 0.36 ± 0.61 vs. 0.02 ± 0.52 mmol/L; MAGE − 0.69 ± 1.14 vs. − 0.09 ± 0.08 mmol/L, although there was insufficient power to achieve statistical significance ( P ≥ 0.11). Overall, there was an approximately 40% greater reduction in blood glucose-lowering medication (MeS) in RT-CGM (− 0.30 ± 0.59) compared to control (0.02 ± 0.23). Conclusion This study provides preliminary evidence that RT-CGM may be an effective strategy to optimise glucose control whilst following a low-carbohydrate lifestyle programme that targets improved glycaemic control, with minimal professional support. Trial Registration Australian New Zealand Clinical Trials Registry identifier, ANZTR: 372898. Funding Grant funding was received for the delivery of the clinical trial only, by the Diabetes Australia Research Trust (DART). Electronic supplementary material The online version of this article (10.1007/s13300-019-0572-z) contains supplementary material, which is available to authorized users.

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“…Type 2 diabetes (T2D) affects 30.3 million people (~ 9.4% of the population) in the USA as of 2017 [ 1 ]. The economic and social costs of T2D are considerable because of its associated serious short- and long-term complications, particularly in patients who do not achieve and/or maintain glycemic control [ 2 , 3 ], as well as its significant contribution to overall mortality (approximately 12% of all deaths) [ 4 ]. Hyperglycemia, which may result from insufficient treatment intensification, significantly increases the risks of microvascular complications, such as retinopathy and nephropathy, as well as macrovascular complications including myocardial infarction, heart failure, stroke, and their composite [ 3 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

Probability of Achieving Glycemic Control with Basal Insulin in Patients with Type 2 Diabetes in Real-World Practice in the USA

et al. 2018

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IntroductionBasal insulin (BI) plays an important role in treating type 2 diabetes (T2D), especially when oral antidiabetic (OAD) medications are insufficient for glycemic control. We conducted a retrospective, observational study using electronic medical records (EMR) data from the IBM® Explorys database to evaluate the probability of achieving glycemic control over 24 months after BI initiation in patients with T2D in the USA.MethodsA cohort of 6597 patients with T2D who started BI following OAD(s) and had at least one valid glycated hemoglobin (HbA1c) result recorded both within 90 days before and 720 days after BI initiation were selected. We estimated the changes from baseline in HbA1c every 6 months, the quarterly conditional probabilities of reaching HbA1c < 7% if a patient had not achieved glycemic control prior to each quarter (Q), and the cumulative probability of reaching glycemic control over 24 months.ResultsOur cohort was representative of patients with T2D who initiated BI from OADs in the USA. The average HbA1c was 9.1% at BI initiation, and decreased robustly (1.5%) in the first 6 months after initiation with no further reductions thereafter. The conditional probability of reaching glycemic control decreased rapidly in the first year (26.6% in Q2; 17.6% in Q3; 8.6% in Q4), and then remained low (≤ 6.1%) for each quarter in the second year. Cumulatively, about 38% of patients reached HbA1c < 7% in the first year; only approximately 8% more did so in the second year.ConclusionOur study of real-world data from a large US EMR database suggested that among patients with T2D who initiated BI after OADs, the likelihood of reaching glycemic control diminished over time, and remained low from 12 months onwards. Additional treatment options should be considered if patients do not reach glycemic control within 12 months of BI initiation.FundingSanofi Corporation.

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Minimizing Glycemic Fluctuations in Patients with Type 2 Diabetes: Approaches and Importance

Cited by 54 publications

References 61 publications

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

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

Efficacy of Real-Time Continuous Glucose Monitoring to Improve Effects of a Prescriptive Lifestyle Intervention in Type 2 Diabetes: A Pilot Study

Probability of Achieving Glycemic Control with Basal Insulin in Patients with Type 2 Diabetes in Real-World Practice in the USA

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