XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

Introduction Diabetes mellitus (DM) is a leading cause of morbidity and mortality worldwide. At the same time, digital health technologies (DHTs), which include mobile health apps (mHealth) have been rapidly gaining popularity in the self-management of chronic diseases, particularly following the COVID-19 pandemic. However, while a great variety of DM-specific mHealth apps exist on the market, the evidence supporting their clinical effectiveness is still limited. Methods A systematic review was performed. A systematic search was conducted in a major electronic database to identify randomized controlled trials (RCTs) of mHealth interventions in DM published between June 2010 and June 2020. The studies were categorized by the type of DM and impact of DM-specific mHealth apps on the management of glycated haemoglobin (HbA1c) was analysed. Results In total, 25 studies comprising 3,360 patients were included. The methodological quality of included trials was mixed. Overall, participants diagnosed with T1DM, T2DM and Prediabetes all demonstrated greater improvements in HbA1c as a result of using a DHT compared with those who experienced usual care. The analysis revealed an overall improvement in HbA1c compared with usual care, with a mean difference of –0.56% for T1DM, –0.90% for T2DM and –0.26% for Prediabetes. Conclusion DM-specific mHealth apps may reduce HbA1c levels in patients with T1DM, T2DM and Prediabetes. The review highlights a need for further research on the wider clinical effectiveness of diabetes-specific mHealth specifically within T1DM and Prediabetes. These should include measures which go beyond HbA1c, capturing outcomes including short-term glycemic variability or hypoglycemic events.

/pdf/the-effectiveness-of-digital-health-technologies-for-2sycnq4d.pdf

The effectiveness of digital health technologies for patients with diabetes mellitus: A systematic review

Objective. To compare mean basal metabolic rate (BMR) estimated using Harris-Benedict equation (HB) and Bioelectrical Impedance Analysis (BIA) and the BMR measured using Indirect Calorimetry (IC) among adult obese Filipino patients with prediabetes or type 2 diabetes mellitus (T2DM). Methodology. This was a multi-center, cross-sectional study based on review of outpatient medical records of adult, obese Filipino patients with pre-diabetes or type 2 diabetes mellitus who were seen prior to weight loss intervention at the Outpatient Clinic of St. Luke’s Medical Center-Quezon City and the Metabolic and Diabetes Center of Providence Hospital from August 2017 to January 2018. BMR was derived using three methods: Harris-Benedict equation, Bioelectrical Impedance Analysis and Indirect Calorimetry. Results. A total of 153 subjects were included in the study. Eighty subjects (52%) have pre-diabetes while 73 subjects (48%) were diagnosed with T2DM. The mean BMR measured using IC is 1299±252 kcal/day while estimated mean BMR predicted using HB equation and BIA were 1628±251 kcal/day and 1635+260 kcal/day, respectively. Compared to measurement by IC, HBE and BIA significantly overestimated the mean BMR by 329 and 336 kcal/day, respectively ( p value =<0.0001). IC measured BMR showed strong positive correlation with weight and moderate positive correlation with height. Multiple stepwise regression analysis yielded the BMR prediction equation: BMR (kcal/day)=-780.806 + (11.108 x weight in kg) + (7.164 x height in cm). Conclusion. Among obese Filipinos with T2DM or prediabetes, HB equation and BIA tend to overestimate the BMR measured using IC.

/pdf/comparison-of-the-harris-benedict-equation-bioelectrical-qz28oxtnln.pdf

Comparison of the Harris-Benedict Equation, Bioelectrical Impedance Analysis, and Indirect Calorimetry for Measurement of Basal Metabolic Rate among Adult Obese Filipino Patients with Prediabetes or Type 2 Diabetes Mellitus

AIMS To compare time in range (TIR) with use of insulin degludec U100 (degludec) versus insulin glargine U100 (glargine U100) in people with type 2 diabetes. MATERIALS AND METHODS We conducted a randomized, crossover, multicentre trial comparing degludec and glargine U100 in basal insulin-treated adults with type 2 diabetes and ≥1 hypoglycaemia risk factor. There were two treatment periods, each with 16-week titration and 2-week maintenance phases (with evaluation of glucose using blinded professional continuous glucose monitoring). The once-weekly titration (target: 3.9-5.0 mmol/L) was based on pre-breakfast self-measured blood glucose. The primary endpoint was percentage of TIR (3.9─10.0 mmol/L). Secondary endpoints included overall and nocturnal percentage of time in tight glycaemic range (3.9-7.8 mmol/L), and mean glycated haemoglobin (HbA1c) and glucose levels. RESULTS At baseline, participants (n = 498) had a mean (SD) age of 62.8 (9.8) years, a diabetes duration of 15.1 (7.7) years and an HbA1c level of 59.6 (11.0) mmol/mol (7.6 [1.0]%). Noninferiority and superiority were confirmed for degludec versus glargine U100 for the primary endpoint, with a mean TIR of 72.1% for degludec versus 70.7% for glargine U100 (estimated treatment difference [ETD] 1.43% [95% confidence interval (CI): 0.12, 2.74; P = 0.03] or 20.6 min/d). Overall time in tight glycaemic range favoured degludec versus glargine U100 (ETD 1.5% [95% CI: 0.15, 2.89] or 21.9 min/d). Degludec also reduced nocturnal time below range (TBR; <3.9 mmol/L) compared with glargine U100 (ETD -0.88% [95% CI: -1.34, -0.42] or 12.7 min/night; post hoc) and significantly fewer nocturnal hypoglycaemic episodes of <3.0 mmol/L were observed. CONCLUSIONS Degludec, compared with glargine U100, provided more TIR and time in tight glycaemic range, and reduced nocturnal TBR in insulin-treated people with type 2 diabetes.

Effect of insulin degludec versus insulin glargine U100 on time in range: SWITCH PRO, a crossover study of basal insulin-treated adults with type 2 diabetes and risk factors for hypoglycaemia.

Several pathophysiological mechanisms would suggest a causal link between hypoglycaemia and cardiovascular death; conversely, current knowledge would not support a causal relationship with other causes of death. To clarify the nature and the magnitude of the association between hypoglycaemia and death, we investigated the 5 year mortality risks for cardiovascular disease, cancer and other causes in individuals with type 2 diabetes admitted to hospital for a severe hypoglycaemic episode. We defined in the UK Clinical Practice Research Datalink database a prevalent cohort of adults with type 2 diabetes diagnosed between 1 January 1998 and 1 January 2011 (index date), with available linkage to the Office for National Statistics (ONS) and the Hospital Episode Statistics (HES). A hospital admission reporting hypoglycaemia as the underlying cause was identified before the index date in the HES; date and underlying cause of death were obtained from the ONS. We quantified the 5 year risk of cause-specific death in people with and without admission to hospital for severe hypoglycaemia, adjusting for potential confounders and accounting for competing risk. Of the 74,610 subjects included in the cohort, 388 (0.5%) were admitted at least once for a severe hypoglycaemic episode; subjects admitted were older, with higher HbA1c and a greater prevalence of multimorbidity. During a median follow-up of 7.1 years, 236 (60.8%) and 18,539 (25.0%) deaths occurred in subjects with and without a previous severe hypoglycaemia, respectively. Non-cardiovascular causes accounted for 71% of all deaths in both subjects with and without hypoglycaemia. In a 60-year-old person with severe hypoglycaemia, the 5 year absolute risk of death, adjusted for age, sex, ethnicity, systolic blood pressure, total cholesterol, HbA1c, BMI, eGFR, smoking status, alcohol consumption and deprivation (Townsend score), was 6.6%, 1.1% and 13.1% for cardiovascular, cancer and other causes, respectively, while the 5 year absolute risk difference compared with a subject without severe hypoglycaemia was 4.7% (95% CI 1.0, 8.3) for cardiovascular, −1.4% (−4.1, 1.4) for cancer and 11.1% (6.1, 16.1) for other causes of death. Results were consistent in models further adjusted for medications and comorbidities (myocardial infarction, stroke, peripheral artery disease, heart failure, atrial fibrillation, cancer), with sulfonylurea and insulin associated with increased mortality rates (from cause-specific hazard ratio of 1.06 [95% CI 0.99, 1.14] for cancer death with use of sulfonylurea to 1.42 [1.29, 1.56] for cardiovascular death with use of insulin). Results were robust to missing data. The results of this study indicate severe hypoglycaemia as a marker of, rather than causally linked to, an increased risk of long-term mortality. Regardless of the nature of the association, a severe hypoglycaemic episode represents a strong negative prognostic factor in patients with type 2 diabetes.

/pdf/severe-hypoglycaemia-and-absolute-risk-of-cause-specific-hrwt7zgv13.pdf

Severe hypoglycaemia and absolute risk of cause-specific mortality in individuals with type 2 diabetes: a UK primary care observational study

The study aimed to determine the relationships between the basal metabolic rate (BMR) and body composition of overweight and obese Chinese adults with type 2 diabetes mellitus (DM). This cross-sectional clinical study enrolled 193 Chinese adults with type 2 DM who were overweight (24 kg/m(2)=BMI≤28 kg/m(2), n=99), or obese (BMI ≥28 kg/m(2), n=94). Ninety-seven adults with normal BMIs, including 50 DM patients and 47 healthy adults, were recruited as a control group. BMR was measured by indirect calorimetry; predicted BMR was calculated according to the Schofield equation; and the relationships between BMR, body composition, and biochemical results were determined by the Pearson correlation. The results showed that obese DM patients had significantly higher BMRs than both overweight patients (P<0.05) and patients with normal BMI did (P<0.05). The measured BMR was significantly lower than the predicted BMR (P<0.05) in all groups. Obese and overweight DM patients had significantly greater weight, waist circumference, hip circumference, BMI, body surface area, body fat percentage, fat mass, and fat-free mass than patients with normal BMI. Except for waist circumference, these body composition measurements were significantly increased in obese DM patients when compared with those in overweight DM patients (P<0.05). Fat-free mass was closely correlated with BMR in both DM patients (r=0.874, P<0.01) and in healthy controls (r=0.902, P<0.01). It was concluded that overweight and obese Chinese adults with type 2 DM had increased BMRs compared with normal-weight controls, which may result from the difference in fat-free mass.

Increased BMR in overweight and obese patients with type 2 diabetes may result from an increased fat-free mass.

Objective: Hypoglycemia has been shown to promote inflammation, a common pathogenic process, in many chronic health conditions including diabetes and cardiovascular disease. The aim of this study was to investigate the association of hypoglycemia, assessed by continuous glucose monitoring (CGM) with major adverse cardiovascular event (MACE) outcomes and all-cause mortality. Methods: A retrospective cohort study was conducted with 1,520 patients with type 2 diabetes mellitus (T2DM). The severity of hypoglycemia event was assessed by CGM system. Results: Three hundred and forty-seven participants experienced hypoglycemia events (323 with mild hypoglycemia and 24 with severe hypoglycemia). A fraction of 72.62% hypoglycemia was asymptomatic. During a median follow-up of 31 months, 380 participants reached the primary outcome of MACE (61 cardiovascular death, 50 non-fatal myocardial infarction [MI], 116 non-fatal stroke, 153 unstable angina requiring hospitalization), 80 participants died before the end of the study. In multivariate Cox regression models, hypoglycemia was associated with cardiovascular death (HR 2.642[95CI% 1.398-4.994]), non-fatal stroke (HR 1.813 [95CI% 1.110-2.960]) and all-cause mortality (HR 1.960 [95 CI% 1.124- 3.418]) after the full adjustment. Hypoglycemia was not associated with non-fatal MI and unstable angina. The HR of severe hypoglycemia was higher than mild hypoglycemia for cardiovascular death. Patients with symptomatic and asymptomatic hypoglycemia had similar MACE outcomes and all-cause mortality. Conclusions: CGM is effective to detect asymptomatic and nocturnal hypoglycemia. Hypoglycemia is associated with an increased risk of non-fatal stroke, cardiovascular related death, and total mortality. The cardiovascular mortality is dose-dependent on the severity of hypoglycemia.

/pdf/the-association-of-hypoglycemia-assessed-by-continuous-4sitn9v28s.pdf

The Association of Hypoglycemia Assessed by Continuous Glucose Monitoring With Cardiovascular Outcomes and Mortality in Patients With Type 2 Diabetes.

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Increased BMR in overweight and obese patients with type 2 diabetes may result from an increased fat-free mass.

The Association of Hypoglycemia Assessed by Continuous Glucose Monitoring With Cardiovascular Outcomes and Mortality in Patients With Type 2 Diabetes.