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In a randomized controlled trial including 340 people living with obesity, with and without type 2 diabetes, digital coaching has induced significant long-term weight loss compared to the usual methods of care. We investigated whether education level influenced this weight loss and which lifestyle changes supported the digital lifestyle coaching program. The intervention consisted of a 1 h face-to-face motivational interview followed by digital coaching using behavioral change techniques. At 6 months, the weight loss in the intervention group was significantly larger in participants with short education (6.0 vs. 2.2 kg, p < 0.01) (p = 0.006). Participants with long education experienced initially a modest weight loss, but the effect was maintained, leading to the largest weight loss at 24 months (5.06 [−11.98–1.86] kg), even though there were fewer coaching sessions in the maintenance period. In multiple regression analyses, the greater weight loss in the intervention group was associated with short education (β = 1.81, p = 0.02), improvements in everyday physical activity (β = 2.60, p = 0.014) and improvements in dietary habits (β = 3.84, p = 0.013). In conclusion, at 6 months, the effect of the intervention was more pronounced in people with short education through improvements in everyday physical activity and dietary habits. However, participants with long education sustained their weight loss at 24 months. [ABSTRACT FROM AUTHOR]

Purpose: To estimate if newly diagnosed patients with different subphenotypes of type 2 diabetes (T2DM) or latent autoimmune diabetes of adults (LADA) differ with respect to subclinical retinal microvascular structure or diabetic retinopathy (DR). Methods: This population‐based, cross‐sectional study of 340 patients (675 eyes) classified patients with recently diagnosed T2DM in different subphenotypes according to beta cell function and insulin sensitivity in to; classical (n = 218), hyperinsulinaemic (n = 86), insulinopenic (n = 20), or LADA (n = 16). Retinal 6‐field images were graded according to the International Clinical DR Severity Scale by a retinal expert. Retinal microvascular structures were analysed in eyes by a semiautomatic software. Results: Median age and duration of diabetes were 58.1 (49.9; 65.5) and 0.9 (0.5; 2.4) years, respectively, and 56.8% were male. In a multivariate linear mixed model regression analysis of eyes without DR (n = 570), there was no statistically significant difference in retinal venular or arteriolar width between subtypes and patients with classical T2DM. In addition, eyes from different subphenotypes did not differ according to vessel density, tortuosity or fractal dimension. In a multivariate logistic regression model adjusted for age, sex, HbA1c, diabetes duration, body mass index, mean arterial blood pressure and history of cardiovascular disease, there was a tendency towards persons with hyperinsulinaemic T2DM to be more likely to have DR (OR 1.97, 95% CI 0.95; 4.09) compared to classical T2DM. Conclusion: We found no difference in retinal microvascular structure in patients with newly diagnosed subtypes of T2DM. However, DR may be more prevalent in newly diagnosed patients with hyperinsulinaemic T2DM compared to individuals with classical T2DM. [ABSTRACT FROM AUTHOR]

Background: Digital health interventions are increasingly used to handle and promote positive health behaviors. Clinical measures are often used, and a certain precision is essential for digital health interventions to have an effect. Only few studies have compared clinically measured weights with self-reported weights. No study has examined the validity of self-reported weight from a mobile app used in a tailored weight loss intervention. Objective: The aim of this study was to analyze the agreement between clinically measured weight and self-reported weight collected from a mobile health lifestyle coaching program during a 12-month weight loss intervention for obese patients with and without type 2 diabetes. The secondary aim was to investigate the determinants for possible discrepancies between clinically measured and self-reported weights of these patients with different demographic and lifestyle characteristics and achievements of weight loss goals. Methods: Weight registrations were collected from participants (N=104) in a Danish randomized controlled trial examining the effect of a digital lifestyle intervention on weight loss among obese patients with and without type 2 diabetes. Data were collected at baseline and after 6 and 12 months. Self-reported weight was measured at home and registered in the app. Results: Self-reported body weight was lower than the weight measured in the clinic after 6 months by 1.03 kg (95% CI 1.01-1.05; P<.001) and after 12 months also by 1.03 kg (95% CI 0.99-1.04; P<.001). After 6 months, baseline weight and BMI were associated with a discrepancy of 0.03 kg (95% CI 0.01-0.04; P=.01) and 0.09 kg (95% CI 0.02-0.17; P=.02) per increment of 1 kg and 1 kg/m2, respectively, between clinically measured weight and self-reported weight. Weight change during the first 6 months was also associated with a difference of 0.1 kg (95% CI 0.04-0.01; P<.001) per kilogram of difference in weight between clinically measured weight and self-reported weight. Participants who did not achieve the 5% weight loss goal underestimated their weight by 0.79 kg (95% CI 0.34-1.23) at 6 months. After 12 months, only baseline weight was associated with a discrepancy of 0.03 kg (95% CI 0.01-0.05; P=.02) per increment of kilogram between clinically measured weight and self-reported weight. None of the other factors showed any significant discrepancy after 12 months. Conclusions: Self-reported weight obtained from mobile health is a valid method for collecting anthropometric measurements. [ABSTRACT FROM AUTHOR]

Objective: Hyperglycaemia in type 2 diabetes is caused by varying degrees of two defects: low insulin sensitivity and beta-cell dysfunction. We assessed if subgrouping of patients into three pathophysiological phenotypes according to these defects could identify individuals with high or low risk of future cardiovascular events. Design: This is a prospective cohort study. Methods: We assessed estimates of insulin sensitivity and beta-cell function from the homeostasis model assessment-2 in 4209 individuals with recently diagnosed type 2 diabetes enrolled from general practitioners and outpatient clinics in Denmark. Individuals were followed for a composite cardiovascular endpoint (either atherosclerotic outcomes (myocardial infarction, unstable angina pectoris, stroke, coronary or peripheral revascularization), heart failure, or cardiovascular death) and all-cause mortality. Results: Totally 417 individuals with the insulinopenic phenotype (high insulin sensitivity and low beta-cell function) had substantially lower risk of cardiovascular events (5-year cumulative incidence: 4.6% vs 10.1%; age-/sex-adjusted hazard ratio (aHR): 0.49; 95% CI: 0.30-0.82) compared with 2685 individuals with the classical phenotype (low insulin sensitivity and low beta-cell function), driven by atherosclerotic events. Conversely, 1107 individuals with the hyperinsulinaemic phenotype (low insulin sensitivity and high beta-cell function) had more cardiovascular events (5-year cumulative incidence: 12.6%; aHR: 1.33; 95% CI: 1.05-1.69), primarily driven by increased heart failure and cardiovascular death and increased all-cause mortality. Conclusions: Simple phenotyping based on insulin sensitivity and beta-cell function predicts distinct future risks of cardiovascular events and death in patients with type 2 diabetes. These results suggest that precision medicine according to underlying type 2 pathophysiology potentially can reduce diabetes complications. [ABSTRACT FROM AUTHOR]

Aims: To determine whether a strategy of intensive blood pressure control reduces the risk of heart failure (HF) events consistently across the spectrum of kidney function and albuminuria. Methods and results: SPRINT was a randomized clinical trial in which 9361 individuals ≥50 years, at high risk for or with cardiovascular disease, a systolic blood pressure of 130–180 mmHg, but without diabetes, were randomized to intensive (target <120 mmHg) vs. standard (target <140 mmHg) blood pressure control. We assessed whether estimated glomerular filtration rate (eGFR) and urine albumin‐to‐creatinine ratio (UACR) modified the effects of the blood pressure control strategy in reducing HF events (either hospitalization or emergency department visits) and the composite of HF events or cardiovascular death, using Cox proportional hazards regression and restricted cubic splines. Of the 9361 individuals included in SPRINT, eGFR and UACR were available for 9324 (99.6%) and 8913 (95.2%) subjects, respectively, including 2650 (28.4%) with eGFR <60 mL/min/1.73 m2 and 248 (2.8%) with UACR >300 mg/g. During a median follow‐up of 3.2 years (range 0–4.8 years), 160 (1.8%) participants had HF events and 233 (2.6%) had HF events or cardiovascular death. Risks of HF events or cardiovascular death increased from 0.42 (0.34–0.53) per 100 patient‐years in patients with eGFR ≥60 mL/min/1.73 m2 and UACR <30 mg/g to 4.55 (3.00–6.91) per 100 patient‐years in patients with eGFR <60 mL/min/1.73 m2 and UACR >300 mg/g. A similar gradient was observed for HF events alone. Both eGFR and UACR were independently, non‐linearly associated with HF hospitalization and HF hospitalization or cardiovascular death (test for overall trend, P < 0.001). While the effects of intensive blood pressure control on HF event risk appeared to attenuate at lower eGFR and higher UACR, there was no significant interaction between eGFR or UACR and blood pressure control strategy (continuous and categorical interaction P > 0.05). Conclusion: In SPRINT, eGFR and albuminuria were strong and additive determinants in forecasting HF risk. The effect of intensive blood pressure control in decreasing HF risk did not significantly vary across the spectrum of kidney function or albuminuria. Multidisciplinary pathways, incorporating blood pressure control, are needed for at‐risk patients with chronic kidney disease to attenuate HF risk. Trial Registration: ClinicalTrials.gov Identifier NCT01206062. [ABSTRACT FROM AUTHOR]

Introduction: We present the protocol for a multifactorial intervention study designed to test whether individualised treatment, based on pathophysiological phenotyping and individualised treatment goals, improves type 2 diabetes (T2D) outcomes. Methods and analysis: We will conduct a prospective controlled multicentre open-label intervention study, drawing on the longitudinal cohort of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2). New clinically diagnosed patients with T2D in the intervention group will be assigned to receive individualised treatment by their general practitioner. Intervention patients will be compared with a matched control cohort of DD2 patients receiving routine clinical care. Among intervention patients, we will first do pathophysiological phenotyping to classify patients into WHO-defined T2D or other specific types of diabetes (monogenic diabetes, secondary diabetes etc). Patients with WHO-defined T2D will then be further subcharacterised by their beta-cell function (BCF) and insulin sensitivity (IS), using the revised homeostatic assessment model, as having either insulinopaenic T2D (high IS and low BCF), classical T2D (low IS and low BCF) or hyperinsulinaemic T2D (low IS and high BCF). For each subtype, a specific treatment algorithm will target the primary pathophysiological defect. Similarly, antihypertensive treatment will be targeted at the specific underlying pathophysiology, characterised by impedance cardiography (relative importance of vascular resistance, intravascular volume and cardiac inotropy). All treatment goals will be based on individual patient assessment of expected positive versus adverse effects. Web-based and face-to-face individualised lifestyle intervention will also be implemented to empower patients to make a sustainable improvement in daily physical activity and to change to a low-carbohydrate diet. Ethics and dissemination: The study will use well-known pharmacological agents according to their labels; patient safety is therefore considered high. Study results will be published in international peer-reviewed journals. [ABSTRACT FROM AUTHOR]

Background: Long-term weight loss in people living with obesity can reduce the risk and progression of noncommunicable diseases. Observational studies suggest that digital coaching can lead to long-term weight loss.Objective: We investigated whether an eHealth lifestyle coaching program for people living with obesity with or without type 2 diabetes led to significant, long-term (12-month) weight loss compared to usual care.Methods: In a randomized controlled trial that took place in 50 municipalities in Denmark, 340 people living with obesity with or without type 2 diabetes were enrolled from April 16, 2018, to April 1, 2019, and randomized via an automated computer algorithm to an intervention (n=200) or a control (n=140) group. Patients were recruited via their general practitioners, the Danish diabetes organization, and social media. The digital coaching intervention consisted of an initial 1-hour face-to-face motivational interview followed by digital coaching using behavioral change techniques enabled by individual live monitoring. The primary outcome was change in body weight from baseline to 12 months.Results: Data were assessed for 200 participants, including 127 from the intervention group and 73 from the control group, who completed 12 months of follow-up. After 12 months, mean body weight and BMI were significantly reduced in both groups but significantly more so in the intervention group than the control group (-4.5 kg, 95% CI -5.6 to -3.4 vs -1.5 kg, 95% CI -2.7 to -0.2, respectively; P<.001; and -1.5 kg/m2, 95% CI -1.9 to -1.2 vs -0.5 kg/m2, 95% CI -0.9 to -0.1, respectively; P<.001). Hemoglobin A1c was significantly reduced in both the intervention (-6.0 mmol/mol, 95% CI -7.7 to -4.3) and control (-4.9 mmol/mol, 95% CI -7.4 to -2.4) groups, without a significant group difference (all P>.46).Conclusions: Compared to usual care, digital lifestyle coaching can induce significant weight loss for people living with obesity, both with and without type 2 diabetes, after 12 months.Trial Registration: ClinicalTrials.gov NCT03788915; https://clinicaltrials.gov/ct2/show/NCT03788915. [ABSTRACT FROM AUTHOR]