To recommend the local primary health-care centre or not: what importance do patients attach to initial contact quality, staff continuity and responsive staff encounters?

OBJECTIVE: This study aims to examine the circumstances associated with patients' tendencies to recommend a primary care centre, based on four hypotheses, the initial contact's quality, care relationship continuity, treatment encounter responsiveness and whether the significance of encounter responsiveness differs depending on whether the patient has been seeing a nurse or physician. DESIGN: The study is based on the patient' self-reported responses, retrieved from the Swedish National Patient Survey. The design is cross-sectional, and data were analysed using a binary logistic regression. SETTING: Data were collected from three primary healthcare centres in the region of Västra Götaland, Sweden. PARTICIPANTS: A total of 362 patients (62% females) having visited any of three publicly run healthcare centres in September 2010 constitute the analytical sample. Participants were fairly evenly distributed across all age groups. MAIN OUTCOME MEASURES: Recommendation was captured by patients' binary responses to the question: Would you recommend the visited primary healthcare centre? RESULTS: The hypotheses involving initial contact quality, care relationship continuity and treatment encounter responsiveness were supported by the analyses. The latter was strongly associated with patient tendency to recommend the primary healthcare centre. However, the profession (nurse or physician) involved in the treatment encounter made no difference for the predictive significance of encounter responsiveness for a patient's tendency to recommend the healthcare centre. CONCLUSIONS: Striving for stable and responsive patient/staff relationships and an open approach towards patients are potentially successful strategies for primary healthcare centres seeking to attract new patients and maintain current ones.

Randomized open-label trial of semaglutide and dapagliflozin in patients with type 2 diabetes of different pathophysiology.

The limited understanding of the heterogeneity in the treatment response to antidiabetic drugs contributes to metabolic deterioration and cardiovascular complications1,2, stressing the need for more personalized treatment1. Although recent attempts have been made to classify diabetes into subgroups, the utility of such stratification in predicting treatment response is unknown3. We enrolled participants with type 2 diabetes (n = 239, 74 women and 165 men) and features of severe insulin-deficient diabetes (SIDD) or severe insulin-resistant diabetes (SIRD). Participants were randomly assigned to treatment with the glucagon-like peptide 1 receptor agonist semaglutide or the sodium-glucose cotransporter 2 inhibitor dapagliflozin for 6 months (open label). The primary endpoint was the change in glycated haemoglobin (HbA1c). Semaglutide induced a larger reduction in HbA1c levels than dapagliflozin (mean difference, 8.2 mmol mol-1; 95% confidence interval, -10.0 to -6.3 mmol mol-1), with a pronounced effect in those with SIDD. No difference in adverse events was observed between participants with SIDD and those with SIRD. Analysis of secondary endpoints showed greater reductions in fasting and postprandial glucose concentrations in response to semaglutide in participants with SIDD than in those with SIRD and a more pronounced effect on postprandial glucose by dapagliflozin in participants with SIDD than in those with SIRD. However, no significant interaction was found between drug assignment and the SIDD or SIRD subgroup. In contrast, continuous measures of body mass index, blood pressure, insulin secretion and insulin resistance were useful in identifying those likely to have the largest improvements in glycaemic control and cardiovascular risk factors by adding semaglutide or dapagliflozin. Thus, systematic evaluation of continuous pathophysiological variables can guide the prediction of the treatment response to these drugs and provide more information than stratified subgroups ( NCT04451837 ).

Digital lifestyle treatment improves long-term metabolic control in type 2 diabetes with different effects in pathophysiological and genetic subgroups.

To address the unmet need for scalable solutions for lifestyle treatment, we developed a new digital method to promote behavioral change. Here we report that patients with type-2 diabetes in Sweden (n = 331) exposed to the intervention have significantly improved HbA1c during a median follow-up of 1038 days (4 mmol/mol compared with matched controls; P = 0.009). This is paralleled by reduced body weight, ameliorated insulin secretion, increased physical activity, and cognitive eating restraints. Participants with high BMI and insulin resistance have an even larger response, as have non-risk allele carriers for the FTO gene. The findings open a new avenue for scalable lifestyle management with sustained efficacy and highlight a previously unrecognized opportunity for digital precision treatment based on genetics and individual pathophysiology. ClinicalTrials.gov NCT04624321.

Effect of Digital Lifestyle Management on Metabolic Control and Quality of Life in Patients with Well-Controlled Type 2 Diabetes.

INTRODUCTION: The lack of effective, scalable solutions for lifestyle treatment is a global clinical problem, causing severe morbidity and mortality. Digital tools could enable broad utility, but long-term metabolic outcomes and the influence on quality of life are unclear. METHODS: We developed a new method for lifestyle treatment that promotes self-reflection and iterative behavioural change, provided as a digital tool, and evaluated its effect on glycaemic control in patients with type 2 diabetes with HbA1c below 52 mmol/mol (n = 297). As a secondary analysis, its effect on quality of life (using SF-12) was examined in both participants with and without diabetes (total n = 1914). The tool was evaluated during a 12-week randomization period to assess the existence of effect, with a subsequent open-label follow-up to study long-term outcomes. RESULTS: Participants were randomized to wait or access the intervention tool. The mean difference in HbA1c was 2 mmol/mol (95% CI - 4 to 0; P = 0.02) after 12 weeks in participants with type 2 diabetes. The groups were then merged to enable all participants to use the tool. The mean HbA1c reduction from baseline in patients with type 2 diabetes using the tool was 2 mmol/mol compared with matched controls (95% CI - 3 to 0; P = 0.005). In users with HbA1c above 45 mmol/mol, the mean difference between the groups was 4 mmol/mol (95% CI - 7 to - 2). The improvements were sustained during the follow-up of 1 year on average. Users of the tool also had improved quality of life from baseline to 6 months, mainly observed in non-diabetic participants. CONCLUSION: The tool does not require in-person reinforcement or increased healthcare resources, and the marginal cost is fundamentally lower than pharmacological treatment and most existing lifestyle interventions. The results therefore open a new means for self-managed lifestyle treatment with long-term metabolic efficacy that can benefit large numbers of people. TRIAL REGISTRATION: ClinicalTrials.gov NCT04624321 and NCT05006508.

Effect of self-managed lifestyle treatment on glycemic control in patients with type 2 diabetes.

The lack of effective, scalable solutions for lifestyle treatment is a global clinical problem, causing severe morbidity and mortality. We developed a method for lifestyle treatment that promotes self-reflection and iterative behavioral change, provided as a digital tool, and evaluated its effect in 370 patients with type 2 diabetes (ClinicalTrials.gov identifier: NCT04691973). Users of the tool had reduced blood glucose, both compared with randomized and matched controls (involving 158 and 204 users, respectively), as well as improved systolic blood pressure, body weight and insulin resistance. The improvement was sustained during the entire follow-up (average 730 days). A pathophysiological subgroup of obese insulin-resistant individuals had a pronounced glycemic response, enabling identification of those who would benefit in particular from lifestyle treatment. Natural language processing showed that the metabolic improvement was coupled with the self-reflective element of the tool. The treatment is cost-saving because of improved risk factor control for cardiovascular complications. The findings open an avenue for self-managed lifestyle treatment with long-term metabolic efficacy that is cost-saving and can reach large numbers of people.