Effect of applying a diabetes risk score on lifestyle counselling and shared decision-making in primary care: A pragmatic cluster randomised trial.

Aims: There is a lack of studies on the impact of diabetes risk scores on diabetes prevention. The aim of this study was to investigate the effect of applying a non-invasive diabetes risk score as component of routine health checks on counselling intensity and shared decision-making (SDM) in primary care.

Methods: Cluster randomised trial, in which primary care physicians (n = 30) enrolled participants (n = 315) with statutory health insurance without known diabetes, ≥ 35 years of age with a body mass index (BMI) ≥ 27.

Built-in selection or confounder bias? Dynamic Landmarking in matched propensity score analyses.

Background: Propensity score matching has become a popular method for estimating causal treatment effects in non-randomized studies. However, for time-to-event outcomes, the estimation of hazard ratios based on propensity scores can be challenging if omitted or unobserved covariates are present. Not accounting for such covariates could lead to treatment estimates, differing from the estimate of interest.

The potential of precision diabetology for type 2 diabetes treatment-evidence from a meta-regression for all-cause mortality from large cardiovascular outcome trials.

Aims: Two prerequisites must be met for the precision treatment approach to be beneficial for treated individuals. First, there must be treatment heterogeneity; second, in case of treatment heterogeneity, clinical predictors to identify people who would benefit from one treatment more than from others must be available. There is an established meta-regression approach to assess these two prerequisites that relies on measuring the variability of a clinical outcome after treatment in placebo-controlled randomised trials.

Optimising the treatment of chronic ischemic heart disease by training general practitioners to deliver very brief advice on physical activity (OptiCor): protocol of the systematic development and evaluation of a complex intervention.

Background: Chronic ischemic heart disease (IHD) is one of the leading causes of morbidity and mortality. Physical activity (PA) is an effective secondary preventive strategy in IHD management. The German treatment guideline recommends that general practitioners (GPs) deliver PA advice to patients.

Evaluation of spatiotemporal associations between COVID-19 pandemic waves and the incidence of pediatric type 1 diabetes in Germany considering time lags: A register-based ecological study.

To analyze the ecological relationship between COVID-19 incidence in the total population and type 1 diabetes (T1D) incidence in children and adolescents, spatiotemporal models were applied considering time lags from 0 to 12 months. The results do not indicate a positive correlation between COVID-19 incidence and T1D incidence.

Modeling Chronic Disease Mortality by Methods From Accelerated Life Testing.

We propose a parametric model for describing chronic disease mortality from cohort data and illustrate its use for Type 2 diabetes. The model uses ideas from accelerated life testing in reliability theory and conceptualizes the occurrence of a chronic disease as putting the observational unit to an enhanced stress level, which is supposed to shorten its lifetime. It further addresses the issue of semi-competing risk, that is, the asymmetry of death and diagnosis of disease, where the disease can be diagnosed before death, but not after.

A discrete time-to-event model for the meta-analysis of full ROC curves.

The development of new statistical models for the meta-analysis of diagnostic test accuracy studies is still an ongoing field of research, especially with respect to summary receiver operating characteristic (ROC) curves. In the recently published updated version of the "Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy", the authors point to the challenges of this kind of meta-analysis and propose two approaches. However, both of them come with some disadvantages, such as the nonstraightforward choice of priors in Bayesian models or the requirement of a two-step approach where parameters are estimated for the individual studies, followed by summarizing the results.

A re-analysis of about 60,000 sparse data meta-analyses suggests that using an adequate method for pooling matters.

In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing meta-analyses from the Cochrane Database of Systematic Reviews in scenarios with zero event trials and few trials.

Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet is associated with lower visceral and hepatic lipid content in recent-onset type 1 diabetes and type 2 diabetes.

Aim: To investigate the associations of the Dietary Approaches to Stop Hypertension (DASH) score with subcutaneous (SAT) and visceral (VAT) adipose tissue volume and hepatic lipid content (HLC) in people with diabetes and to examine whether changes in the DASH diet were associated with changes in these outcomes.

Methods: In total, 335 participants with recent-onset type 1 diabetes (T1D) and type 2 diabetes (T2D) from the German Diabetes Study were included in the cross-sectional analysis, and 111 participants in the analysis of changes during the 5-year follow-up. Associations between the DASH score and VAT, SAT and HLC and their changes were investigated using multivariable linear regression models by diabetes type.

Balancing versus modelling in weighted analysis of non-randomised studies with survival outcomes: A simulation study.

Weighting methods are widely used for causal effect estimation in non-randomised studies. In general, these methods use the propensity score (PS), the probability of receiving the treatment given the covariates, to arrive at the respective weights. All of these "modelling" methods actually optimize prediction of the respective outcome, which is, in the PS model, treatment assignment.

A nonparametric proportional risk model to assess a treatment effect in time-to-event data.

Time-to-event analysis often relies on prior parametric assumptions, or, if a semiparametric approach is chosen, Cox's model. This is inherently tied to the assumption of proportional hazards, with the analysis potentially invalidated if this assumption is not fulfilled. In addition, most interpretations focus on the hazard ratio, that is often misinterpreted as the relative risk (RR), the ratio of the cumulative distribution functions.

Mortality of type 2 diabetes in Germany: additional insights from Gompertz models.

Aims: The Gompertz law of mortality proclaims that human mortality rates in middle to old ages grow log-linearly with age and this law has been confirmed at multiple instances. We investigated if diabetes mortality in Germany also obeys to the Gompertz law and how this information helps to communicate diabetes mortality more intuitively.

Methods: We analyzed all statutory health-insured persons in Germany in 2013 that were aged 30 years or older.

Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta-regression analysis of 120 randomized controlled trials.

Aims: To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability.

Methods: We used randomized clinical trials (RCTs) comparing glucose-lowering drugs (including but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.

A parametric additive hazard model for time-to-event analysis.

Background: In recent years, the use of non- and semi-parametric models which estimate hazard ratios for analysing time-to-event outcomes is continuously criticized in terms of interpretation, technical implementation, and flexibility. Hazard ratios in particular are critically discussed for their misleading interpretation as relative risks and their non-collapsibility. Additive hazard models do not have these drawbacks but are rarely used because they assume a non- or semi-parametric additive hazard which renders computation and interpretation complicated.

Absolute treatment effects of novel antidiabetic drugs on a composite renal outcome: meta-analysis of digitalized individual patient data.

Background: Absolute treatment benefits-expressed as numbers needed to treat-of the glucose lowering and cardiovascular drugs, glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose transporter 2 (SGLT2) inhibitors on renal outcomes remain uncertain. With the present meta-analysis of digitalized individual patient data, we aimed to display and compare numbers needed to treat of both drugs on a composite renal outcome.

Methods: From Kaplan-Meier plots of major cardiovascular outcome trials of GLP-1 receptor agonists and SGLT2 inhibitors vs.

Spatiotemporal association between COVID-19 incidence and type 1 diabetes incidence among children and adolescents: a register-based ecological study in Germany.

Objective: Studies have shown an increased incidence of pediatric type 1 diabetes during the COVID-19 pandemic, but the detailed role of SARS-CoV-2 infection in the incidence increase in type 1 diabetes remains unclear. We investigated the spatiotemporal association of pediatric type 1 diabetes and COVID-19 incidence at the district level in Germany.

Methods: For the period from March 2020 to June 2022, nationwide data on incident type 1 diabetes among children and adolescents aged <20 years and daily documented COVID-19 infections in the total population were obtained from the German Diabetes Prospective Follow-up Registry and the Robert Koch Institute, respectively.

Synergism between coexisting eye diseases and sex in increasing the prevalence of the dry eye syndrome.

The aim was to investigate prevalence of dry eye syndrome (DES) in a population-based sample in Germany. The association between coexisting eye diseases and DES was also of interest. We recontacted participants of the Heinz Nixdorf Recall study between 2018 and 2021 by postal questionnaire that included the Women's Health Study questionnaire on DES.

Efficacy of automated insulin delivery (AID) systems in type 1 diabetes: protocol of a systematic review and network meta-analysis of outpatient randomised controlled trials.

Introduction: Automated insulin delivery (AID), also known as artificial pancreas system or 'closed-loop system', represents a novel option for current treatments for type 1 diabetes (T1D). The objective of this systematic review and meta-analysis is to assess the efficacy of AID systems in comparison with current intensified insulin therapy for glycaemic control and patient-reported outcomes in individuals with T1D.

Methods And Analysis: Studies will be eligible if they are randomised controlled trials (RCTs) in people with T1D of all ages, and if they compare an AID system for self-administration during the day and night period with any other type of insulin therapy for at least 3 weeks.

The mediating role of obesity on the prospective association between urinary sucrose and diabetes incidence in a sub-cohort of the EPIC-Norfolk.

Background/objectives: Findings from epidemiological studies showed controversial findings between dietary sugar intake and the development of diabetes. Most of these studies assessed dietary sugar intake by self-reports which might be prone to bias. Urinary sucrose, an objective biomarker of sucrose intake, might provide better insights into this association.

Mediation Analysis in Medical Research.

Background: Mediation analysis addresses the question of the mechanisms by which an exposure causes an outcome. This article is intended to convey basic knowledge of statistical mediation analysis.

Methods: Selected articles and examples are used to explain the principle of mediation analysis.

An Empirical Approach to Derive Water T from Multiparametric MR Images Using an Automated Pipeline and Comparison With Liver Stiffness.

Background: Water T of the liver has been shown to be promising in discriminating the progressive forms of fatty liver diseases, inflammation, and fibrosis, yet proper correction for iron and lipid is required.

Purpose: To examine the feasibility of an empirical approach for iron and lipid correction when measuring imaging-based T and to validate this approach by spectroscopy on in vivo data.

Study Type: Retrospective.

Diabetes incidence before and after COVID-19 vaccination - Results from the German Disease Analyzer database.

Objective: We investigated whether COVID-19 vaccination had an impact on diabetes risk.

Methods: We used data of 6,198 patients (mean age 64.3 years) from the nationwide Disease Analyzer database, a representative panel of physicians' practices in Germany.

Association of a lifestyle score with cardiometabolic markers among individuals with diabetes: a cross-sectional study.

Introduction: To investigate the associations of a lifestyle score with various cardiovascular risk markers, indicators for fatty liver disease as well as MRI-determined total, subcutaneous and visceral adipose tissue mass in adults with new-onset diabetes.

Research Design And Methods: This cross-sectional analysis included 196 individuals with type 1 (median age: 35 years; median body mass index (BMI): 24 kg/m²) and 272 with type 2 diabetes (median age: 53 years; median BMI: 31 kg/m²) from the German Diabetes Study. A healthy lifestyle score was generated based on healthy diet, moderate alcohol consumption, recreational activity, non-smoking and non-obese BMI.