Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank.

AIMS/HYPOTHESIS: The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. METHODS: From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. RESULTS: At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. CONCLUSIONS/INTERPRETATION: Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

Branched-chain amino acid levels are inversely associated with incident and prevalent chronic kidney disease in people with type 2 diabetes.

AIM: To investigate the association of plasma metabolites with incident and prevalent chronic kidney disease (CKD) in people with type 2 diabetes and establish whether this association is causal. MATERIALS AND METHODS: The Hoorn Diabetes Care System cohort is a large prospective cohort consisting of individuals with type 2 diabetes from the northwest part of the Netherlands. In this cohort we assessed the association of baseline plasma levels of 172 metabolites with incident (Ntotal = 462/Ncase = 81) and prevalent (Ntotal = 1247/Ncase = 120) CKD using logistic regression. Additionally, replication in the UK Biobank, body mass index (BMI) mediation and causality of the association with Mendelian randomization was performed. RESULTS: Elevated levels of total and individual branched-chain amino acids (BCAAs)-valine, leucine and isoleucine-were associated with an increased risk of incident CKD, but with reduced odds of prevalent CKD, where BMI was identified as an effect modifier. The observed inverse effects were replicated in the UK Biobank. Mendelian randomization analysis did not provide evidence for a causal relationship between BCAAs and prevalent CKD. CONCLUSIONS: Our study shows the intricate relationship between plasma BCAA levels and CKD in individuals with type 2 diabetes. While an association exists, its manifestation varies based on disease status and BMI, with no definitive evidence supporting a causal link between BCAAs and prevalent CKD.

The cross-sectional association between dietary total, animal, and plant-based protein intake and the prevalence and severity of depressive symptoms in Dutch adults with type 2 diabetes: The Hoorn Diabetes Care System cohort.

OBJECTIVE: This study aimed to investigate cross-sectional associations of total, animal, and plant-based protein intake and depressive symptoms in Dutch adults with type 2 diabetes (T2D). METHODS: We included 1137 individuals with T2D (aged 68.6 ± 9.0) from the Hoorn Diabetes Care System cohort. Energy-adjusted protein intake was assessed using a validated Food Frequency Questionnaire. The nine-item Patient Health Questionnaire (PHQ-9) was used to assess the prevalence of depressive symptoms (PHQ-9 ≥ 10 and/or anti-depressant use) and the severity of depressive symptoms (continuous PHQ-9 score). Associations between total, animal, and plant-based protein (quartiles) with depressive symptoms were assessed using multiple logistic and linear regression. RESULTS: Highest intake of total, animal, and plant-based protein was not associated with the prevalence of depressive symptoms, compared to lowest intake (e.g., total protein, ORQ4vsQ1:0.75, 95%CI 0.42;1.32). For the severity of depressive symptoms, highest total protein intake was significantly associated with lower PHQ-9 scores (ORQ4vsQ1:0.87, 95%CI 0.75;1.00), compared to lowest intake. Animal protein was not associated with the severity of depressive symptoms (ߠ∼ 1), while the association for plant-based protein was marginally non-significant (ßQ4vsQ1:0.88, 95%CI 0.76;1.02). CONCLUSION: In individuals with T2D, higher total protein intake was associated with reduced severity of depressive symptoms, but not with the prevalence of depressive symptoms. Further prospective research with a larger sample size is needed to confirm these associations.

The association of obesogenic environments with weight status, blood pressure, and blood lipids: A cross-sectional pooled analysis across five cohorts.

In this observational cross-sectional study, we investigated the relationship between combined obesogenic neighbourhood characteristics and various cardiovascular disease risk factors in adults, including BMI, systolic blood pressure, and blood lipids, as well as the prevalence of overweight/obesity, hypertension, and dyslipidaemia. We conducted a large-scale pooled analysis, comprising data from five Dutch cohort studies (n = 183,871). Neighbourhood obesogenicity was defined according to the Obesogenic Built-environmental CharacterisTics (OBCT) index. The index was calculated for 1000m circular buffers around participants' home addresses. For each cohort, the association between the OBCT index and prevalence of overweight/obesity, hypertension and dyslipidaemia was analysed using robust Poisson regression models. Associations with continuous measures of BMI, systolic blood pressure, LDL-cholesterol, HDL-cholesterol, and triglycerides were analysed using linear regression. All models were adjusted for age, sex, education level and area-level socio-economic status. Cohort-specific estimates were pooled using random-effects meta-analyses. The pooled results show that a 10 point higher OBCT index score was significantly associated with a 0.17 higher BMI (95%CI: 0.10 to 0.24), a 0.01 higher LDL-cholesterol (95% CI: 0.01 to 0.02), a 0.01 lower HDL cholesterol (95% CI: -0.02 to -0.01), and non-significantly associated with a 0.36 mmHg higher systolic blood pressure (95%CI: -0.14 to 0.65). A 10 point higher OBCT index score was also associated with a higher prevalence of overweight/obesity (PR = 1.03; 95% CI: 1.02 to 1.05), obesity (PR = 1.04; 95% CI: 1.01 to 1.08) and hypertension (PR = 1.02; 95% CI: 1.00 to 1.04), but not with dyslipidaemia. This large-scale pooled analysis of five Dutch cohort studies shows that higher neighbourhood obesogenicity, as measured by the OBCT index, was associated with higher BMI, higher prevalence of overweight/obesity, obesity, and hypertension. These findings highlight the importance of considering the obesogenic environment as a potential determinant of cardiovascular health.

Genomics Research of Lifetime Depression in the Netherlands: The BIObanks Netherlands Internet Collaboration (BIONIC) Project.

In this cohort profile article we describe the lifetime major depressive disorder (MDD) database that has been established as part of the BIObanks Netherlands Internet Collaboration (BIONIC). Across the Netherlands we collected data on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) lifetime MDD diagnosis in 132,850 Dutch individuals. Currently, N = 66,684 of these also have genomewide single nucleotide polymorphism (SNP) data. We initiated this project because the complex genetic basis of MDD requires large population-wide studies with uniform in-depth phenotyping. For standardized phenotyping we developed the LIDAS (LIfetime Depression Assessment Survey), which then was used to measure MDD in 11 Dutch cohorts. Data from these cohorts were combined with diagnostic interview depression data from 5 clinical cohorts to create a dataset of N = 29,650 lifetime MDD cases (22%) meeting DSM-5 criteria and 94,300 screened controls. In addition, genomewide genotype data from the cohorts were assembled into a genomewide association study (GWAS) dataset of N = 66,684 Dutch individuals (25.3% cases). Phenotype data include DSM-5-based MDD diagnoses, sociodemographic variables, information on lifestyle and BMI, characteristics of depressive symptoms and episodes, and psychiatric diagnosis and treatment history. We describe the establishment and harmonization of the BIONIC phenotype and GWAS datasets and provide an overview of the available information and sample characteristics. Our next step is the GWAS of lifetime MDD in the Netherlands, with future plans including fine-grained genetic analyses of depression characteristics, international collaborations and multi-omics studies.

Type 2 Diabetes, the Epidemic: Trends in Prevalence and Incidence, 2004-2020.

Aims/Hypothesis: Only a few studies reported the incidence of type 2 diabetes (T2D). Understanding recent trends in diabetes is vital for planning future diabetes care. This study updated national trends in the prevalence and incidence of type 2 diabetes (T2D) in the Netherlands from 2004-2020. Methods: The DIAbetes, MANagement and Treatment (DIAMANT) cohort was used. A cross-sectional design with yearly measurements for the study period was used. The prevalence was calculated by dividing the total number of people with T2D by the total number of all residents. The incidence was calculated by dividing new cases of T2D by the resident population at risk during the calendar year of interest. Results: Among men, the prevalence of T2D in the Netherlands increased from 2.3% in 2004 to 6.3% in 2020. Women's prevalence increased from 2.3% in 2004 to 5.3% in 2020. During 2005-2009, the incidence rate for both men and women was relatively stable Between 2010 and 2020, the incidence rate fell about 1.5 per 1000 in both men and women. Conclusion: From 2004-2020, the prevalence of T2D in the Netherlands more than doubled, with a decreasing incidence from 2010 onwards.

Research in context What is already known about this subject? Many studies have reported the increasing prevalence of type 2 diabetes (T2D). However, only a few studies reported the incidence.In a recent systematic review of all these studies, the incidence fell in over a third of the most high-income populations and increased in a minority of populations. Data from the Netherlands were included, but they date back to 1996.Understanding recent trends in diabetes, the prevalence and incidence are vital for planning future diabetes care.What is the key question? To update national trends in the prevalence and incidence of T2D in the Netherlands for 2004-2020.What are the new findings? During 2004-2020, the prevalence of T2D in the Netherlands more than doubled, with a decreasing incidence from 2010 onwards.How might this impact on clinical practice in the foreseeable future? It demonstrates the effectiveness of preventive strategies, public health education and awareness campaigns contributing to this trend.

The effect of cognitive behavioral therapy for insomnia on sleep and glycemic outcomes in people with type 2 diabetes: A randomized controlled trial.

STUDY OBJECTIVES: Investigate whether aiding sleep by online cognitive behavioral therapy for insomnia (CBT-I) can improve glycemic and metabolic control, mood, quality of life (QoL) and insomnia symptoms in people with type 2 diabetes and assess the mediating role of lifestyle factors. METHODS: Adults with type 2 diabetes and insomnia symptoms were randomly assigned to CBT-I or care as usual. At baseline, three and six months we assessed HbA1c as primary outcome and glycemic control, metabolic outcomes, sleep, mood and QoL as secondary outcomes. Mixed models were used to determine within-person and between-persons differences in outcomes and mediation analysis for lifestyle factors. RESULTS: We randomized 29 participants to CBT-I and 28 to care as usual. Intention-to-treat analysis showed no significant differences in glycemic control, metabolic outcomes, anger, distress or QoL, but showed a significantly larger decrease in insomnia (-1.37(2.65: 0.09)) and depressive symptoms (-0.92(-1.77: 0.06)) and increase in BMI (0.29 kg/m2(0.00:0.57)) in the intervention compared to the control group. Only half of the intervention participants completed the CBT-I. Per protocol analysis showed a not statistically significant decrease in HbA1c (-2.10 mmol/l(-4.83:0.63)) and glucose (-0.39 mmol/l(-1.19:0.42)), metabolic outcomes and increase in QoL. Furthermore, the intervention group showed a significant decrease in insomnia (-2.22(-3.65: 0.78)) and depressive symptoms (-1.18(-2.17: 0.19)) compared to the control group. Lifestyle factors partially mediated the effect of the intervention. CONCLUSIONS: CBT-I might improve insomnia symptoms and mood, and perhaps improves glycemic control, albeit not significant, in people with type 2 diabetes and insomnia symptoms, compared to care as usual.

Increased interleukin-6 is associated with higher risk of heart failure in people with type 2 diabetes.

AIMS: We aimed to determine the association between serum interleukin-6 (IL-6) concentrations and new-onset heart failure (HF) in persons with type 2 diabetes (T2D). METHODS AND RESULTS: We performed a case-control study nested in the Diabetes Care System Cohort, a prospective cohort of persons with T2D in primary care. We included 724 participants, of whom 141 developed HF during 5 years of follow-up and 583 were age- and sex-matched controls. IL-6 was measured at baseline and categorized into four groups: Group 1 was composed of participants with IL-6 below the detection limit of 1.5 pg/mL, and the remainder were divided into tertiles. We performed logistic regression analyses with categorized IL-6 or continuous IL-6 as the determinant and new-onset HF as the outcome adjusted for follow-up time, age, sex, glycated haemoglobin, estimated glomerular filtration rate, albumin/creatinine ratio, and cardiovascular disease at baseline. Effect modification by sex was tested. Participants were 70.7 ± 9.0 years, and 38% were women. In comparison with Group 1, all tertiles were associated with an increased risk of HF with odds ratios of 2.1 [95% confidence interval (CI): 1.2-2.9], 2.8 (95% CI: 2.0-3.7), and 2.1 (95% CI: 1.3-3.0), respectively, for Tertiles 1-3. Continuous IL-6 was associated with the development of HF with an odds ratio of 1.2 (95% CI: 1.0-1.5). No effect modification by sex was observed. CONCLUSIONS: Higher IL-6 levels are associated with the development of HF in persons with T2D. Further research should determine whether IL-6-lowering interventions could prevent the development of HF.

Limited incremental predictive value of the frailty index and other vulnerability measures from routine care data for mortality risk prediction in older patients with COVID-19 in primary care.

BACKGROUND: During the COVID-19 pandemic, older patients in primary care were triaged based on their frailty or assumed vulnerability for poor outcomes, while evidence on the prognostic value of vulnerability measures in COVID-19 patients in primary care was lacking. Still, knowledge on the role of vulnerability is pivotal in understanding the resilience of older people during acute illness, and hence important for future pandemic preparedness. Therefore, we assessed the predictive value of different routine care-based vulnerability measures in addition to age and sex for 28-day mortality in an older primary care population of patients with COVID-19. METHODS: From primary care medical records using three routinely collected Dutch primary care databases, we included all patients aged 70 years or older with a COVID-19 diagnosis registration in 2020 and 2021. All-cause mortality was predicted using logistic regression based on age and sex only (basic model), and separately adding six vulnerability measures: renal function, cognitive impairment, number of chronic drugs, Charlson Comorbidity Index, Chronic Comorbidity Score, and a Frailty Index. Predictive performance of the basic model and the six vulnerability models was compared in terms of area under the receiver operator characteristic curve (AUC), index of prediction accuracy and the distribution of predicted risks. RESULTS: Of the 4,065 included patients, 9% died within 28 days after COVID-19 diagnosis. Predicted mortality risk ranged between 7-26% for the basic model including age and sex, changing to 4-41% by addition of comorbidity-based vulnerability measures (Charlson Comorbidity Index, Chronic Comorbidity Score), more reflecting impaired organ functioning. Similarly, the AUC of the basic model slightly increased from 0.69 (95%CI 0.66 - 0.72) to 0.74 (95%CI 0.71 - 0.76) by addition of either of these comorbidity scores. Addition of a Frailty Index, renal function, the number of chronic drugs or cognitive impairment yielded no substantial change in predictions. CONCLUSION: In our dataset of older COVID-19 patients in primary care, the 28-day mortality fraction was substantial at 9%. Six different vulnerability measures had little incremental predictive value in addition to age and sex in predicting short-term mortality.

Cross-sectional associations between 24-hour movement behaviors and cardiometabolic health among adults with type 2 diabetes mellitus: A comparison according to weight status.

OBJECTIVES: Type 2 diabetes mellitus (T2DM) is a chronic disease associated with overweight and obesity. Evidence suggests that 24-hour movement behaviors (24 h-MBs) play a crucial role in cardiometabolic health. However, it is not yet known if 24 h-MBs differ between weight status groups among people with T2DM (PwT2DM) and how 24 h-MBs are associated with their cardiometabolic health. DESIGN: Cross-sectional study. METHODS: Cardiometabolic variables (i.e. Body Mass Index (BMI), waist circumference (WC), HbA1c, fasting glucose, triglycerides, total-cholesterol, HDL-cholesterol, LDL-cholesterol, blood pressure) and 24 h-MBs (accelerometry and sleep-diary) of 1001 PwT2DM were collected. Regression models using compositional data analysis explored differences in 24 h-MBs between weight status groups and analyzed associations with cardiometabolic variables. RESULTS: The 24 h-MBs of PwT2DM being obese consisted of less sleep, light physical activity (LPA) and moderate to vigorous physical activity (MVPA) and more sedentary time (ST) per day as compared to PwT2DM being overweight or normal weight (p < 0.001). Regardless of weight status, the largest associations were found when reallocating 20 min a day from ST into MVPA for BMI (-0.32 kg/m2; [-0.55; -0.09], -1.09 %), WC (-1.44 cm, [-2.26; -0.62], -1.35 %) and HDL-cholesterol (0.02 mmol/l, [0.01, 0.02], +1.59 %), as well as from ST into LPA for triglycerides (-0.04 mmol/l, [-0.05; -0.03], -2.3 %). Moreover, these associations were different when stratifying people by short-to-average (7.7 h/night) versus long sleep (9.3 h/night) period. CONCLUSIONS: This study highlights the importance of 24 h-MBs in the cardiometabolic health of PwT2DM. Shifting time from ST and/or sleep toward LPA or MVPA might theoretically benefit cardiometabolic health among relatively inactive PwT2DM, irrespective of weight status.

Genome-wide association study of serum magnesium in type 2 diabetes.

People with type 2 diabetes have a tenfold higher prevalence of hypomagnesemia, which is suggested to be caused by low dietary magnesium intake, medication use, and genetics. This study aims to identify the genetic loci that influence serum magnesium concentration in 3466 people with type 2 diabetes. The GWAS models were adjusted for age, sex, eGFR, and HbA1c. Associated traits were identified using publicly available data from GTEx consortium, a human kidney eQTL atlas, and the Open GWAS database. The GWAS identified a genome-wide significant locus in TAF3 (p = 2.9 × 10-9) in people with type 2 diabetes. In skeletal muscle, loci located in TAF3 demonstrate an eQTL link to ATP5F1C, a gene that is involved in the formation of Mg2+-ATP. Serum Mg2+ levels were associated with MUC1/TRIM46 (p = 2.9 × 10-7), SHROOM3 (p = 4.0 × 10-7), and SLC22A7 (p = 1.0 × 10-6) at nominal significance, which is in combination with the eQTL data suggesting that they are possible candidates for renal failure. Several genetic loci were in agreement with previous genomic studies which identified MUC1/TRIM46 (Pmeta = 6.9 × 10-29, PQ = 0.81) and SHROOM3 (Pmeta = 2.9 × 10-27, PQ = 0.04) to be associated with serum Mg2+ in the general population. In conclusion, serum magnesium concentrations are associated with genetic variability around the regions of TAF3, MUC1/TRIM46, SHROOM3, and SLC22A7 in type 2 diabetes.

Potentially Inappropriate Medication in Older Persons With Dementia: Does a Migration Background Matter?

OBJECTIVES: Previous research in the general population shows more potentially inappropriate medications (PIMs) among persons with a migration background compared with persons without a migration background. This study investigated the association between non-Western (nw) migration background (MB) and dementia-specific PIMs in older adults with dementia in the Netherlands. DESIGN: Cohort study using routinely recorded electronic health records and administrative data. SETTING AND PARTICIPANTS: Electronic health record data of general practitioners from the NIVEL-Primary Care Database, were linked to registries managed by Statistics Netherlands (2013-2014). A total of 9055 community-dwelling older adults with dementia were included, among whom 294 persons had an nw-MB from Africa, South America, or Asia, based on their country of birth. METHODS: We determined the presence of dementia-specific PIM prescriptions and compared this between persons with an nw-MB and without an MB, using logistic regression analysis adjusted for follow-up time, age, registered sex, and total number of prescriptions. Interaction effects of potentially relevant covariates were tested. The 3 largest nw-MB groups in the Netherlands were analyzed separately. RESULTS: Dementia-specific PIMs were less frequently prescribed to persons with an nw-MB compared to persons without an MB with a dementia diagnosis [30.6% vs 34.4%, odds ratio (OR) 0.71, 95% CI 0.54-0.92], with especially less often a benzodiazepine prescription in the group with an nw-MB, compared to persons without an MB (15.0% vs 19.3%, OR 0.61, 95% CI 0.43-0.84). Dementia duration, living alone, household income, and degree of urbanization did not influence the associations. CONCLUSIONS AND IMPLICATIONS: Among older adults with dementia in the Netherlands, persons with an nw-MB had less often a dementia-specific PIM prescription compared to persons without an MB. Whether this difference is a reflection of better quality of care, higher professional uncertainty, or less recognition of (mental) health problems in persons with an nw-MB and dementia, needs further investigation.

External validation of six COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

OBJECTIVES: To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care, and nursing homes. STUDY DESIGN AND SETTING: This retrospective external validation study included 14,092 older individuals of ≥70 years of age with a clinical or polymerase chain reaction-confirmed COVID-19 diagnosis from March 2020 to December 2020. The six validation cohorts include three hospital-based (CliniCo, COVID-OLD, COVID-PREDICT), two primary care-based (Julius General Practitioners Network/Academisch network huisartsgeneeskunde/Network of Academic general Practitioners, PHARMO), and one nursing home cohort (YSIS) in the Netherlands. Based on a living systematic review of COVID-19 prediction models using Prediction model Risk Of Bias ASsessment Tool for quality and risk of bias assessment and considering predictor availability in validation cohorts, we selected six prognostic models predicting mortality risk in adults with COVID-19 infection (GAL-COVID-19 mortality, 4C Mortality Score, National Early Warning Score 2-extended model, Xie model, Wang clinical model, and CURB65 score). All six prognostic models were validated in the hospital cohorts and the GAL-COVID-19 mortality model was validated in all three healthcare settings. The primary outcome was in-hospital mortality for hospitals and 28-day mortality for primary care and nursing home settings. Model performance was evaluated in each validation cohort separately in terms of discrimination, calibration, and decision curves. An intercept update was performed in models indicating miscalibration followed by predictive performance re-evaluation. MAIN OUTCOME MEASURE: In-hospital mortality for hospitals and 28-day mortality for primary care and nursing home setting. RESULTS: All six prognostic models performed poorly and showed miscalibration in the older population cohorts. In the hospital settings, model performance ranged from calibration-in-the-large -1.45 to 7.46, calibration slopes 0.24-0.81, and C-statistic 0.55-0.71 with 4C Mortality Score performing as the most discriminative and well-calibrated model. Performance across health-care settings was similar for the GAL-COVID-19 model, with a calibration-in-the-large in the range of -2.35 to -0.15 indicating overestimation, calibration slopes of 0.24-0.81 indicating signs of overfitting, and C-statistic of 0.55-0.71. CONCLUSION: Our results show that most prognostic models for predicting mortality risk performed poorly in the older population with COVID-19, in each health-care setting: hospital, primary care, and nursing home settings. Insights into factors influencing predictive model performance in the older population are needed for pandemic preparedness and reliable prognostication of health-related outcomes in this demographic.

A deprescribing programme aimed to optimise blood glucose-lowering medication in older people with type 2 diabetes mellitus, the OMED2-study: the study protocol for a randomised controlled trial.

BACKGROUND: Older patients with type 2 diabetes mellitus (T2D) have an increased risk of hypoglycaemic episodes when using sulphonylureas or insulin. In the Netherlands, guidelines exist for reducing glucose-lowering medication in older patients. However, evidence is lacking that a medication reduction in older patients can be safely pursued. Here, we will examine if promoting the deprescribing of insulin/sulphonylureas with a deprescribing programme (DPP) in general practice affects T2D-complications in older overtreated patients. METHODS: We will perform a 1:1 cluster randomised controlled trial in 86 general practices in the Netherlands. The DPP will consist of education sessions with general practitioners and practice nurses about reducing glucose-lowering medication in older patients (≥ 70 years). Topics of the sessions include the necessity of deprescribing, tools to initiate deprescribing and strategies to discuss deprescribing with patients (shared decision making). The DPP further includes a support programme with practice visits. The study will employ a selection tool to identify possibly overtreated older patients from the electronic medical records of the general practitioner. Eligibility for enrolment in the study will be based on HbA1c targets indicated by the Dutch guidelines, which depend on age, diabetes duration, presence of frailty, and life expectancy. The control group will provide usual care. We aim to include 406 patients. The follow-up period will be 2 years. For the primary outcome, the effect of the DPP on T2D-complications will be assessed by counting the cumulative incidence of events related to under- and overtreatment in T2D as registered in the electronic medical records. We shall perform an intention-to-treat analysis and an analysis including only patients for whom deprescribing was initiated. The implementation of the DPP in general practice will be evaluated quantitatively and qualitatively using the Extended Normalisation Process Theory (ENPT) and the Reach, Efficacy - Adoption, Implementation and Maintenance (RE-AIM) model. Other secondary outcomes include quality of life, cognitive functioning, events related to overtreatment or undertreatment, biomarkers of health, amount of blood glucose-lowering medication prescriptions, and cost-effectiveness. DISCUSSION: This study will provide insight into the safety and feasibility of a programme aimed at deprescribing sulphonylureas/insulin in older people with T2D who are treated in general practice. TRIAL REGISTRATION: ISRCTN Registry, ISRCTN50008265 , registered 09 March, 2023.

Longitudinal association of premature atrial contractions with atrial fibrillation and brain ischemia in people with type 2 diabetes: The Hoorn Diabetes Care System cohort.

Background: Premature atrial contractions (PACs) are potential markers for imminent onset of both atrial fibrillation (AF) and brain ischemia (BI; transient ischemic attack [TIA] or ischemic stroke). We investigated the association of PACs with incident AF and BI events separately, and of incident AF with BI events in people with type 2 diabetes (T2D) without pre-existing AF or cerebrovascular disease. Methods: A prospective longitudinal study of 12,242 people with T2D without known AF or cerebrovascular disease from the Hoorn Diabetes Care System cohort. Annual measurements (1998-2018) included cardiovascular risk factors, over 85,000 ECGs, and self-reported cardiovascular events. We assessed the association of PACs with incident AF and BI events and of incident AF with BI events using time-dependent Cox-regression models, adjusted for time-varying cardiovascular risk factors and medication use (Hazard Ratios with 95%CIs). Results: The baseline mean age was 62.2 ± 11.9 years. During a median follow-up of 7.0 (IQR 3.4-11.0) years, 1031 (8.4 %) participants had PACs, and 566 (4.6 %) had incident AF at any of the median 6 (IQR 3-10) annual ECG recordings. BI events occurred in 517 (4.2 %) people (304 TIAs, 213 ischemic strokes). After adjustment, PACs were associated with incident AF (Hazard Ratio, 1.96 (95%CI, 1.53-2.50)), but not with overall BI events (1.09 (0.76-1.56)), or with TIA (0.91 (0.57-1.46)) or ischemic stroke (1.50 (0.88-2.54)) separately. AF was not associated with BI events (0.95 (0.55-1.63)). Conclusions: In people with T2D without a history of AF or BI events, PACs are associated with a two-fold increased risk of incident AF.