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Jetty A Overbeek,1,2 Giel Nijpels,2 Karin MA Swart,1,2 Marieke T Blom,2,3 Petra JM Elders,2,3 Ron MC Herings1,4 1PHARMO Institute for Drug Outcomes Research, Utrecht, Netherlands; 2Amsterdam UMC, Location Vrije Universiteit Amsterdam, Department of General Practice, Amsterdam, Netherlands; 3Amsterdam Public Health, Health Behaviors & Chronic Diseases, Amsterdam, Netherlands; 4Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Epidemiology and Data Science, Amsterdam, NetherlandsCorrespondence: Jetty A Overbeek, Email jetty.overbeek@pharmo.nlAims/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.Plain Language Summary: Research in contextWhat 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.Keywords: type 2 diabetes, prevalence, incidence, epidemiology

Jetty A Overbeek,1– 3 Karin MA Swart,1– 3 Emma YM van der Pal,2,3 Marieke T Blom,2,3 Joline WJ Beulens,3– 5 Giel Nijpels,2,3 Petra JM Elders,2,3 Ron MC Herings1,3,4 1Department Research, PHARMO Institute for Drug Outcomes Research, Utrecht, Netherlands; 2Department of General Practice, Amsterdam UMC - Location Vrije Universiteit Amsterdam, Amsterdam, Netherlands; 3Health Behaviors & Chronic Diseases, Amsterdam Public Health, Amsterdam, Netherlands; 4Department of Epidemiology and Data Science, Amsterdam UMC - Location Vrije Universiteit Amsterdam, Amsterdam, Netherlands; 5Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, NetherlandsCorrespondence: Jetty A Overbeek, Department Research, PHARMO Institute for Drug Outcomes Research, Van Deventerlaan 30-40, Utrecht, 3528 AE, Netherlands, Tel +3130 7440 800, Email jetty.overbeek@pharmo.nlIntroduction: The increasing number of people with diabetes and the unclear long-term safety and effectiveness of newer and older blood-glucose-lowering treatments emphasize the need for more pharmaco-epidemiological studies in this field. A prospective, regularly updated cohort of people with diabetes would provide quick and up-to-date information regarding prevalence, treatment, safety and effectiveness. The current aim was to describe the design of the DIAbetes MANagement and Treatment (DIAMANT) cohort.Methods: The DIAMANT cohort is a population-based, dynamic, prospective cohort of persons with diabetes. It contains real-world data (RWD) from general practitioners (GP), including diagnoses, symptoms, examinations, communication to/from specialists and medication. Diabetes is defined as a recorded diabetes diagnosis or a prescription of drugs used in diabetes. The cohort is part of the national infrastructure of “Stichting Informatievoorziening voor Zorg en Onderzoek” (STIZON) and is linked to other data sources.Results: Currently, the cohort enables access to information of 89,883 patients in 2004 to 344,914 in 2020 (6% T1D, 84% T2D and 10% unclassified type of diabetes), with 193,931 participants still registered as being present in the GP practice (active) in 2020. The frequency of follow-up of persons with diabetes is practice dependent. The Dutch guidelines advise 2– 4 contacts per year with a more extensive yearly check-up. The DIAMANT cohort is updated several times a year. Anonymised data from the DIAMANT cohort are available to researchers.Discussion: The DIAMANT cohort provides the opportunity to gain RWD insights into the treatment and outcomes among people with diabetes in daily general practice. The data can be enriched by established linkages to other data sources (eg, hospital data, the Perinatal Registry, the Cancer Registry). The DIAMANT cohort serves as a start of a national infrastructure to study, manage and provide personalised care in order to ultimately improve care and outcomes for people with diabetes.Keywords: diabetes, type 2 diabetes, epidemiology, follow-up, prospective cohort, real-world data

Abeer Ahmad,1 M Ruth Mast,1 Giel Nijpels,2 Petra JM Elders,2 Jacqueline M Dekker,3 Jacqueline G Hugtenburg1 1Department of Clinical Pharmacology and Pharmacy, 2Department of General Practice, 3Departments of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands Background: Drug-related problems (DRP) following hospital discharge are common among elderly patients using multiple drugs for the treatment of chronic diseases. The aim of this study was to investigate the occurrence of DRP in these patients using a specific tool for the identification of DRP by community pharmacists. Methods: An observational study involving 340 patients aged over 60 years using at least five prescription drugs and discharged from hospital. The occurrence of DRP was assessed by means of an identification tool specifically developed for use by community pharmacists, including a semistructured patient interview and a checklist of common DRP. Results: In total, 992 potential DRP were observed in the 340 patients (mean 2.9 ± 1.7). No drug prescribed but clear indication, an unnecessarily long duration of treatment, dose too low, and incorrect drug selection were the DRP most commonly observed. Ten percent of DRP occurring in 71 patients were drug–drug interactions. The number of DRP was related to the number of drugs prescribed. Frequently occurring DRP found using the patient interview were fear of side effects and no or insufficient knowledge of drug use. Medication of patients discharged from the pulmonary department and of those with type 2 diabetes was particularly associated with occurrence of DRP. Conclusion: Following hospital discharge, DRP occur frequently among elderly patients using five or more drugs for the treatment of chronic disease. The number of DRP increased with the number of drugs used. An important task for community pharmacists is to identify, resolve, and prevent the occurrence of DRP among this patient group. Since DRP are associated with an increased risk of hospital readmissions, morbidity, and mortality, it is very important to develop intervention strategies to resolve and prevent DRP. Keywords: drug-related problems, elderly, discharge from hospital, community pharmacy

Jacqueline G Hugtenburg,1 Lonneke Timmers,1 Petra JM Elders,2 Marcia Vervloet,3 Liset van Dijk31EMGO+ Institute and Department of Clinical Pharmacology and Pharmacy, VU University Medical Center, Amsterdam, 2ANH-VUmc, VU University Medical Center, Amsterdam, 3NIVEL, Netherlands Institute for Health Services Research, Utrecht, The NetherlandsBackground: Nonadherence with medication is a complex and multidimensional health care problem. The causes may be related to the patient, treatment, and/or health care provider. As a consequence, substantial numbers of patients do not benefit optimally from pharmacotherapy, resulting in increased morbidity and mortality as well as increased societal costs. Several interventions may contribute to improved adherence. However, most interventions have only a modest effect. Thus, despite the many efforts made, there has been little progress made as yet in tackling the problem of nonadherence.Methods: This paper summarizes the definitions and taxonomy of adherence with medication, as well as types and causes of nonadherence. In addition, interventions aimed at improvement of adherence are discussed.Conclusion: There is not just one solution for the nonadherence problem that fits all patients. Most interventions to improve adherence are aimed at all patients regardless of whether they are adherent or not. Recently, a number of tailored interventions have been described in the literature. Modern techniques are useful. Electronic pill boxes combined with Short Message Service reminders are specifically designed to improve unintentional adherence and have resulted in an increase in refill adherence in diabetic patients with suboptimal adherence. Tailored Internet interventions are a possibility for influencing patient drug-taking behavior and show promising results. Tailored counseling interventions targeted at the underlying causes of nonadherence seem an attractive method for supporting patients with their use of drugs. However, despite the plausible theoretical framework, data on long-term health effects of the various interventions are not available. To improve adherence effectively, there is a need for a tailored approach based on the type and cause of nonadherence and the specific needs of the patient.Keywords: adherence, compliance, concordance, tailored intervention

Aim: To uncover differences in small non-coding RNAs (sncRNAs) in individuals with type 2 diabetes (T2D) categorized into five clusters based on individual characteristics, which may aid in the identification of those prone to rapid progression., Materials and Methods: In the Hoorn Diabetes Care System (DCS) cohort, participants were clustered by age, body mass index (BMI), and glycated haemoglobin, C-peptide and high-density lipoprotein (HDL) cholesterol levels, yielding severe insulin-deficient diabetes, severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), mild diabetes, and mild diabetes with high HDL cholesterol clusters (n = 412). Utilizing plasma sncRNA-sequencing, we identified distinct cluster-specific sncRNAs. Validation was performed in a smaller DCS Hoorn dataset (n = 138). To elucidate their potential functions, we examined tissue expression, identified potential targets or (co-)regulated proteins, conducted gene set enrichment analyses on the targets through Reactome, and examined tissue expression of the (co-)regulated proteins., Results: The insulin-resistant cluster exhibited aberrant expression of 10 sncRNAs, while the high BMI cluster featured eight differentially expressed sncRNAs. Multiple (co-)regulated proteins were identified for sncRNAs associated with both clusters. Proteins associated with both clusters showed enrichment for metabolism. Proteins that specifically and only associated with the SIRD cluster showed enrichment for immune-related signalling. Furthermore, MOD cluster-specific associated proteins showed enrichment for the complement system., Conclusions: Our research showed differential sncRNA levels among type 2 diabetes clusters. This may reflect and could deepen our understanding of molecular mechanisms, in development, progression, and risk factors for each cluster., (© 2024 The Author(s). Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

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 (β ∼ 1), while the association for plant-based protein was marginally non-significant (βQ4vsQ1:0.88, 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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

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., Competing Interests: Disclosures The authors declare no conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

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., (© 2024 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

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., (© 2024. The Author(s).)

Background: Social jetlag is a chronic disruption of sleep timing that is characterized by different sleep timing during workdays and free days. Social jetlag has been associated with disturbed glucose metabolism, insulin resistance, and increased risk of metabolic syndrome and type 2 diabetes. In this study, we aim to investigate whether a combination of bright light therapy in the morning, bright light reduction in the evening and sleep advance instructions for 3 weeks reduces social jetlag and if this results in improvement of glycemic and metabolic control, sleep, mood and quality of life after 3 and 12 weeks in people with prediabetes and type 2 diabetes and to assess possible mediators, compared to regular sleep habits., Methods: In this randomized controlled trial, 60 people with prediabetes or type 2 diabetes with > 1 h social jetlag will be recruited. The intervention consists of bright light therapy (5000 lx) emitted by Vitamine-L (Lumie, UK) for 30 min each morning, combined with the advice to follow sleep advance instructions and to wear bright light-dimming goggles every evening for a period of 3 weeks. The control group adheres to their regular sleep habits and conditions. The primary outcome is glycated hemoglobin (HbA1c) after 12 weeks comparing the intervention and control in an intention-to-treat analysis. Secondary outcomes at 3 and 12 weeks are (1) social jetlag; (2) insulin sensitivity, fasting blood glucose, glucose-lowering medication use, and frequency of perceived hypoglycemia; (3) metabolic outcomes, including body mass index (BMI), waist circumference, body fat percentage, and blood pressure; (4) mood, including depression, fatigue and anxiety (measured with questionnaires); and (5) quality of life measured using EQ5D questionnaire. To assess other factors that might play a role as possible mediators, we will measure (para)sympathetic nervous system activity assessed with ECGs and electrochemical skin conductance tests, sleep quality and sleep phase distribution assessed with a sleep measuring headband (ZMax), the Dim Light Melatonin Onset in saliva samples (in a subgroup) at 3 and 12 weeks, the feeling of satiety and satiation with a 10-cm visual analog scale (VAS), diet using a food frequency questionnaire, and physical activity using an accelerometer (ActiGraph)., Discussion: Social jetlag can contribute to poorer glycemic control and metabolic control in those with type 2 diabetes. With this intervention, we aim to reduce social jetlag and thereby improve glycemic and metabolic control. This could offer a way to improve overall population health and to reduce the disease burden of type 2 diabetes., Trial Registration: ISRCTN registry ISRCTN11967109 . Registered on 9 May 2024., (© 2024. The Author(s).)

Aims/hypothesis: This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA 1c , HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed., Results: Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%., Conclusions/interpretation: Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators., (© 2024. The Author(s).)

Background: Subclinical thyroid diseases are often the subject of debate concerning their clinical significance, the appropriateness of diagnostic testing, and possible treatment. This systematic review addresses the variation in international guidelines for subclinical hyperthyroidism, focusing on diagnostic workup, treatment, and follow-up recommendations., Methods: Following the PRISMA guidelines, we searched PubMed, Embase, and guideline-specific databases and included clinical practice guidelines with recommendations on subclinical hyperthyroidism. Guideline recommendations were extracted, and quality assessment was performed using selected questions of the Appraisal of Guidelines for Research & Evaluation (AGREE) II instrument., Results: Of the 2624 records screened, 22 guidelines were included, which were published between 2007 and 2021. Guideline quality was generally intermediate to low. Diagnostic approaches differed substantially, particularly in the extent of recommended testing. Treatment initiation depended on TSH levels, age, and comorbidities, but the level of detail regarding defining precise comorbidities varied. Recommendations for monitoring intervals for follow-up ranged from 3 to 12 months., Conclusion: This review underscores the existing variability in (inter)national guidelines concerning subclinical hyperthyroidism. There isa need for clear recommendations in guidelines considering diagnostic workup, treatment, and follow-up of subclinical hyperthyroidism. In order to establish this, future research should focus on determining clear and evidence-based intervention thresholds.

Apolipoprotein-CIII (apo-CIII) inhibits the clearance of triglycerides from circulation and is associated with an increased risk of diabetes complications. It exists in four main proteoforms: O-glycosylated variants containing either zero, one, or two sialic acids and a non-glycosylated variant. O-glycosylation may affect the metabolic functions of apo-CIII. We investigated the associations of apo-CIII glycosylation in blood plasma, measured by mass spectrometry of the intact protein, and genetic variants with micro- and macrovascular complications (retinopathy, nephropathy, neuropathy, cardiovascular disease) of type 2 diabetes in a DiaGene study ( n = 1571) and the Hoorn DCS cohort ( n = 5409). Mono-sialylated apolipoprotein-CIII (apo-CIII 1 ) was associated with a reduced risk of retinopathy (β = -7.215, 95% CI -11.137 to -3.294) whereas disialylated apolipoprotein-CIII (apo-CIII 2 ) was associated with an increased risk (β = 5.309, 95% CI 2.279 to 8.339). A variant of the GALNT2 -gene (rs4846913), previously linked to lower apo-CIII 0a , was associated with a decreased prevalence of retinopathy (OR = 0.739, 95% CI 0.575 to 0.951). Higher apo-CIII 1 levels were associated with neuropathy (β = 7.706, 95% CI 2.317 to 13.095) and lower apo-CIII 0a with macrovascular complications (β = -9.195, 95% CI -15.847 to -2.543). In conclusion, apo-CIII glycosylation was associated with the prevalence of micro- and macrovascular complications of diabetes. Moreover, a variant in the GALNT2 -gene was associated with apo-CIII glycosylation and retinopathy, suggesting a causal effect. The findings facilitate a molecular understanding of the pathophysiology of diabetes complications and warrant consideration of apo-CIII glycosylation as a potential target in the prevention of diabetes complications.

This study evaluated the yield of routine laboratory examination in a large population of older women in primary care. The prevalence of laboratory abnormalities was low and the clinical consequences in follow-up were limited. There was a weak association of laboratory abnormalities with osteoporosis but no association with vertebral fractures and recent fractures., Purpose: Most osteoporosis guidelines advice routine laboratory examination. We have investigated the yield of laboratory examinations in facture risk evaluation of elderly women in primary care., Methods: We assessed the prevalence of laboratory abnormalities and their association with risk factors for fractures, recent fractures, low bone mineral density (BMD), and prevalent vertebral fracture in 8996 women ≥ 65 years of age participating in a primary care fracture risk screening study. In a sample of 2208 of these participants, we also evaluated the medical consequences in the medical records during a follow-up period of ≥ 1 year., Results: Vitamin D deficiency (< 30 nmol/L) was present in 13% and insufficiency (< 50 nmol/L) in 43% of the study sample. The prevalence of other laboratory abnormalities (ESR, calcium, creatinine, FT4) was 4.6% in women with risk factors for fractures, 6.1% in women with low BMD (T-score ≤  - 2.5), 6.0% after a prevalent vertebral fracture, 5.2% after a recent fracture and 2.6% in the absence of important risk factors for fractures. Laboratory abnormalities other than vitamin D were associated with low BMD (OR 1.4, 95%CI 1.1-1.8) but not with prevalent vertebral fractures nor recent fractures. Low BMD was associated with renal failure (OR 2.0, 95%CI 1.3-3.4), vitamin D insufficiency (OR 1.2, 95%CI 1.0-1.3) and deficiency (OR 1.3, 95%CI 1.1-.5). In the follow-up period, 82% of the laboratory abnormalities did not result in a new diagnosis or treatment reported in the medical records., Conclusions: We identified a low prevalence of laboratory abnormalities in a primary care population of older women and the majority of these findings had no medical consequences., (© 2024. The Author(s).)

Aims/hypothesis: People with type 2 diabetes are heterogeneous in their disease trajectory, with some progressing more quickly to insulin initiation than others. Although classical biomarkers such as age, HbA 1c and diabetes duration are associated with glycaemic progression, it is unclear how well such variables predict insulin initiation or requirement and whether newly identified markers have added predictive value., Methods: In two prospective cohort studies as part of IMI-RHAPSODY, we investigated whether clinical variables and three types of molecular markers (metabolites, lipids, proteins) can predict time to insulin requirement using different machine learning approaches (lasso, ridge, GRridge, random forest). Clinical variables included age, sex, HbA 1c , HDL-cholesterol and C-peptide. Models were run with unpenalised clinical variables (i.e. always included in the model without weights) or penalised clinical variables, or without clinical variables. Model development was performed in one cohort and the model was applied in a second cohort. Model performance was evaluated using Harrel's C statistic., Results: Of the 585 individuals from the Hoorn Diabetes Care System (DCS) cohort, 69 required insulin during follow-up (1.0-11.4 years); of the 571 individuals in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort, 175 required insulin during follow-up (0.3-11.8 years). Overall, the clinical variables and proteins were selected in the different models most often, followed by the metabolites. The most frequently selected clinical variables were HbA 1c (18 of the 36 models, 50%), age (15 models, 41.2%) and C-peptide (15 models, 41.2%). Base models (age, sex, BMI, HbA 1c ) including only clinical variables performed moderately in both the DCS discovery cohort (C statistic 0.71 [95% CI 0.64, 0.79]) and the GoDARTS replication cohort (C 0.71 [95% CI 0.69, 0.75]). A more extensive model including HDL-cholesterol and C-peptide performed better in both cohorts (DCS, C 0.74 [95% CI 0.67, 0.81]; GoDARTS, C 0.73 [95% CI 0.69, 0.77]). Two proteins, lactadherin and proto-oncogene tyrosine-protein kinase receptor, were most consistently selected and slightly improved model performance., Conclusions/interpretation: Using machine learning approaches, we show that insulin requirement risk can be modestly well predicted by predominantly clinical variables. Inclusion of molecular markers improves the prognostic performance beyond that of clinical variables by up to 5%. Such prognostic models could be useful for identifying people with diabetes at high risk of progressing quickly to treatment intensification., Data Availability: Summary statistics of lipidomic, proteomic and metabolomic data are available from a Shiny dashboard at https://rhapdata-app.vital-it.ch ., (© 2024. The Author(s).)

Background: In 2018, a grant was provided for an evidence-based guideline on osteoporosis and fracture prevention based on 10 clinically relevant questions., Methods: A multidisciplinary working group was formed with delegates from Dutch scientific and professional societies, including representatives from the patient's organization and the Dutch Institute for Medical Knowledge. The purpose was to obtain a broad consensus among all participating societies to facilitate the implementation of the updated guideline., Results: Novel recommendations in our guideline are as follows: - In patients with an indication for DXA of the lumbar spine and hips, there is also an indication for VFA. - Directly starting with anabolic drugs (teriparatide or romosozumab) in patients with a very high fracture risk; - Directly starting with zoledronic acid in patients 75 years and over with a hip fracture (independent of DXA); - Directly starting with parenteral drugs (denosumab, teriparatide, zoledronic acid) in glucocorticoid-induced osteoporosis with very high fracture risk; - A lifelong fracture risk management, including lifestyle, is indicated from the start of the first treatment., Conclusion: In our new multidisciplinary guideline osteoporosis and fracture prevention, we developed 5 "relatively new statements" that are all a crucial step forward in the optimization of diagnosis and treatment for fracture prevention. We also developed 5 flowcharts, and we suppose that this may be helpful for individual doctors and their patients in daily practice and may facilitate implementation., (© 2024. The Author(s).)

Objective: Social jetlag is a discordance between the social and biological rhythm and is associated with higher HbA1c, higher BMI, and higher odds of obesity. The pathways that could explain these associations are still debated. This study aims to assess the mediating role of several lifestyle factors in the cross-sectional association between social jetlag and BMI., Methods: We used cross-sectional data from 1784 adults from urban areas in the Netherlands, collected in 2019. Social jetlag (difference in midpoint of sleep between week and weekend nights) was categorized as low(<1 h), moderate(1-2h), and high(>2 h). BMI(kg/m 2 ) was calculated from self-reported height and weight. The association between social jetlag and BMI was assessed using linear regression, adjusted for sex, age, education, and sleep duration and stratified for the effect modifier stress (high vs. low). Mediation analysis was performed for self-reported smoking, physical activity, alcohol consumption, and adherence to a healthy diet., Results: High social jetlag was associated with higher BMI (0.69 kg/m 2 ,95%CI 0.05;1.33). This association was stronger in people with high stress (0.93 kg/m 2 ,95%CI 0.09;1.76). Social jetlag was also associated with higher odds of smoking, lower physical activity, higher alcohol consumption, and lower healthy diet adherence. In people with high stress, these factors mediated 10-15% of the association between social jetlag and BMI., Conclusions: Social jetlag is associated with higher BMI and this association is stronger in people with high stress. In people with high stress, healthy diet adherence mediated 12% of this association. Other pathways involved in this association should be further investigated., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Left ventricular diastolic dysfunction (LVDD) without symptoms, and heart failure (HF) with preserved ejection fraction (HFpEF) represent the most common phenotypes of HF in individuals with type 2 diabetes mellitus, and are more common than HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and left ventricular systolic dysfunction (LVSD) in these individuals. However, diagnostic criteria for HF have changed over the years, resulting in heterogeneity in the prevalence/incidence rates reported in different studies. We aimed to give an overview of the diagnosis and epidemiology of HF in type 2 diabetes, using both a narrative and systematic review approach; we focus narratively on diagnosing (using the 2021 European Society of Cardiology [ESC] guidelines) and screening for HF in type 2 diabetes. We performed an updated (2016-October 2022) systematic review and meta-analysis of studies reporting the prevalence and incidence of HF subtypes in adults ≥18 years with type 2 diabetes, using echocardiographic data. Embase and MEDLINE databases were searched and data were assessed using random-effects meta-analyses, with findings presented as forest plots. From the 5015 studies found, 209 were screened using the full-text article. In total, 57 studies were included, together with 29 studies that were identified in a prior meta-analysis; these studies reported on the prevalence of LVSD (n=25 studies, 24,460 individuals), LVDD (n=65 studies, 25,729 individuals), HFrEF (n=4 studies, 4090 individuals), HFmrEF (n=2 studies, 2442 individuals) and/or HFpEF (n=8 studies, 5292 individuals), and on HF incidence (n=7 studies, 17,935 individuals). Using Hoy et al's risk-of-bias tool, we found that the studies included generally had a high risk of bias. They showed a prevalence of 43% (95% CI 37%, 50%) for LVDD, 17% (95% CI 7%, 35%) for HFpEF, 6% (95% CI 3%, 10%) for LVSD, 7% (95% CI 3%, 15%) for HFrEF, and 12% (95% CI 7%, 22%) for HFmrEF. For LVDD, grade I was found to be most prevalent. Additionally, we reported a higher incidence rate of HFpEF (7% [95% CI 4%, 11%]) than HFrEF 4% [95% CI 3%, 7%]). The evidence is limited by the heterogeneity of the diagnostic criteria over the years. The systematic section of this review provides new insights on the prevalence/incidence of HF in type 2 diabetes, unveiling a large pre-clinical target group with LVDD/HFpEF in which disease progression could be halted by early recognition and treatment.Registration PROSPERO ID CRD42022368035., (© 2024. The Author(s).)

Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised "bottom-up" approach, we attempt to group T2D patients based solely on -omics data generated from plasma., Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics., Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p =3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor., Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D., Competing Interests: GR has received grant funding from, and is a consultant for, Sun Pharmaceuticals Inc. KS is CEO of Lipotype. KS and CK are shareholders of Lipotype. MG is an employee of Lipotype. MH is an employee of Janssen Research & Development. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Li, Dragan, Tran, Fung, Kuznetsov, Hansen, Beulens, Hart, Slieker, Donnelly, Gerl, Klose, Mehl, Simons, Elders, Pearson, Rutter and Ibberson.)

The relationship between self-reported falls and fracture risk was estimated in an international meta-analysis of individual-level data from 46 prospective cohorts. Previous falls were associated with an increased fracture risk in women and men and should be considered as an additional risk factor in the FRAX® algorithm., Introduction: Previous falls are a well-documented risk factor for subsequent fracture but have not yet been incorporated into the FRAX algorithm. The aim of this study was to evaluate, in an international meta-analysis, the association between previous falls and subsequent fracture risk and its relation to sex, age, duration of follow-up, and bone mineral density (BMD)., Methods: The resource comprised 906,359 women and men (66.9% female) from 46 prospective cohorts. Previous falls were uniformly defined as any fall occurring during the previous year in 43 cohorts; the remaining three cohorts had a different question construct. The association between previous falls and fracture risk (any clinical fracture, osteoporotic fracture, major osteoporotic fracture, and hip fracture) was examined using an extension of the Poisson regression model in each cohort and each sex, followed by random-effects meta-analyses of the weighted beta coefficients., Results: Falls in the past year were reported in 21.4% of individuals. During a follow-up of 9,102,207 person-years, 87,352 fractures occurred of which 19,509 were hip fractures. A previous fall was associated with a significantly increased risk of any clinical fracture both in women (hazard ratio (HR) 1.42, 95% confidence interval (CI) 1.33-1.51) and men (HR 1.53, 95% CI 1.41-1.67). The HRs were of similar magnitude for osteoporotic, major osteoporotic fracture, and hip fracture. Sex significantly modified the association between previous fall and fracture risk, with predictive values being higher in men than in women (e.g., for major osteoporotic fracture, HR 1.53 (95% CI 1.27-1.84) in men vs. HR 1.32 (95% CI 1.20-1.45) in women, P for interaction = 0.013). The HRs associated with previous falls decreased with age in women and with duration of follow-up in men and women for most fracture outcomes. There was no evidence of an interaction between falls and BMD for fracture risk. Subsequent risk for a major osteoporotic fracture increased with each additional previous fall in women and men., Conclusions: A previous self-reported fall confers an increased risk of fracture that is largely independent of BMD. Previous falls should be considered as an additional risk factor in future iterations of FRAX to improve fracture risk prediction., (© 2024. International Osteoporosis Foundation and Bone Health and Osteoporosis Foundation.)

Objective: To assess the cultural competence (CC) of GP trainees and GP trainers. Design and setting: A cross-sectional survey study was conducted at the GP Training Institute of Amsterdam UMC., Subjects: We included 92 GP trainees and 186 GP trainers., Main Outcome Measures: We measured the three domains of cultural competency: 1) knowledge, 2) culturally competent attitudes and 3) culturally competent skills. Regression models were used to identify factors associated with levels of CC. Participants rated their self-perceived CC at the beginning and end of the survey, and the correlation between self-perceived and measured CC was assessed., Results: Approximately 94% of the GP trainees and 81% of the GP trainers scored low on knowledge; 45% and 42%, respectively, scored low on culturally competent attitudes. The level of culturally competent skills was moderate (54.3%) or low (48.4%) for most GP trainees and GP trainers. The year of residency and the GP training institute were significantly associated with one or more (sub-)domains of CC in GP trainees. Having >10% migrant patients and experience as a GP trainer were positively associated with one or more (sub-) domains of cultural competence in GP trainers. The correlation between measured and self-perceived CC was positive overall but very weak (Spearman correlation coefficient ranging from -0.1-0.3)., Conclusion: The level of cultural competence was low in both groups, especially in the knowledge scores. Cultural competence increased with experience and exposure to an ethnically diverse patient population. Our study highlights the need for cultural competence training in the GP training curricula.

Introduction: There is conflicting evidence whether lower extremity arterial calcification coincides with coronary arterial calcification (CAC). The aims of this study were to investigate the associations between (1) femoral and crural calcification with CAC, and (2) femoral and crural calcification pattern with CAC., Research Design and Methods: This cross-sectional study included 405 individuals (74% men, 62.6±10.9 years) from the ARTEMIS cohort study at high risk of cardiovascular disease (CVD) who underwent a CT scan of the femoral, crural and coronary arteries. High CVD risk was defined as history/presence of cerebrovascular disease, coronary artery disease, abdominal aortic aneurysm, renal artery stenosis, peripheral artery disease or CVD risk factors: diabetes mellitus type 2, hypertension, hyperlipidemia. Calcification score within each arterial bed was expressed in Agatston units. Dominant calcification patterns (intimal, medial, absent/indistinguishable) were determined via a CT-guided histologically validated scoring algorithm. Multivariable-adjusted multinomial logistic regression analyses were used. Replication was performed in an independent population of individuals with diabetes mellitus type 2 (Early-HFpEF cohort study)., Results: Every 100-point increase in femoral and crural calcification score was associated with 1.23 (95% CI=1.09 to 1.37, p<0.001) and 1.28 (95% CI=1.11 to 1.47, p=0.001) times higher odds of having CAC within tertile 3 (high) versus tertile 1 (low), respectively. The association appeared stronger for crural versus femoral arteries. Moreover, the presence of femoral intimal (OR=10.81, 95% CI=4.23 to 27.62, p<0.001), femoral medial (OR=10.37, 95% CI=3.92 to 27.38, p<0.001) and crural intimal (OR=6.70, 95% CI=2.73 to 16.43, p<0.001) calcification patterns were associated with higher odds of having CAC within tertile 3 versus tertile 1, independently from concomitant calcification score. This association appeared stronger for intimal versus medial calcification patterns. The replication analysis yielded similar results., Conclusions: Higher femoral and crural calcification scores were associated with higher CAC. Moreover, the presence of femoral intimal, femoral medial and crural intimal calcification patterns was associated with increased CAC. It appears that arterial calcification is a systemic process which occurs simultaneously in various arterial beds., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Competing Interests: MHAM has acted as a consultant or speaker and received honoraria from AstraZeneca, Eli Lilly, and NovoNordisk. DHvR has acted as a consultant and received honoraria from Boehringer Ingelheim and Lilly, Merck, Novo Nordisk, Sanofi, and AstraZeneca, and has received research operating funds from Boehringer Ingelheim–Lilly Diabetes Alliance, AstraZeneca, and Novo Nordisk. PJME declares no competing interests.

A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX., Introduction: The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD)., Methods: We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture, and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD, and duration of follow-up. The results of the different studies were merged by using the weighted β-coefficients., Results: A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06), or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination., Conclusion: A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies., (© 2023. International Osteoporosis Foundation and Bone Health and Osteoporosis Foundation.)