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, 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.

Adverse Lipid Profiles Are Associated with Lower Dementia Risk in Older People.

OBJECTIVE: Midlife dyslipidemia is associated with higher risk of dementia in late-life dementia, but the impact of late-life dyslipidemia on dementia risk is uncertain. This may be due to the large heterogeneity in cholesterol measures and study designs employed. We used detailed data from a large prospective cohort of older persons to comprehensively assess the relation between a broad range of cholesterol measures and incident dementia, addressing potential biases, confounders, and modifiers. DESIGN: Post hoc observational analysis based on data from a dementia prevention trial (PreDIVA). SETTING AND PARTICIPANTS: 3392 community-dwelling individuals, without dementia, aged 70-78 years at baseline (recruited between June 2006 and March 2009). METHODS: Total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides, and apolipoprotein A1 and B were assessed. Over a median of 6.7 years' follow-up, dementia was established by clinical diagnosis confirmed by independent outcome adjudication. Hazard ratios (HRs) for dementia and mortality were calculated using Cox regression. RESULTS: Dementia occurred in 231 (7%) participants. One-SD increase in LDL/HDL conveyed a 19% (P = .01) lower dementia risk and a 10% (P = .02) lower risk of dementia/mortality combined. This was independent of age, cardiovascular risk factors, cognitive function, apolipoprotein E genotype, and cholesterol-lowering drugs (CLD). This association was not influenced by the competing risk of mortality. Consistent and significant interactions suggested these associations were predominant in individuals with low body mass index (BMI) and higher education. CONCLUSIONS AND IMPLICATIONS: Dyslipidemia in older individuals was associated with a lower risk of dementia. Low BMI and higher education level mitigate poor outcomes associated with dyslipidemia. These findings suggest that a different approach may be appropriate for interpreting lipid profiles that are conventionally considered adverse in older adults. Such an approach may aid predicting dementia risk and designing intervention studies aimed at reducing dementia risk in older populations.

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.

Antihypertensive medication classes and risk of incident dementia in primary care patients: a longitudinal cohort study in the Netherlands.

Background: Hypertension is a modifiable risk factor for dementia affecting over 70% of individuals older than 60. Lowering dementia risk through preferential treatment with antihypertensive medication (AHM) classes that are otherwise equivalent in indication could offer a cost-effective, safe, and accessible approach to reducing dementia incidence globally. Certain AHM-classes have been associated with lower dementia risk, potentially attributable to angiotensin-II-receptor (Ang-II) stimulating properties. Previous study results have been inconclusive, possibly due to heterogeneous methodology and limited power. We aimed to comprehensively investigate associations between AHM (sub-)classes and dementia risk using large-scale continuous, real-world prescription and outcome data from primary care. Methods: We used data from three Dutch General Practice Registration Networks. Primary endpoints were clinical diagnosis of incident all-cause dementia and mortality. Using Cox regression analysis with time-dependent covariates, we compared the use of angiotensin-converting enzyme inhibitors (ACEi) to angiotensin receptor blockers (ARBs), beta blockers, calcium channel blockers (CCBs), and diuretics; and Ang-II-stimulating- to Ang-II-inhibiting AHM. Findings: Of 133,355 AHM-using participants, 5877 (4.4%) developed dementia, and 14,079 (10.6%) died during a median follow-up of 7.6 [interquartile range = 4.1-11.0] years. Compared to ACEi, ARBs [HR = 0.86 (95% CI = 0.80-0.92)], beta blockers [HR = 0.81 (95% CI = 0.75-0.87)], CCBs [HR = 0.77 (95% CI = 0.71-0.84)], and diuretics [HR = 0.65 (95% CI = 0.61-0.70)] were associated with significantly lower dementia risks. Regarding competing risk of death, beta blockers [HR = 1.21 (95% CI = 1.15-1.27)] and diuretics [HR = 1.69 (95% CI = 1.60-1.78)] were associated with higher, CCBs with similar, and ARBs with lower [HR = 0.83 (95% CI = 0.80-0.87)] mortality risk. Dementia [HR = 0.88 (95% CI = 0.82-0.95)] and mortality risk [HR = 0.86 (95% CI = 0.82-0.91)] were lower for Ang-II-stimulating versus Ang-II-inhibiting AHM. There were no interactions with sex, diabetes, cardiovascular disease, and number of AHM used. Interpretation: Among patients receiving AHM, ARBs, CCBs, and Ang-II-stimulating AHM were associated with lower dementia risk, without excess mortality explaining these results. Extensive subgroup and sensitivity analyses suggested that confounding by indication did not importantly influence our findings. Dementia risk may be influenced by AHM-classes' angiotensin-II-receptor stimulating properties. An RCT comparing BP treatment with different AHM classes with dementia as outcome is warranted. Funding: Netherlands Organisation for Health, Research and Development (ZonMw); Stoffels-Hornstra Foundation.

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.

Prevention of dementia using mobile phone applications (PRODEMOS): a multinational, randomised, controlled effectiveness-implementation trial.

BACKGROUND: The expected increase of dementia prevalence in the coming decades will mainly be in low-income and middle-income countries and in people with low socioeconomic status in high-income countries. This study aims to reduce dementia risk factors in underserved populations at high-risk using a coach-supported mobile health (mHealth) intervention. METHODS: This open-label, blinded endpoint, hybrid effectiveness-implementation randomised controlled trial (RCT) investigated whether a coach-supported mHealth intervention can reduce dementia risk in people aged 55-75 years of low socioeconomic status in the UK or from the general population in China with at least two dementia risk factors. The primary effectiveness outcome was change in cardiovascular risk factors, ageing, and incidence of dementia (CAIDE) risk score from baseline to after 12-18 months of intervention. Implementation outcomes were coverage, adoption, sustainability, appropriateness, acceptability, fidelity, feasibility, and costs assessed using a mixed-methods approach. All participants with complete data on the primary outcome, without imputation of missing outcomes were included in the analysis (intention-to-treat principle). This trial is registered with ISRCTN, ISRCTN15986016, and is completed. FINDINGS: Between Jan 15, 2021, and April 18, 2023, 1488 people (601 male and 887 female) were randomly assigned (734 to intervention and 754 to control), with 1229 (83%) of 1488 available for analysis of the primary effectiveness outcome. After a mean follow-up of 16 months (SD 2·5), the mean CAIDE score improved 0·16 points in the intervention group versus 0·01 in the control group (mean difference -0·16, 95% CI -0·29 to -0·03). 1533 (10%) invited individuals responded; of the intervention participants, 593 (81%) of 734 adopted the intervention and 367 (50%) of 734 continued active participation throughout the study. Perceived appropriateness (85%), acceptability (81%), and fidelity (79%) were good, with fair overall feasibility (53% of intervention participants and 58% of coaches), at low cost. No differences in adverse events between study arms were found. INTERPRETATION: A coach-supported mHealth intervention is modestly effective in reducing dementia risk factors in those with low socioeconomic status in the UK and any socioeconomic status in China. Implementation is challenging in these populations, but those reached actively participated. Whether this intervention will result in less cognitive decline and dementia requires a larger RCT with long follow-up. FUNDING: EU Horizon 2020 Research and Innovation Programme and the National Key R&D Programmes of China. TRANSLATION: For the Mandarin translation of the abstract see Supplementary Materials section.

The association of cardiometabolic, diet and lifestyle parameters with plasma glucagon-like peptide-1: An IMI DIRECT study.

CONTEXT: The role of glucagon-like peptide-1(GLP-1) in Type 2 diabetes (T2D) and obesity is not fully understood. OBJECTIVE: We investigate the association of cardiometabolic, diet and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. METHOD: We analysed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1(n=2127) individuals at risk of diabetes; cohort 2 (n=789) individuals with new-onset of T2D. RESULTS: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin resistant phenotype and observe a strong independent relationship with male sex, increased adiposity and liver fat particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycaemia, higher adiposity, liver fat, male sex and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit and vegetables inpeople with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. CONCLUSION: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D.

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.

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.

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.

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.

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.

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.

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.

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.

The entero-endocrine response following a mixed-meal tolerance test with a non-nutritive pre-load in participants with pre-diabetes and type 2 diabetes: A crossover randomized controlled trial proof of concept study.

INTRODUCTION: This crossover randomized controlled trial (RCT) investigated differences in short-term entero-endocrine response to a mixed-meal tolerance test preceded by nutrient sensing between participants with pre-diabetes (pre-T2D) and type 2 diabetes (T2D). Additionally, differences in gut and oral microbiome composition between participants with a high and low entero-endocrine response were investigated. RESEARCH DESIGN AND METHODS: Ten participants with pre-T2D and ten with T2D underwent three test days with pre-loads consisting of either swallowing water (control), or rinsing with a non-nutritive sweetener solution, or swallowing the sweetener solution before a mixed-meal tolerance test. Blood glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide-1 (GLP-1), glucagon, glucose, insulin and peptide YY (PYY) were determined at t = -20, 0, 15, 30, 60, 120 and 240 minutes. The composition of the oral and gut microbiome at baseline were also determined. RESULTS: The entero-endocrine response differed by pre-loads, e.g. a lower PYY response after swallowing the non-nutritive sweetener (-3585.2pg/mL [95% CI: -6440.6; -729.8]; p = 0.01). But it also differed by T2D status, e.g. a higher glucose, glucagon and PYY response was found in participants with T2D, compared to those with pre-T2D. Evidence for associations between the oral and gut microbiome composition and the entero-endocrine response was limited. Still, the level of entero-endocrine response was associated with several oral microbiome measures. Higher oral anterior α-diversity was associated with a lower PYY response (e.g. Inverse Simpson index -1357pg/mL [95% CI -2378; -336; 1.24]), and higher oral posterior α-diversitywith a higher GIP response (e.g. Inverse Simpson index 6773pg/mL [95% CI 132; 13414]) in models adjusted for sex, age and T2D status. CONCLUSIONS: Non-nutritive pre-loads influence the entero-endocrine response to a mixed-meal, and this effect varies based on (pre-)T2D status. The entero-endocrine response is likely not associated with the gut microbiome, and there is limited evidence for association with the α-diversity of the oral microbiome composition. TRIAL REGISTRATION: Trial register: Netherlands Trial Register NTR7212, accessible through International Clinical Trials Registry Platform: ICTRP Search Portal (who.int).

The Lancet Commission to reduce the global burden of sudden cardiac death: a call for multidisciplinary action.

Despite major advancements in cardiovascular medicine, sudden cardiac death (SCD) continues to be an enormous medical and societal challenge, claiming millions of lives every year. Efforts to prevent SCD are hampered by imperfect risk prediction and inadequate solutions to specifically address arrhythmogenesis. Although resuscitation strategies have witnessed substantial evolution, there is a need to strengthen the organisation of community interventions and emergency medical systems across varied locations and health-care structures. With all the technological and medical advances of the 21st century, the fact that survival from sudden cardiac arrest (SCA) remains lower than 10% in most parts of the world is unacceptable. Recognising this urgent need, the Lancet Commission on SCD was constituted, bringing together 30 international experts in varied disciplines. Consistent progress in tackling SCD will require a completely revamped approach to SCD prevention, with wide-sweeping policy changes that will empower the development of both governmental and community-based programmes to maximise survival from SCA, and to comprehensively attend to survivors and decedents' families after the event. International collaborative efforts that maximally leverage and connect the expertise of various research organisations will need to be prioritised to properly address identified gaps. The Commission places substantial emphasis on the need to develop a multidisciplinary strategy that encompasses all aspects of SCD prevention and treatment. The Commission provides a critical assessment of the current scientific efforts in the field, and puts forth key recommendations to challenge, activate, and intensify efforts by both the scientific and global community with new directions, research, and innovation to reduce the burden of SCD worldwide.

Identification of frailty in primary care: accuracy of electronically derived measures.

BACKGROUND: Routinely collected clinical data based on electronic medical records could be used to define frailty. AIM: To estimate the ability of four potential frailty measures that use electronic medical record data to identify older patients who were frail according to their GP. DESIGN AND SETTING: This retrospective cohort study used data from 36 GP practices in the Dutch PHARMO Data Network. METHOD: The measures were the Dutch Polypharmacy Index, Charlson Comorbidity Index (CCI), Chronic Disease Score (CDS), and Frailty Index. GPs' clinical judgement of patients' frailty status was considered the reference standard. Performance of the measures was assessed with the area under the receiver operating characteristic curve (AUC). Analyses were done in the total population and stratified by age and sex. RESULTS: Of 31 511 patients aged ≥65 years, 3735 (11.9%) patients were classified as frail by their GP. The CCI showed the highest AUC (0.79, 95% confidence interval [CI] = 0.78 to 0.80), followed by the CDS (0.69, 95% CI = 0.68 to 0.70). Overall, the measures showed poorer performance in males and females aged ≥85 years than younger age groups (AUC 0.55-0.58 in females and 0.57-0.60 in males). CONCLUSION: This study showed that of four frailty measures based on electronic medical records in primary care only the CCI had an acceptable performance to assess frailty compared with frailty assessments done by professionals. In the youngest age groups diagnostic performance was acceptable for all measures. However, performance declined with older age and was least accurate in the oldest age group, thereby limiting the use in patients of most interest.

Dispatch of Volunteer Responders to Out-of-Hospital Cardiac Arrests.

BACKGROUND: Systems for dispatch of volunteer responders to collect automated external defibrillators and/or to provide cardiopulmonary resuscitation (CPR) in cases of nearby out-of-hospital cardiac arrest (OHCA) are widely implemented. OBJECTIVES: This study aimed to investigate whether the activation of a volunteer responder system to OHCAs was associated with higher rates of bystander CPR, bystander defibrillation, and 30-day survival vs no system activation. METHODS: This was a retrospective observational analysis within the ESCAPE-NET (European Sudden Cardiac Arrest network: Towards Prevention, Education, New Effective Treatment) collaborative research network. Included were cases of OHCA between 2015 and 2019 from 5 European sites with volunteer responder systems. At all sites, systems were activated by dispatchers at the emergency medical communication center in response to suspected OHCA. Exposed cases (system activation) were compared with nonexposed cases (no system activation). Risk ratios (RRs) were calculated for the outcomes of bystander CPR, bystander defibrillation, and 30-day survival after inverse probability treatment weighting. Missing data were handled using multiple imputation. RESULTS: In total, 9,553 cases were included. In 4,696 cases, the volunteer responder system was activated, and in 4,857 it was not. The pooled RRs were 1.30 (95% CI: 1.15-1.47) for bystander CPR, 1.89 (95% CI: 1.36-2.63) for bystander defibrillation, and 1.22 (95% CI: 1.07-1.39) for 30-day survival. CONCLUSIONS: Activation of a volunteer response system in cases of OHCA was associated with a higher chance of bystander CPR, bystander defibrillation, and 30-day survival vs no system activation. A randomized controlled trial is necessary to determine fully the causal effect of volunteer responder systems.