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.

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.

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.

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.

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.

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.

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.

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.

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.

Data-driven sudden cardiac arrest research in Europe: Experts' perspectives on ethical challenges and governance strategies.

Background: Observational studies using large-scale databases and biobanks help improve prevention and treatment of sudden cardiac arrest (SCA) but the lack of guidance on data protection issues in this setting may harm patients' rights and the research enterprise itself. This qualitative study explored the ethical aspects of observational SCA research, as well as solutions. Methods: European experts in SCA research, medical ethics and health law reflected on this topic through semi-structured interviews (N = 29) and a virtual roundtable conference (N = 18). The ESCAPE-NET project served as a discussion case. Findings were coded and thematically analysed. Results: The first theme concerned the potential benefits and harms (at individual and group level) of observational data-based SCA studies and included the following sub-themes: societal value, scientific validity, data privacy, disclosure of genetic findings, stigma and discrimination, and medicalisation of sudden death. The second theme involved governance through 'privacy by design', 'privacy by policy' and associated regulation and oversight. Sub-themes were: de-identification of data, informed consent (broad and deferred), ethics review, and harmonisation. Conclusions: Researchers and scientific societies should be aware that ethico-legal issues may arise during data-driven studies in SCA and other emergencies. These can be mitigated by combining technical data protection safeguards with appropriate informed consent policies and proportional ethics oversight. To ensure responsible conduct of data research in emergency medicine, we recommend the establishment of 'codes of conduct' which should be developed in interdisciplinary groups and together with patient representatives.

Prolongation of the QTc interval is associated with an increased risk of cardiovascular diseases: The Hoorn study.

BACKGROUND/OBJECTIVE: Prolonged heart rate-corrected QT interval (QTc) on the electrocardiogram (ECG) is maybe associated with the occurrence of cardiovascular diseases (CVD), but the evidence is inconsistent. Therefore, we investigated whether baseline prolongation of the QTc interval is associated with CVD morbidity and mortality and its subtypes and whether glucose tolerance modifies this association in a population-based cohort study with a mean follow-up of 10.8 years. METHODS: We analyzed a glucose tolerance stratified sample (N = 487) from the longitudinal population-based Hoorn Study cohort (age 64 ± 7 years, 48% female). Cox regression was used to investigate the association between sex-specific baseline QTc quartiles and CVD morbidity and mortality. The risk was also estimated per 10 ms increase in QTc. All analyses were adjusted for age, sex, smoking status, systolic blood pressure, prevalent CVD, glucose tolerance status, hypertension and total cholesterol. In addition, stratified analyses were conducted for glucose tolerance status. RESULTS: During a mean follow-up of 10.8 years, 351 CVD events were observed. The adjusted hazard ratios (95% CI) for each 10 ms increase in QTc interval were 1.06 (95% CI: 1.02-1.10) for CVD, 1.06 (95% CI: 0.97-1.15) for acute myocardial infarction, 1.07 (95% CI: 1.01-1.13) for stroke, 1.12 (95% CI: 1.06-1.19) for heart failure, 1.04 (95% CI: 0.96-1.12) for peripheral arterial disease and 1.01 (95% CI:0.95-1.08) for coronary heart disease. Glucose tolerance status did not modify the association (P > 0.2). CONCLUSION/INTERPRETATION: Prolongation of the QTc interval is associated with morbidity and mortality due to general CVD. Glucose tolerance status did not modify these associations.

Patient-reported outcomes for people with diabetes: what and how to measure? A narrative review.

Patient-reported outcomes (PROs) are valuable for shared decision making and research. Patient-reported outcome measures (PROMs) are questionnaires used to measure PROs, such as health-related quality of life (HRQL). Although core outcome sets for trials and clinical practice have been developed separately, they, as well as other initiatives, recommend different PROs and PROMs. In research and clinical practice, different PROMs are used (some generic, some disease-specific), which measure many different things. This is a threat to the validity of research and clinical findings in the field of diabetes. In this narrative review, we aim to provide recommendations for the selection of relevant PROs and psychometrically sound PROMs for people with diabetes for use in clinical practice and research. Based on a general conceptual framework of PROs, we suggest that relevant PROs to measure in people with diabetes are: disease-specific symptoms (e.g. worries about hypoglycaemia and diabetes distress), general symptoms (e.g. fatigue and depression), functional status, general health perceptions and overall quality of life. Generic PROMs such as the 36-Item Short Form Health Survey (SF-36), WHO Disability Assessment Schedule (WHODAS 2.0), or Patient-Reported Outcomes Measurement Information System (PROMIS) measures could be considered to measure commonly relevant PROs, supplemented with disease-specific PROMs where needed. However, none of the existing diabetes-specific PROM scales has been sufficiently validated, although the Diabetes Symptom Self-Care Inventory (DSSCI) for measuring diabetes-specific symptoms and the Diabetes Distress Scale (DDS) and Problem Areas in Diabetes (PAID) for measuring distress showed sufficient content validity. Standardisation and use of relevant PROs and psychometrically sound PROMs can help inform people with diabetes about the expected course of disease and treatment, for shared decision making, to monitor outcomes and to improve healthcare. We recommend further validation studies of diabetes-specific PROMs that have sufficient content validity for measuring disease-specific symptoms and consider generic item banks developed based on item response theory for measuring commonly relevant PROs.

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

BACKGROUND: The COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting. METHODS: Based on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated. DISCUSSION: Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.

Validation of the ARIC prediction model for sudden cardiac death in the European population: The ESCAPE-NET project.

BACKGROUND: Sudden cardiac death is responsible for 10% to 20% of all deaths in Europe. The current study investigates how well the risk of sudden cardiac death can be predicted. To this end, we validated a previously developed prediction model for sudden cardiac death from the Atherosclerosis Risk in Communities study (USA). METHODS: Data from participants of the Copenhagen City Heart Study (CCHS) (n=9988) was used to externally validate the previously developed prediction model for sudden cardiac death. The model's performance was assessed through discrimination (C-statistic) and calibration by the Hosmer-Lemeshow goodness-of-fit (HL) statistics suited for censored data and visual inspection of calibration plots. Additional validation was performed using data from the Hoorn Study (N=2045), employing the same methods. RESULTS: During ten years of follow-up of CCHS participants (mean age: 58.7 years, 56.2% women), 425 experienced SCD (4.2%). The prediction model showed good discrimination for sudden cardiac death risk (C-statistic: 0.81, 95% CI: 0.79-0.83). Calibration was robust (HL statistic: P=0.8). Visual inspection of the calibration plot showed that the calibration could be improved. Sensitivity was 89.8%, and specificity was 60.6%. The positive and negative predictive values were 10.1% and 99.2%. Model performance was similar in the Hoorn Study (C-statistic: 0.81, 95% CI: 0.77-0.85 and the HL statistic: 1.00). CONCLUSION: Our study showed that the previously developed prediction model in North American adults performs equally well in identifying those at risk for sudden cardiac death in a general North-West European population. However, the positive predictive value is low.

Social jet lag and (changes in) glycemic and metabolic control in people with type 2 diabetes.

OBJECTIVE: Social jet lag, i.e., the discordance among social and biological rhythms, is associated with poor metabolic control. This study aimed to assess cross-sectional and longitudinal associations among social jet lag and glycemic and metabolic control in people with type 2 diabetes. METHODS: In a prospective cohort (N = 990) with type 2 diabetes, social jet lag was measured at baseline using daily diaries and was categorized (high, moderate, or low). Metabolic outcomes were assessed at baseline and at 1 and 2 years of follow-up. Associations among social jet lag and glycemic and metabolic control were analyzed using linear regression and linear mixed models adjusted for confounding factors. Analyses were stratified for work status (retired vs. working; p value for interaction = 0.007 for glycated hemoglobin [HbA1c]). RESULTS: In working people, a cross-sectional association between high social jet lag and HbA1c (1.87 mmol/mol [95% CI: 0.75 to 2.99]) and blood pressure (5.81 mm Hg [95% CI: 4.04 to 7.59]) was observed. For retired people, high social jet lag was negatively associated with HbA1c (-1.58 mmol/mol [95% CI: -2.54 to -0.62]), glucose (-0.19 mmoL/L [95% CI:-0.36 to -0.01]), and blood pressure (-3.70 mm Hg [95% CI: -5.36 to -2.04]), and the association with BMI was positive (1.12 kg/m2 [95% CI: 0.74 to 1.51]). Prospective associations had the same direction as cross-sectional findings but were nonsignificant for working or retired people. CONCLUSIONS: Social jet lag was cross-sectionally, but not prospectively, associated with glycemic and metabolic markers. Interaction with work status was present, and directions of the associations were generally detrimental in the working population, whereas higher social jet lag was associated with improved glycemic and metabolic control for retired people.