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.

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.

Cost-Effectiveness of SGLT2 Inhibitors in a Real-World Population: A MICADO Model-Based Analysis Using Routine Data from a GP Registry.

OBJECTIVE: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have been shown to reduce the risk of cardiovascular complications, which largely drive diabetes' health and economic burdens. Trial results indicated that SGLT2i are cost effective. However, these findings may not be generalizable to the real-world target population. This study aims to evaluate the cost effectiveness of SGLT2i in a routine care type 2 diabetes population that meets Dutch reimbursement criteria using the MICADO model. METHODS: Individuals from the Hoorn Diabetes Care System cohort (N = 15,392) were filtered to satisfy trial inclusion criteria (including EMPA-REG, CANVAS, and DECLARE-TIMI58) or satisfy the current Dutch reimbursement criteria for SGLT2i. We validated a health economic model (MICADO) by comparing simulated and observed outcomes regarding the relative risks of events in the intervention and comparator arm from three trials, and used the validated model to evaluate the long-term health outcomes using the filtered cohorts' baseline characteristics and treatment effects from trials and a review of observational studies. The incremental cost-effectiveness ratio (ICER) of SGLT2i, compared with care-as-usual, was assessed from a third-party payer perspective, measured in euros (2021 price level), using a discount rate of 4% for costs and 1.5% for effects. RESULTS: From Dutch individuals with diabetes in routine care, 15.8% qualify for the current Dutch reimbursement criteria for SGLT2i. Their characteristics were significantly different (lower HbA1c, higher age, and generally more preexisting complications) than trial populations. After validating the MICADO model, we found that lifetime ICERs of SGLT2i, when compared with usual care, were favorable (< €20,000/QALY) for all filtered cohorts, resulting in an ICER of €5440/QALY using trial-based treatment effect estimates in reimbursed population. Several pragmatic scenarios were tested, the ICERs remained favorable. CONCLUSIONS: Although the Dutch reimbursement indications led to a target group that deviates from trial populations, SGLT2i are likely to be cost effective when compared with usual care.

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.

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.

Presence of retinopathy and incident kidney and cardiovascular events in type 2 diabetes with normoalbuminuria - A post-hoc analysis of the PRIORITY randomized clinical trial.

AIMS: Baseline diabetic retinopathy (DR) and risk of development of microalbuminuria, kidney function decline, and cardiovascular events (CVEs) in type 2 diabetes. METHODS: Post-hoc analysis of the PRIORITY study including 1758 persons with type 2 diabetes and normoalbuminuria followed for a median of 2.5 (IQR: 2.0-3.0) years. DR diagnosis included non-proliferative and proliferative abnormalities, macular oedema, or prior laser treatment. Cox models were fitted to investigate baseline DR presence with development of persistent microalbuminuria (urinary albumin-creatinine ratio > 30 mg/g); chronic kidney disease (CKD) G3 (eGFR <60 ml/min/1.73m2); and CVE. Models were adjusted for relevant risk factors. RESULTS: At baseline, 304 (17.3 %) had DR. Compared to persons without DR, they were older (mean ± SD: 62.7 ± 7.7 vs 61.4 ± 8.3 years, p = 0.019), had longer diabetes duration (17.9 ± 8.4 vs. 10.6 ± 7.0 years, p < 0.001), and higher HbA1c (62 ± 13 vs. 56 ± 12 mmol/mol, p < 0.001). The adjusted hazard ratios of DR at baseline for development of microalbuminuria (n = 197), CKD (n = 166), and CVE (n = 64) were: 1.50 (95%CI: 1.07, 2.11), 0.87 (95%CI: 0.56, 1.34), and 2.61 (95%CI: 1.44, 4.72), compared to without DR. CONCLUSIONS: Presence of DR in normoalbuminuric type 2 diabetes was associated with an increased risk of developing microalbuminuria and CVE, but not with kidney function decline.

Longitudinal association of electrocardiogram abnormalities with major adverse cardiac events in people with Type 2 diabetes: the Hoorn Diabetes Care System cohort.

AIMS: To investigate the association of (changes in) electrocardiogram (ECG) abnormalities with incident major adverse cardiac events (MACE) in people with Type 2 diabetes (T2D) without pre-existing cardiovascular disease (CVD). METHODS AND RESULTS: A prospective longitudinal study of 11 993 people with T2D without known CVD from the Hoorn Diabetes Care System cohort. Annually repeated measurements (1998-2018), included cardiovascular risk factors, over 70 000 ECG, and self-reported cardiovascular events. ECG abnormalities were classified according to the Minnesota Classification as prolonged PR duration, prolonged QRS duration, left QRS-axis, QS pattern, ST-segment/T-wave abnormalities, or tall R-wave. The association of ECG abnormalities with MACEs was assessed using time-dependent Cox-regression models, adjusted for time-varying cardiovascular risk factors, and medication use [hazard ratios (HRs) with 95% confidence intervals (CIs)]. During a median follow-up of 6.6 (IQR, 3.1-10.7) years, 5445 (45.4%) of the participants had an ECG abnormality (prevalent or incident) at any of the median 6 (IQR, 3-10) annual ECG recordings, and 905 people (7.5%) had a MACE (529 coronary heart disease (CHD), 250 heart failure (HF), and 126 sudden cardiac arrest (SCA)). After adjustment, most ECG abnormalities were associated with HF: prolonged QRS duration [HR, 4.01 (95% CI, 2.67-6.03)], QS pattern [2.68 (0.85-8.49)], ST-segment/T-wave abnormalities [4.26 (2.67-6.80)], and tall R-wave [2.23 (1.33-3.76)]. Only QS pattern [2.69 (1.20-6.03)] and ST-segment/T-wave abnormalities [2.11 (1.48-3.02)] were associated with CHD. These associations were robust across age, sex, hypertension, or estimated CVD risk subgroups. CONCLUSION: In people with T2D without pre-existing CVD, ECG abnormalities related to decelerated conduction, ischaemia, and hypertrophy are predominantly early signs of emerging HF, while only abnormalities related to ischaemic disorders are signs of CHD.

In this cohort study of 11 993 people with Type 2 diabetes (T2D) that were still free of cardiovascular disease (CVD), the people with electrocardiogram (ECG) abnormalities were up to four times as likely to experience heart failure and up to twice as likely to experience a heart attack, regardless of their age, sex, blood pressure, or estimated risk of CVD. • Most ECG abnormalities are related to a higher risk of heart failure, but only ECG abnormalities that indicate reduced oxygen supply to the heart are related to a higher risk of a heart attack. • Periodical ECG examinations can help detect developing heart disease in an early stage for all people with T2D still free of CVD.

Prolongation of the heart rate-corrected QT interval is associated with cardiovascular diseases: Systematic review and meta-analysis.

BACKGROUND: Conflicting findings have described the association between prolonged heart rate-corrected QT interval (QTc) and cardiovascular disease. AIMS: To identify articles investigating the association between QTc and cardiovascular disease morbidity and mortality, and to summarize the available evidence for the general and type 2 diabetes populations. METHODS: A systematic search was performed in PubMed and Embase in May 2022 to identify studies that investigated the association between QTc prolongation and cardiovascular disease in both the general and type 2 diabetes populations. Screening, full-text assessment, data extraction and risk of bias assessment were performed independently by two reviewers. Effect estimates were pooled across studies using random-effect models. RESULTS: Of the 59 studies included, 36 qualified for meta-analysis. Meta-analysis of the general population studies showed a significant association for: overall cardiovascular disease (fatal and non-fatal) (hazard ratio [HR] 1.68, 95% confidence interval [CI] 1.33-2.12; I2=69%); coronary heart disease (fatal and non-fatal) in women (HR 1.27, 95% CI 1.08-1.50; I2=38%; coronary heart disease (fatal and non-fatal) in men (HR 2.07, 95% CI 1.26-3.39; I2=78%); stroke (HR 1.59, 95% CI 1.29-1.96; I2=45%); sudden cardiac death (HR 1.60, 95% CI 1.14-2.25; I2=68%); and atrial fibrillation (HR 1.55, 95% CI 1.31-1.83; I2=0.0%). No significant association was found for cardiovascular disease in the type 2 diabetes population. CONCLUSION: QTc prolongation was associated with risk of cardiovascular disease in the general population, but not in the type 2 diabetes population.

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

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

The DIAbetes MANagement and Treatment (DIAMANT) Cohort.

Introduction: 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.

"I am my own doctor": A qualitative study of the perspectives and decision-making process of Muslims with diabetes on Ramadan fasting.

BACKGROUND: Many Muslims with diabetes choose to fast against medical advice during Ramadan, potentially increasing their risk of acute complications. Patients are often reluctant to disclose fasting to their health care providers, and their needs regarding Ramadan are not met in consultations. For healthcare professionals to provide patient-centred care, it is important to gain more insight into patients' decision-making process. This study therefore aims to explore how Muslims with diabetes decide whether to fast during Ramadan. METHODS: A qualitative study was conducted consisting of 15 focus groups with Muslims with diabetes within a constructivist paradigm. Convenience sampling was used. All focus groups were transcribed verbatim and analyzed using Braun and Clarke's reflexive thematic analysis. RESULTS: Four themes were found to be important in the decision on whether to fast: (1) values and beliefs concerning Ramadan, (2) experiences and emotions concerning Ramadan, (3) the perception of illness, and (4) advice from health care professionals, imams and family. Many participants indicated fasting against medical advice and trusting their subjective assessments on whether they could fast. Moreover, three main stages in the decision-making process for eventually refraining from fasting were identified: (1) the stage where positive experiences with fasting dominate, (2) the stage where one encounters challenges but their determination to fast prevails and (3) the stage where one decides to refrain from fasting after experiencing too many physical difficulties with fasting. CONCLUSIONS: Muslims with diabetes experience autonomy in their decisions on Ramadan fasting. The decision to refrain from fasting often resulted from a difficult and dynamic decision-making process and was often made after participants reached their physical limits. These findings highlight the importance of not only shared decision-making to empower patients to make well-informed decisions on Ramadan fasting but also pre-Ramadan diabetes education to help people with diabetes have a safe Ramadan.

Safety risks among frail older people living at home in the Netherlands - A cross-sectional study in a routine primary care sample.

Frail older people face a range of problems and risks that could undermine their ability to live safely at home. A comprehensive overview of these risks, from a multidimensional perspective, is currently lacking. This study aims to examine the prevalence of risks in multiple domains of life among frail older people living at home. We used cross-sectional data from 824 people aged 65 years and older, who received a comprehensive geriatric assessment (the interRAI Home Care [interRAI-HC]) between 2014 and 2018, as part of routine care from 25 general practices in the region of West-Friesland, the Netherlands. The interRAI-HC identifies amenable risks related to people's clinical conditions, functioning, lifestyle and behaviour, and social and physical environment. Descriptive statistics were used to examine population characteristics (age, gender, marital status, living arrangements and presence of chronic conditions) and prevalence of risks. Most common risks were related to people's clinical conditions (i.e cardio-respiratory health, urinary incontinence, pain), functioning (i.e. limitations in instrumental activities of daily living and mood) and social environment (i.e. limitations in informal care and social functioning). More than 80% of frail older people faced multiple risks, and often on multiple domains of life simultaneously. People experiencing multiple risks per person, and on multiple domains simultaneously, were more often widowed and living alone. The multidimensional character of risks among frail older people living at home implies that an integrated approach to care, comprising both health and social care, is necessary. Insight in the prevalence of these risks can give direction to care allocation decisions.

Diagnostic value of echocardiographic markers for diastolic dysfunction and heart failure with preserved ejection fraction.

This study aimed to evaluate the diagnostic performance of echocardiographic markers of heart failure with preserved ejection fraction (HFpEF) and left ventricular diastolic dysfunction (LVDD) in comparison with the gold standard of cardiac catheterization. Diagnosing HFpEF is challenging, as symptoms are non-specific and often absent at rest. A clear need exists for sensitive echocardiographic markers to diagnose HFpEF. We systematically searched for studies testing the diagnostic value of novel echocardiographic markers for HFpEF and LVDD. Two investigators independently reviewed the studies and assessed the risk of bias. Results were meta-analysed when four or more studies reported a similar diagnostic measure. Of 353 studies, 20 fulfilled the eligibility criteria. The risk of bias was high especially in the patients' selection domain. The highest diagnostic performance was demonstrated by a multivariable model combining echocardiographic, clinical and arterial function markers with an area under the curve of 0.95 (95% CI, 0.89-0.98). A meta-analysis of four studies indicated a reasonable diagnostic performance for left atrial strain with an AUC of 0.83 (0.70-0.95), a specificity of 93% (95% CI, 90-97%) and a sensitivity of 77% (95% CI, 59-96%). Moreover, the addition of exercise E/e' improved the sensitivity of HFpEF diagnostic algorithms up to 90%, compared with 60 and 34% of guidelines alone. Despite the heterogeneity of the included studies, this review supported the current multivariable-based approach for the diagnosis of HFpEF and LVDD and showed a potential diagnostic role for exercise echocardiography and left atrial strain. Larger well-designed studies are needed to evaluate the incremental value of novel diagnostic tools to current diagnostic algorithms.

Plasma protein N-glycosylation is associated with cardiovascular disease, nephropathy, and retinopathy in type 2 diabetes.

INTRODUCTION: Although associations of total plasma N-glycome (TPNG) with type 2 diabetes have been reported, little is known on the role of TPNG in type 2 diabetes complications, a major cause of type 2 diabetes-related morbidity and mortality. Here, we assessed TPNG in relation to type 2 diabetes complications in subsamples of two Dutch cohorts using mass spectrometry (n=1815 in DiaGene and n=1518 in Hoorn Diabetes Care System). RESEARCH DESIGN AND METHODS: Blood plasma samples and technical replicates were pipetted into 96-well plates in a randomized manner. Peptide:N-glycosidase F (PNGase F) was used to release N-glycans, whereafter sialic acids were derivatized for stabilization and linkage differentiation. After total area normalization, 68 individual glycan compositions were quantified in total and were used to calculate 45 derived traits which reflect structural features of glycosylation. Associations of glycan features with prevalent and incident microvascular or macrovascular complications were tested in logistic and Cox regression in both independent cohorts and the results were meta-analyzed. RESULTS: Our results demonstrated similarities between incident and prevalent complications. The strongest association for prevalent cardiovascular disease was a high level of bisection on a group of diantennary glycans (A2FS0B; OR=1.38, p=1.34×10-11), while for prevalent nephropathy the increase in 2,6-sialylation on triantennary glycans was most pronounced (A3E; OR=1.28, p=9.70×10-6). Several other TPNG features, including fucosylation, galactosylation, and sialylation, firmly demonstrated associations with prevalent and incident complications of type 2 diabetes. CONCLUSIONS: These findings may provide a glance on how TPNG patterns change before complications emerge, paving the way for future studies on prediction biomarkers and potentially disease mechanisms.

Performance of prediction models for nephropathy in people with type 2 diabetes: systematic review and external validation study.

OBJECTIVES: To identify and assess the quality and accuracy of prognostic models for nephropathy and to validate these models in external cohorts of people with type 2 diabetes. DESIGN: Systematic review and external validation. DATA SOURCES: PubMed and Embase. ELIGIBILITY CRITERIA: Studies describing the development of a model to predict the risk of nephropathy, applicable to people with type 2 diabetes. METHODS: Screening, data extraction, and risk of bias assessment were done in duplicate. Eligible models were externally validated in the Hoorn Diabetes Care System (DCS) cohort (n=11 450) for the same outcomes for which they were developed. Risks of nephropathy were calculated and compared with observed risk over 2, 5, and 10 years of follow-up. Model performance was assessed based on intercept adjusted calibration and discrimination (Harrell's C statistic). RESULTS: 41 studies included in the systematic review reported 64 models, 46 of which were developed in a population with diabetes and 18 in the general population including diabetes as a predictor. The predicted outcomes included albuminuria, diabetic kidney disease, chronic kidney disease (general population), and end stage renal disease. The reported apparent discrimination of the 46 models varied considerably across the different predicted outcomes, from 0.60 (95% confidence interval 0.56 to 0.64) to 0.99 (not available) for the models developed in a diabetes population and from 0.59 (not available) to 0.96 (0.95 to 0.97) for the models developed in the general population. Calibration was reported in 31 of the 41 studies, and the models were generally well calibrated. 21 of the 64 retrieved models were externally validated in the Hoorn DCS cohort for predicting risk of albuminuria, diabetic kidney disease, and chronic kidney disease, with considerable variation in performance across prediction horizons and models. For all three outcomes, however, at least two models had C statistics >0.8, indicating excellent discrimination. In a secondary external validation in GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland), models developed for diabetic kidney disease outperformed those for chronic kidney disease. Models were generally well calibrated across all three prediction horizons. CONCLUSIONS: This study identified multiple prediction models to predict albuminuria, diabetic kidney disease, chronic kidney disease, and end stage renal disease. In the external validation, discrimination and calibration for albuminuria, diabetic kidney disease, and chronic kidney disease varied considerably across prediction horizons and models. For each outcome, however, specific models showed good discrimination and calibration across the three prediction horizons, with clinically accessible predictors, making them applicable in a clinical setting. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42020192831.

The interobserver agreement of ECG abnormalities using Minnesota codes in people with type 2 diabetes.

OBJECTIVES: To assess the interobserver agreement in categories of electrocardiogram (ECG) abnormalities using the Minnesota Code criteria. METHODS: We used a random sample of 180 ECGs from people with type 2 diabetes. ECG abnormalities were classified and coded using the Minnesota ECG Classification. Each ECG was independently rated on several abnormalities by an experienced rater (rater 1) and by two cardiologists (raters 2 and 3) trained to apply the Minnesota codes on four Minnesota codes; 1-codes as an indication for myocardial infarction, 4 en 5-codes as an indication for ischemic abnormalities, 3-codes as an indication for left ventricle hypertrophy, 7-1-codes as an indication for ventricular conduction abnormalities, and 8-3-codes as an indication for atrial fibrillation / atrial flutter. After all pairwise tables were summed, the overall agreement, the specific positive and negative agreement were calculated with a 95% confidence interval (CI) for each abnormality. Also, Kappa's with a 95% CI were calculated. RESULTS: The overall agreement (with 95% CI) were for myocardial infarction, ischemic abnormalities, left ventricle hypertrophy, conduction abnormalities and atrial fibrillation/atrial flutter respectively: 0.87 (0.84-0.91), 0.79 (0.74-0.84), 0.81 (0.76-0.85), 0.93 (0.90-0.95), 0.96 (0.93-0.97). CONCLUSION: This study shows that the overall agreement of the Minnesota code is good to excellent.

Prognostic models for predicting the risk of foot ulcer or amputation in people with type 2 diabetes: a systematic review and external validation study.

AIMS/HYPOTHESIS: Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10-20 times higher than that of people without type 2 diabetes. Prognostic models can aid in targeted monitoring but an overview of their performance is lacking. This study aimed to systematically review prognostic models for the risk of foot ulcer or amputation and quantify their predictive performance in an independent cohort. METHODS: A systematic review identified studies developing prognostic models for foot ulcer or amputation over minimal 1 year follow-up applicable to people with type 2 diabetes. After data extraction and risk of bias assessment (both in duplicate), selected models were externally validated in a prospective cohort with a 5 year follow-up in terms of discrimination (C statistics) and calibration (calibration plots). RESULTS: We identified 21 studies with 34 models predicting polyneuropathy, foot ulcer or amputation. Eleven models were validated in 7624 participants, of whom 485 developed an ulcer and 70 underwent amputation. The models for foot ulcer showed C statistics (95% CI) ranging from 0.54 (0.54, 0.54) to 0.81 (0.75, 0.86) and models for amputation showed C statistics (95% CI) ranging from 0.63 (0.55, 0.71) to 0.86 (0.78, 0.94). Most models underestimated the ulcer or amputation risk in the highest risk quintiles. Three models performed well to predict a combined endpoint of amputation and foot ulcer (C statistics >0.75). CONCLUSIONS/INTERPRETATION: Thirty-four prognostic models for the risk of foot ulcer or amputation were identified. Although the performance of the models varied considerably, three models performed well to predict foot ulcer or amputation and may be applicable to clinical practice.

Discovery of predictors of sudden cardiac arrest in diabetes: rationale and outline of the RESCUED (REcognition of Sudden Cardiac arrest vUlnErability in Diabetes) project.

INTRODUCTION: Early recognition of individuals with increased risk of sudden cardiac arrest (SCA) remains challenging. SCA research so far has used data from cardiologist care, but missed most SCA victims, since they were only in general practitioner (GP) care prior to SCA. Studying individuals with type 2 diabetes (T2D) in GP care may help solve this problem, as they have increased risk for SCA, and rich clinical datasets, since they regularly visit their GP for check-up measurements. This information can be further enriched with extensive genetic and metabolic information. AIM: To describe the study protocol of the REcognition of Sudden Cardiac arrest vUlnErability in Diabetes (RESCUED) project, which aims at identifying clinical, genetic and metabolic factors contributing to SCA risk in individuals with T2D, and to develop a prognostic model for the risk of SCA. METHODS: The RESCUED project combines data from dedicated SCA and T2D cohorts, and GP data, from the same region in the Netherlands. Clinical data, genetic data (common and rare variant analysis) and metabolic data (metabolomics) will be analysed (using classical analysis techniques and machine learning methods) and combined into a prognostic model for risk of SCA. CONCLUSION: The RESCUED project is designed to increase our ability at early recognition of elevated SCA risk through an innovative strategy of focusing on GP data and a multidimensional methodology including clinical, genetic and metabolic analyses.

Prevalence of ECG abnormalities in people with type 2 diabetes: The Hoorn Diabetes Care System cohort.

AIMS: The American Diabetes Association, and the joint European Society of Cardiology and European Association for the Study of Diabetes guidelines recommend a resting ECG in people with type 2 diabetes with hypertension or suspected cardiovascular disease (CVD). However, knowledge on the prevalence of ECG abnormalities is incomplete. We aimed to analyse the prevalence of ECG abnormalities and their cross-sectional associations with cardiovascular risk factors in people with type 2 diabetes. METHODS: We used data of the Diabetes Care System cohort obtained in 2018. ECG abnormalities were defined using the Minnesota Classification and categorised into types of abnormalities. The prevalence was calculated for the total population (n = 8068) and the subgroup of people without a history of CVD (n = 6494). Logistic regression models were used to asses cross-sectional associations. RESULTS: Approximately one-third of the total population had minor (16.0%) or major (13.1%) ECG abnormalities. Of the participants without a CVD history, approximately one-quarter had minor (14.9%) or major (9.1%) ECG abnormalities, and for those with hypertension or very high CVD risk, the prevalence was 27.5% and 39.6%, respectively. ECG abnormalities were significantly and consistently associated with established CVD risk factors. CONCLUSIONS: Resting ECG abnormalities are common in all people with type 2 diabetes (29.1%), including those without a history of CVD (24.0%), and their prevalence is related to traditional cardiovascular risk factors such as older age, male sex, hypertension, lower HDL cholesterol, higher BMI, and smoking behaviour.

Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes: An IMI-DIRECT study.

AIM: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. METHODS: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. RESULTS: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. CONCLUSIONS: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.