Development and validation of a lifetime prediction model for incident type 2 diabetes in patients with established cardiovascular disease: the CVD2DM model.

AIMS: Identifying patients with established cardiovascular disease (CVD) who are at high risk of type 2 diabetes (T2D) may allow for early interventions, reducing the development of T2D and associated morbidity. The aim of this study was to develop and externally validate the CVD2DM model to estimate the 10-year and lifetime risks of T2D in patients with established CVD. METHODS AND RESULTS: Sex-specific, competing risk-adjusted Cox proportional hazard models were derived in 19 281 participants with established CVD and without diabetes at baseline from the UK Biobank. The core model's pre-specified predictors were age, current smoking, family history of diabetes mellitus, body mass index, systolic blood pressure, fasting plasma glucose, and HDL cholesterol. The extended model also included HbA1c. The model was externally validated in 3481 patients from the UCC-SMART study. During a median follow-up of 12.2 years (interquartile interval 11.3-13.1), 1628 participants with established CVD were diagnosed with T2D in the UK Biobank. External validation c-statistics were 0.79 [95% confidence interval (CI) 0.76-0.82] for the core model and 0.81 (95% CI 0.78-0.84) for the extended model. Calibration plots showed agreement between predicted and observed 10-year risk of T2D. CONCLUSION: The 10-year and lifetime risks of T2D can be estimated with the CVD2DM model in patients with established CVD, using readily available clinical predictors. The model would benefit from further validation across diverse ethnic groups to enhance its applicability. Informing patients about their T2D risk could motivate them further to adhere to a healthy lifestyle.

In this study, we developed and externally validated the CVD2DM model, which predicts the 10-year and lifetime risk of type 2 diabetes (T2D) in individuals who already have cardiovascular disease (CVD). The key findings are as follows: The CVD2DM model is the first model to estimate the risk of developing T2D applicable in all patients with atherosclerotic CVD. The model is based on several factors available in clinical practice, such as age, fasting plasma glucose, family history of diabetes, and body mass index. It was developed in 19 281 patients from the UK Biobank. The model performed well in 3481 patients from the UCC-SMART study.Informing patients about their T2D risk could motivate them further to adhere to a healthy lifestyle.

Lifetime and 10-year cardiovascular risk prediction in individuals with type 1 diabetes: The LIFE-T1D model.

AIMS: To develop and externally validate the LIFE-T1D model for the estimation of lifetime and 10-year risk of cardiovascular disease (CVD) in individuals with type 1 diabetes. MATERIALS AND METHODS: A sex-specific competing risk-adjusted Cox proportional hazards model was derived in individuals with type 1 diabetes without prior CVD from the Swedish National Diabetes Register (NDR), using age as the time axis. Predictors included age at diabetes onset, smoking status, body mass index, systolic blood pressure, glycated haemoglobin level, estimated glomerular filtration rate, non-high-density lipoprotein cholesterol, albuminuria and retinopathy. The model was externally validated in the Danish Funen Diabetes Database (FDDB) and the UK Biobank. RESULTS: During a median follow-up of 11.8 years (interquartile interval 6.1-17.1 years), 4608 CVD events and 1316 non-CVD deaths were observed in the NDR (n = 39 756). The internal validation c-statistic was 0.85 (95% confidence interval [CI] 0.84-0.85) and the external validation c-statistics were 0.77 (95% CI 0.74-0.81) for the FDDB (n = 2709) and 0.73 (95% CI 0.70-0.77) for the UK Biobank (n = 1022). Predicted risks were consistent with the observed incidence in the derivation and both validation cohorts. CONCLUSIONS: The LIFE-T1D model can estimate lifetime risk of CVD and CVD-free life expectancy in individuals with type 1 diabetes without previous CVD. This model can facilitate individualized CVD prevention among individuals with type 1 diabetes. Validation in additional cohorts will improve future clinical implementation.

Age at cardiovascular disease onset, dementia risk, and the role of lifestyle factors.

INTRODUCTION: We first examined the role of age at cardiovascular disease (CVD) onset for incident dementia, and then examined whether lifestyle factors at guideline-recommended levels in individuals with CVD mitigates dementia risk. METHODS: We used population-based data (Whitehall II: n = 10,308/baseline 1985-1988/examinations every 4-5 years). Lifestyle factors (non-smoking, body mass index [BMI], physical activity, diet) were extracted post-CVD. RESULTS: Over a median of 31.6 years, 3275 (32.1%) developed CVD. At age 70, risk of dementia was higher in individuals with CVD onset before (hazard ratio [HR] of incident dementia for participants with CVD before age 60, using participants without CVD at age 70 as the reference: 1.56, 95% confidence interal [CI] 1.18-2.08) but not after 60 years. In participants with CVD, a greater number of lifestyle factors at recommended levels post-CVD was associated with a lower dementia risk (per lifestyle factor at recommended level HR: 0.73, 95% CI 0.59-0.92). DISCUSSION: Our results suggest that early onset CVD is associated with a higher dementia risk at older ages. In those with CVD, the dementia risk was lower if lifestyle factors are at recommended levels following CVD diagnosis. HIGHLIGHTS: CVD in midlife but not in late life is associated with a higher risk of dementia. Dementia risk in CVD patients is lower if their lifestyle factors are at recommended levels. These findings provide evidence to promote CVD prevention in midlife or earlier. Study findings also show the importance of a healthy lifestyle in those with CVD.

Long-term lifestyle change and risk of mortality and Type 2 diabetes in patients with cardiovascular disease.

AIMS: To quantify the relationship between self-reported, long-term lifestyle changes (smoking, waist circumference, physical activity, and alcohol consumption) and clinical outcomes in patients with established cardiovascular disease (CVD). METHODS AND RESULTS: Data were used from 2011 participants (78% male, age 57 ± 9 years) from the Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease cohort who returned for a re-assessment visit (SMART2) after ∼10 years. Self-reported lifestyle change was classified as persistently healthy, improved, worsened, or persistently unhealthy. Cox proportional hazard models were used to quantify the relationship between lifestyle changes and the risk of (cardiovascular) mortality and incident Type 2 diabetes (T2D). Fifty-seven per cent of participants was persistently healthy, 17% improved their lifestyle, 8% worsened, and 17% was persistently unhealthy. During a median follow-up time of 6.1 (inter-quartile range 3.6-9.6) years after the SMART2 visit, 285 deaths occurred, and 99 new T2D diagnoses were made. Compared with a persistently unhealthy lifestyle, individuals who maintained a healthy lifestyle had a lower risk of all-cause mortality [hazard ratio (HR) 0.48, 95% confidence interval (CI) 0.36-0.63], cardiovascular mortality (HR 0.57, 95% CI 0.38-0.87), and incident T2D (HR 0.46, 95% CI 0.28-0.73). Similarly, those who improved their lifestyle had a lower risk of all-cause mortality (HR 0.52, 95% CI 0.37-0.74), cardiovascular mortality (HR 0.46, 95% CI 0.26-0.81), and incident T2D (HR 0.50, 95% CI 0.27-0.92). CONCLUSION: These findings suggest that maintaining or adopting a healthy lifestyle can significantly lower mortality and incident T2D risk in CVD patients. This study emphasizes the importance of ongoing lifestyle optimization in CVD patients, highlighting the potential for positive change regardless of previous lifestyle habits.

In this study, we investigated whether lifestyle changes were related to improved health outcomes in individuals with cardiovascular disease (CVD). We assessed self-reported lifestyle behaviours (smoking, waist circumference, alcohol consumption, and physical activity), at inclusion in the cohort and again ∼10 years later. The results emphasize the importance of making healthy lifestyle choices, even for individuals already diagnosed with CVD, and suggest that it is never too late to improve one's lifestyle.

Is the number of ideal cardiovascular health metrics in midlife associated with lower risk of cancer? Evidence from 3 European prospective cohorts.

BACKGROUND: Primordial prevention may be a relevant strategy for the prevention of cancer. Given the commonality of risk factors and mechanisms between cancer and cardiovascular disease, we examined the associations between the number of ideal cardiovascular health metrics in midlife and incident cancer. METHODS: In 3 European cohorts (NutriNet-Santé and GAZEL, France; Whitehall II, United Kingdom), the number of ideal cardiovascular health metrics was determined at baseline (range 0-7). Follow-up for cancer events was until October 2020 (NutriNet-Santé), March 2017 (Whitehall II) and December 2015 (GAZEL). Cox regression was conducted in each cohort, and results were thereafter pooled using a random-effects model. RESULTS: Data were available on 39 718 participants. A total of 16 237 were from NutriNet-Santé (mean age 51.3 yr; 28% men), 9418 were from Whitehall II (mean age 44.8 yr; 68% men) and 14 063 were from GAZEL (mean age 45.2 yr; 75% men). The median follow-up was 8.1 years in NutriNet-Santé, 29.6 years in Whitehall II and 24.8 years in GAZEL, and yielded a total of 4889 cancer events. A greater number of ideal cardiovascular health metrics was associated with a lower overall cancer risk in each cohort, with an aggregate hazard ratio (HR) per 1 increment in number of ideal metrics of 0.91 (95% confidence interval [CI] 0.88-0.93). This association remained after removal of the smoking metric (aggregate HR per unit increment in number of ideal metrics: 0.94, 95% CI 0.90-0.97), and site-specific analysis demonstrated a significant association with lung cancer. INTERPRETATION: A greater number of ideal cardiovascular health metrics in midlife was associated with lower cancer risk, notably lung cancer. Primordial prevention of cardiovascular risk factors in midlife may be a complementary strategy to prevent the onset of cancer.

Association of type 2 diabetes according to the number of risk factors within the recommended range with incidence of major depression and clinically relevant depressive symptoms: a prospective analysis.

BACKGROUND: Type 2 diabetes is associated with an increased risk of depression, but the extent to which risk factor modification can mitigate this risk is unclear. We aimed to examine the association between the incidence of major depression and clinically relevant depressive symptoms among individuals with type 2 diabetes, according to the number of risk factors within the recommended target range, compared with individuals without diabetes. METHODS: We did a prospective analysis of population-based data from the UK Biobank and the Maastricht Study. Individuals with type 2 diabetes were categorised according to the number of risk factors within the recommended target range (non-smoking, guideline-recommended levels of glycated haemoglobin (HbA1c), blood pressure, BMI, albuminuria, physical activity, and diet). The primary outcome, based on data from the UK Biobank, was the incidence of major depression ascertained from hospital records; the secondary outcome, based on data from the UK Biobank and the Maastricht Study, was clinically relevant depressive symptoms based on a score of 10 or higher on the Patient Health Questionnaire (PHQ-9). FINDINGS: The study population of the UK Biobank comprised 77 786 individuals (9047 with type 2 diabetes and 68 739 without diabetes; median age 59 years [IQR 51-64]; 34 136 [43·9%] women and 43 650 [56·1%] men). A median of 12·7 years (IQR 11·8-13·4) after recruitment (between March 13, 2006, and Oct 1, 2010), 493 (5·5%) of 9047 individuals with type 2 diabetes and 2574 (3·7%) of 68 739 individuals without diabetes developed major depression. Compared with individuals without diabetes, those with type 2 diabetes had a higher risk of major depression (hazard ratio [HR] 1·61 [95% CI 1·49-1·77]). Among individuals with type 2 diabetes, the excess risk of depression decreased stepwise with an increasing number of risk factors within the recommended target range (HR 2·04 [95% CI 1·65-2·52] for up to two risk factors within the recommended target range; 1·95 [1·65-2·30] for three risk factors within the recommended target range; 1·38 [1·16-1·65] for four risk factors within the recommended target range; and 1·34 [1·12-1·62] for five to seven risk factors within the recommended target range). In the UK Biobank dataset, a median of 7·5 years (IQR 6·8-8·2) after the baseline examination, 147 (7·5%) of 1953 individuals with type 2 diabetes and 954 (4·5%) of 21 413 individuals without diabetes had developed clinically relevant depressive symptoms. The study population of the Maastricht Study comprised 4530 individuals (1158 with type 2 diabetes and 3372 without diabetes; median age 60 years [IQR 53-66]; 2244 [49·5%] women and 2286 [50·1%] men). A median of 5·1 years (IQR 4·1-6·1) after recruitment (between Sept 1, 2010, and Dec 7, 2017), 170 (14·7%) of 1158 individuals with type 2 diabetes and 227 (6·7%) of 3372 individuals without diabetes developed clinically relevant depressive symptoms. Similarly, in both the UK Biobank dataset and the Maastricht Study cohort, among individuals with type 2 diabetes, the excess risk of clinically relevant depressive symptoms decreased stepwise with an increasing number of risk factors within the recommended target range. INTERPRETATION: Among individuals with type 2 diabetes, the excess risk of major depression and clinically relevant depressive symptoms decreased stepwise with an increasing number of risk factors within the recommended target range. This study provides further evidence to promote risk factor modification strategies in individuals with type 2 diabetes and to encourage the adoption of a healthy lifestyle. FUNDING: ZonMW, Hartstichting, and Diabetes Fonds.

Association of Cardiovascular Health With Risk of Clinically Relevant Depressive Symptoms.

Importance: Cardiovascular health may be used for prevention of depressive symptoms. However, data on the association of cardiovascular health across midlife with depressive symptoms are lacking. Objective: To evaluate whether better baseline cardiovascular health and improvement of cardiovascular health over time are associated with a lower risk of both incident depressive symptoms and unfavorable trajectories of depressive symptoms. Design, Setting, and Participants: Participants without depressive symptoms were included from a prospective community-based cohort in France (GAZEL cohort). Cardiovascular health examinations occurred in 1990 and 1997 and assessment of depressive symptoms in 1997 and every 3 years thereafter until 2015. Data were analyzed from January to October 2022. Exposures: Number of cardiovascular health metrics (smoking, body mass index, physical activity, diet, blood pressure, glucose, and cholesterol) at an intermediate or ideal level in 1997 (range, 0-7) and 7-year change in cardiovascular health between 1990 and 1997. Main Outcomes and Measures: Primary outcome was incident depressive symptoms (20-item Center for Epidemiologic Studies-Depression Scale [CES-D] score of 17 or greater in men or 23 or greater in women); secondary outcome was trajectories of depressive symptoms scores. Trajectories included consistently low scores, moderately elevated scores, low starting then increasing scores, moderately high starting, increasing, then remitting scores, and moderately high starting then increasing scores. Results: Of 6980 included patients, 1671 (23.9%) were women, and the mean (SD) age was 53.3 (3.5) years. During a follow-up spanning 19 years after 1997, 1858 individuals (26.5%) had incident depressive symptoms. Higher baseline cardiovascular health in 1997 and improvement in cardiovascular health over 7 years were each associated with lower risk of depressive symptoms (odds ratio [OR] per additional metric at intermediate or ideal level at baseline, 0.87; 95% CI, 0.84-0.91; OR per 1 higher metric at intermediate or ideal level over 7 years, 0.91; 95% CI, 0.86-0.96). Also, better cardiovascular health was associated with lower risk of unfavorable depressive symptoms trajectories. Compared with the consistently low score trajectory, the lowest risks were observed for the low starting then increasing score trajectory (OR per additional metric at intermediate or ideal level at baseline, 0.70; 95% CI, 0.64-0.76; OR per 1 higher metric at intermediate or ideal level over 7 years, 0.73; 95% CI, 0.68-0.79) and the moderately high starting then increasing score trajectory (OR per additional metric at intermediate or ideal level at baseline, 0.71; 95% CI, 0.64-0.79; OR per 1 higher metric at intermediate or ideal level over 7 years, 0.71; 95% CI, 0.64-0.77). Conclusions and Relevance: In this prospective community-based cohort study of adults, higher cardiovascular health was associated with a lower risk of depressive symptoms over time. Elucidating which set of cardiovascular factors may affect depression risk could be important for prevention.

Microvascular Dysfunction Is Associated With Worse Cognitive Performance: The Maastricht Study.

Microvascular dysfunction may be associated with worse cognitive performance. Most previous studies did not adjust for important confounders, evaluated only individual measures of microvascular dysfunction, and showed inconsistent results. We evaluated the association between a comprehensive set of measures of microvascular dysfunction and cognitive performance in the population-based Maastricht Study. We used cross-sectional data including 3011 participants (age 59.5±8.2; 48.9% women; 26.5% type 2 diabetes mellitus [oversampled by design]). Measures of microvascular dysfunction included magnetic resonance imaging features of cerebral small vessel disease, plasma biomarkers of microvascular dysfunction, albuminuria, flicker light-induced retinal arteriolar and venular dilation response and heat-induced skin hyperemia. These measures were summarized into a microvascular dysfunction composite score. Cognitive domains assessed were memory, processing speed, and executive function. A cognitive function score was calculated as the sum of the scores on these 3 cognitive domains. The microvascular dysfunction score was associated with a worse cognitive function score (standardized ß, -0.087 [95% CI, -0.127 to -0.047]), independent of age, education level, sex, type 2 diabetes mellitus, smoking, alcohol use, hypertension, total/HDL (high-density lipoprotein) cholesterol ratio, triglycerides, lipid-modifying medication, prior cardiovascular disease, depression and plasma biomarkers of low-grade inflammation. The fully adjusted ß-coefficient of the association between the microvascular dysfunction score and the cognitive function score was equivalent to 2 (range, 1-3) years of aging for each SD higher microvascular dysfunction score. The microvascular dysfunction score was associated with worse memory and processing speed but not with worse executive function. The present study shows that microvascular dysfunction is associated with worse cognitive performance.

Co-administration of cyclosporine and ticagrelor may lead to a higher exposure to cyclosporine: a case report of a 49-year-old man.

ADVERSE EVENT: A drug interaction leading to higher exposure to cyclosporine. DRUGS IMPLICATED: Cyclosporine and ticagrelor. THE PATIENT: A 49-year-old man with a stable renal graft, managed with cyclosporine with stable trough blood concentrations for several years, was treated with ticagrelor for unstable angina pectoris. EVIDENCE THAT LINKS THE DRUG TO THE EVENT: The timeline was consistent with the appearance of an interaction, the interaction was confirmed by an increase in trough concentration of cyclosporine, and there were no alternative causes that by themselves could have caused the increase in cyclosporine exposure. MANAGEMENT: Cessation of ticagrelor. MECHANISM: Inhibition of CYP3A4 and P-glycoprotein by ticagrelor. IMPLICATIONS FOR THERAPY: Clinicians should be aware of this potential interaction as ticagrelor is frequently prescribed in individuals using cyclosporine. Close monitoring of cyclosporine serum concentrations is warranted to avoid overdosing of cyclosporine. A pharmacokinetic study is needed to further examine the probable interaction between cyclosporine and ticagrelor.

The systolic-diastolic difference in carotid stiffness is increased in type 2 diabetes: The Maastricht Study.

OBJECTIVE: In type 2 diabetes (T2D), increased arterial stiffening results from accelerated arterial wall matrix remodeling. The associated structural alterations modify the pressure dependency of arterial stiffness, which can be quantified by the systolic-diastolic difference in carotid pulse wave velocity (δPWV). We evaluated the association between T2D and δPWV as marker for matrix remodeling and whether δPWV may contain additional information beyond carotid stiffness (cPWV). METHODS: In 746 individuals from The Maastricht Study, 415 with normal glucose metabolism; 126 with prediabetes; and 205 with T2D, carotid pulse wave velocity (cPWV) and δPWV were determined by ultrasonography and tonometry. Multiple linear regression analyses were used to investigate associations of glucose metabolism status (with normal glucose metabolism as reference) with cPWV and δPWV, adjusting for age, sex, mean arterial pressure, prior cardiovascular disease, estimated glomerular filtration rate and smoking, and δPWV or cPWV as appropriate. RESULTS: After adjustment for age, sex, mean arterial pressure, prior cardiovascular disease, estimated glomerular filtration rate and smoking, T2D was associated with greater cPWV [ß (95% confidence interval) 0.376 (0.119; 0.632)] and δPWV [0.301 (0.013; 0.589)]. After additional adjustment for δPWV or cPWV, associations of T2D with cPWV and δPWV were attenuated [0.294 (0.048; 0.539) and 0.173 (-0.103; 0.449), respectively]. Prediabetes was not associated with either cPWV or δPWV. CONCLUSION: The systolic-diastolic difference in carotid stiffness is increased in T2D, but not prediabetes. Importantly, the association was not abolished by carotid stiffness, which suggests that systolic-diastolic difference in carotid stiffness carries additional information regarding arterial matrix remodeling.

Association between serum uric acid, aortic, carotid and femoral stiffness among adults aged 40-75 years without and with type 2 diabetes mellitus: The Maastricht Study.

OBJECTIVE: Arterial stiffness may be a mechanism to explain the association between uric acid and cardiovascular disease. We aimed to analyse associations between serum uric acid and regional and local arterial stiffness, and assess potential differences related to sex and glucose metabolism status. METHODS: A cross-sectional study was performed in 614 adults [52.6% men; mean age 58.7 ±â€Š8.5 years; 23.2% type 2 diabetes mellitus (by design)] from The Maastricht Study. Arterial stiffness was assessed by carotid-femoral pulse wave velocity (cfPWV), distensibility, and compliance coefficient of the carotid and femoral artery, and carotid artery Young's elastic modulus. RESULTS: Higher uric acid (per SD of 74 µmol/l) was associated with greater stiffness indicated by a significantly higher cfPWV [ß = 0.216 (95% confidence interval 0.061, 0.372); P = 0.006] and lower carotid distensibility coefficient [ß = -0.633 (95% confidence interval -1.099, -0.166); P = 0.008] after adjustment for sex, age, and glucose metabolism status. Associations lost significance after adjusting for mean arterial pressure, BMI, waist, smoking status, heart rate, total : high-density lipoprotein cholesterol ratio, triglycerides, estimated glomerular filtration rate, use of lipid-lowering, antihypertensive, and diabetes medication, and use of secondary uricosurics. No associations were found between uric acid and carotid compliance coefficient, carotid Young's elastic modulus, or stiffness of the femoral artery. A significant interaction (P < 0.10) with glucose metabolism status was found for cfPWV. However, none of the stratified associations were significant. There was no interaction with sex. CONCLUSION: Uric acid was not significantly associated with stiffness of the aorta, or the carotid or femoral artery among adults aged 40-75 years without and with type 2 diabetes mellitus.