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

Risk of Parkinson Disease and Secondary Parkinsonism in Myocardial Infarction Survivors

Background In addition to primary neurodegenerative processes, vascular disorders, such as stroke, can lead to parkinsonism. However, some cardiovascular risk factors, such as smoking and elevated cholesterol levels, are associated with reduced risk of Parkinson disease. We examined the risk of Parkinson disease and secondary parkinsonism in 1‐year survivors of myocardial infarction (MI). Methods and Results We conducted a nationwide population‐based matched cohort study using Danish medical registries from 1995 to 2016. We identified all patients with a first‐time MI diagnosis and sampled a sex‐, age‐, and calendar year–matched general population comparison cohort without MI. Cox regression analysis was used to compute adjusted hazard ratios (aHRs) for Parkinson disease and secondary parkinsonism, controlled for matching factors and adjusted for relevant comorbidities and socioeconomic factors. We identified 181 994 patients with MI and 909 970 matched comparison cohort members (median age, 71 years; 62% men). After 21 years of follow‐up, the cumulative incidence was 0.9% for Parkinson disease and 0.1% for secondary parkinsonism in the MI cohort. Compared with the general population cohort, MI was associated with a decreased risk of Parkinson disease (aHR, 0.80; 95% CI, 0.73–0.87) and secondary parkinsonism (aHR, 0.72; 95% CI, 0.54–0.94). Conclusions MI was associated with a 20% decreased risk of Parkinson disease and 28% decreased risk of secondary parkinsonism. Reduced risk may reflect an inverse relationship between cardiovascular risk factors and Parkinson disease

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