The validation of cardiovascular risk scores for patients with type 2 diabetes mellitus.

OBJECTIVE: Various cardiovascular prediction models have been developed for patients with type 2 diabetes. Their predictive performance in new patients is mostly not investigated. This study aims to quantify the predictive performance of all cardiovascular prediction models developed specifically for diabetes patients. DESIGN AND METHODS: Follow-up data of 453, 1174 and 584 type 2 diabetes patients without pre-existing cardiovascular disease (CVD) in the EPIC-NL, EPIC-Potsdam and Secondary Manifestations of ARTerial disease cohorts, respectively, were used to validate 10 prediction models to estimate risk of CVD or coronary heart disease (CHD). Discrimination was assessed by the c-statistic for time-to-event data. Calibration was assessed by calibration plots, the Hosmer-Lemeshow goodness-of-fit statistic and expected to observed ratios. RESULTS: There was a large variation in performance of CVD and CHD scores between different cohorts. Discrimination was moderate for all 10 prediction models, with c-statistics ranging from 0.54 (95% CI 0.46 to 0.63) to 0.76 (95% CI 0.67 to 0.84). Calibration of the original models was poor. After simple recalibration to the disease incidence of the target populations, predicted and observed risks were close. Expected to observed ratios of the recalibrated models ranged from 1.06 (95% CI 0.81 to 1.40) to 1.55 (95% CI 0.95 to 2.54), mainly driven by an overestimation of risk in high-risk patients. CONCLUSIONS: All 10 evaluated models had a comparable and moderate discriminative ability. The recalibrated, but not the original, prediction models provided accurate risk estimates. These models can assist clinicians in identifying type 2 diabetes patients who are at low or high risk of developing CVD.

The separate and combined effects of adiposity and cardiometabolic dysfunction on the risk of recurrent cardiovascular events and mortality in patients with manifest vascular disease.

OBJECTIVES: A remarkable variation exists in the cardiometabolic consequences of obesity. We evaluated the separate and combined effects of adiposity and cardiometabolic dysfunction on the occurrence of cardiovascular events and mortality in patients with vascular disease. METHODS: We prospectively followed 5231 patients with a history of clinical cardiovascular disease without diabetes from the Second Manifestations of ARTerial disease (SMART) study. Patients were classified according to body mass index and cardiometabolic function. The presence of cardiometabolic dysfunction was defined as ≥3 of the modified National Cholesterol Education Program (NCEP) metabolic syndrome criteria (waist circumference replaced by elevated C-reactive protein). Cox proportional-hazards analysis was used to estimate HRs for cardiovascular events and mortality. RESULTS: The prevalence of cardiometabolic dysfunction was 40% in normal weight, 58% in overweight and 75% in obese patients. During a median follow-up of 6.1 years, 769 patients died and 705 patients experienced a major cardiovascular event. In the absence of cardiometabolic dysfunction, overweight (HR 1.18, 95% CI 0.90 to 1.55) and obese patients (HR 0.93, 95% CI 0.53 to 1.64) were not at increased risk of recurrent major cardiovascular events compared with normal weight patients without cardiometabolic dysfunction. An increased cardiovascular risk was observed in patients with cardiometabolic dysfunction and normal weight (HR 1.58, 95% CI 1.23 to 2.04), overweight (HR 1.35, 95% CI 1.07 to 1.70) and obesity (HR 1.50, 95% CI 1.12 to 2.00) compared with normal weight patients without cardiometabolic dysfunction. A similar pattern was observed for vascular and all-cause mortality. CONCLUSIONS: In patients with vascular disease, the cardiometabolic consequences of adiposity rather than adiposity per se increase the risk of recurrent cardiovascular events and mortality.

Participation of end users in the design of assistive technology for people with mild to severe cognitive problems; the European Rosetta project.

BACKGROUND: In the European Rosetta project three separate, previously developed, ICT systems were improved and integrated to create one modular system that helps community-dwelling people with mild cognitive impairment and dementia in different stages of the disease. The system aims to support them in daily functioning, monitor (deviations from) patterns in daily behaviour and to automatically detect emergency situations. The study aimed to inventory the end users' needs and wishes regarding the development and design of the new integrated Rosetta system, and to describe the to be developed Rosetta system. METHODS: Qualitative user-participatory design with in total 50 persons: 14 people with dementia, 13 informal carers, 6 professional carers, 9 dementia experts, 7 care partners within the project, and 1 volunteer. In the Netherlands user focus group sessions were performed and in Germany individual interviews. Dementia experts were consulted by means of a questionnaire, an expert meeting session, and interviews. RESULTS: Persons with dementia and informal carers appreciated the following functionalities most: help in cases of emergencies, navigation support and the calendar function. Dementia experts rated various behaviours relevant to monitor in order to detect timely changes in functioning, e.g. eating, drinking, going to the toilet, taking medicine adequately, performance of activities and sleep patterns. No ethical issues regarding the use of sensors and cameras were mentioned. CONCLUSION: The user participatory design resulted in valuable input from persons with dementia, informal carers and professional carers/dementia experts, based on which a first prototype Rosetta system was built.