Chapter 2 provides an overview of the currently available evidence regarding the prolongation of QTc interval on the ECG and the risk of CVD in the general and T2D population. The general population studies meta-analysis showed a significant association between prolongation of the QTc interval and overall CVD (fatal and non-fatal), CHD (women and men separately), stroke, SCD and AF. No significant association was found for CVD in the T2D population. In Chapter 3, we investigated whether the prolongation of QTc interval is associated with the risk of CVD in the general population. In addition, we investigated whether glucose tolerance modified this potential association. We found that prolonging the QTc interval is significantly associated with a higher risk of overall CVD morbidity and mortality, stroke and heart failure. However, glucose tolerance status did not modify these associations. In Chapter 4 we investigated the association between the age at menopause and the risk of ischemic and hemorrhagic stroke. We observed that earlier menopause was associated with an increased risk of total stroke and ischemic stroke, but not with hemorrhagic stroke. In addition, the association with menopausal age was stronger for natural menopause than surgical menopause. In Chapter 5 we validated a recently developed North-American prediction model for SCD in the general population in two European cohorts, and we investigated whether it was possible to improve this prediction model by adding data on income and the use of anti-depressant medication. Our analyses showed that the previously developed prediction model is equally good at predicting the risk of SCD in a general North-West European population. However, we found a low positive predictive value and a low specificity, meaning this prediction model cannot be used in general practice. Furthermore, adding the extra predictors did not improve the model. In Chapter 6 we validated the prediction model for SCD, that was developed for the general population, in a European T2D population. Furthermore, we also investigated whether it was possible to improve this prediction model by adding the year change in glucose and blood pressure after T2D diagnosis and information about ECG abnormalities. Our analyses showed that the previously developed North-American prediction model performed somewhat worse in the T2D population. Moreover, we found a low positive predictive value and specificity. Lastly, adding additional predictors did not improve the model.
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