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In this investigation ECG parameters of 117 relatives of 40 index patients suffering from dilated cardiomyopathy (DCM) were examined. Subjects of this analysis were QT and QRS intervals as well as their dispersion with the aim to identify markers of inapparent disease in the relatives. QT and QRS intervals were measured in as many leads as possible from a standard 12 lead ECG and correlated with echocardiographic results. Furthermore the subjects were classified according to the Mestroni criteria into the three groups of subjects labelled as ''ill'', ''borderline'' and ''without criteria''. Besides, the groups of ''ill'' and ''borderline'' were investigated as the metagroup of ''with criteria'' as was the group ''healthy'', consisting of the borderline subjects and those without disease criteria. A statistically significant mildly positive correlation between the echocardiographically diagnosed enddiastolic left ventricular dimension and the duration of QT- and QRS-intervals could be observed. There was a negative correlation between fractional shortening and QRS dispersion. The duration of QT- and QRS-intervals was significantly different between the groups, except of no significant differences between the groups ''without criteria'' and ''borderline''. When the durations of QT and QRS were longer, the clinical status of the group was more severe. Neither QT-dispersion nor frequency-adjusted QT-dispersion was able to show significant differences between the three groups. QRS- and frequency-adjusted QRS-dispersion exhibited significant differences only between the ill subjects and the other groups. Thus one can conclude that there are ECG parameters that are affected by DCM, but QT- and QRS-dispersion show no advantage in clinical practice compared to simple intervals. The different groups overlap to a large degree. This implies that only very extreme values are meaningful and helpful in clinical practice. In future studies one should establish threshold levels for these parameters with larger samples or further differentiate the groups, e.g. for gender, which was not possible in this study because the sample size was too small.