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Details

Autor(en) / Beteiligte
Titel
Prodromal features for Parkinson's disease - baseline data from the TREND study
Ist Teil von
  • European journal of neurology, 2014-05, Vol.21 (5), p.766-772
Ort / Verlag
England: Blackwell Publishing Ltd
Erscheinungsjahr
2014
Quelle
Wiley Online Library Journals Frontfile Complete
Beschreibungen/Notizen
  • Background and purpose A number of non‐motor features are known to precede motor manifestations of Parkinson's disease (PD). They are supposed to already represent the prodromal neurodegenerative state in those who later develop PD and are thus called prodromal markers. In this study, three prodromal markers, depression, rapid eye movement behaviour disorder (RBD) and hyposmia, were selected and were related to other prodromal features in elderly individuals without PD. Methods From the Tübinger Evaluation of Risk Factors for Early Detection of Neurodegeneration (TREND) study, 698 healthy individuals aged 50–80 years reporting one or more of the selected prodromal markers (SPMs), but without neurodegenerative disorders, were evaluated and classified according to the status of prodromal markers. Other prodromal PD‐related features were assessed with a 23‐item questionnaire and compared between participants with and without the three SPMs. Results Individuals with the SPMs for PD endorsed more of the additional possible prodromal features of PD than those without; of 23 possible prodromal features, the median number identified amongst participants with no SPMs was two, compared with four with one marker, five with two and seven with three (P < 0.001). Regarding individual SPMs, participants with depression and RBD endorsed five of 23 markers, compared with three for those with hyposmia (P = 0.001). There was no significant increase in the number of prodromal features amongst those with two SPMs compared with those with only one marker. Conclusions Individuals with the SPMs for PD report a higher prevalence of other prodromal PD symptoms. This may indicate that these markers can identify individuals at risk for PD.

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