Non-motor symptoms in Parkinson's disease: An explorative network study

Gwenda Engels, L. Douw, Yvonne Kerst, H. Weinstein, Erik Scherder, Annemarie Vlaar

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

Research on the association between non-motor symptoms (NMS) of Parkinson's disease (PD) and patients' quality of life (QoL) has given insight into the burden of NMS. Most studies investigate NMS by assessing the contribution of individual symptoms to QoL. However, symptoms could also have an interactive relationship, which might not be fully taken into account when only studying these individual contributions. Recently, a network approach has been developed that treats symptoms as nodes and associations between symptoms as edges in a network, providing the opportunity to investigate the dimensional spectrum of NMS. In the current cross-sectional study, we investigated NMS with both approaches: first, we assessed individual contributions of NMS to QoL. Second, we aimed to assess NMS using a network approach. Seventy PD patients completed questionnaires on NMS and QoL. Our primary analysis shows that the domains Mood and Pain are significant contributors to QoL. Our secondary network analysis suggests that Mood and Sleep play central roles in the NMS-network, and that Mood and Cognition are strongly related. Because of power issues, the generalizability of our explorative results is limited. However, complementary information from the network analysis does suggest that focusing on sleep problems might help both mood and pain symptoms, which negatively affect QoL. Investigating symptoms not only as individual and independent entities but rather as part of a connected network could show how treating one symptom affects other symptoms.
Original languageEnglish
Pages (from-to)237-240
Number of pages4
JournalParkinsonism and Related Disorders
Volume66
DOIs
Publication statusPublished - 1 Sept 2019

Keywords

  • Non-motor symptoms
  • Parkinson's disease
  • Quality of life
  • Symptom network

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