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Evaluation of a sensor algorithm for motor state rating in Parkinson's disease.
Johansson, Dongni; Thomas, Ilias; Ericsson, Anders; Johansson, Anders; Medvedev, Alexander; Memedi, Mevludin; Nyholm, Dag; Ohlsson, Fredrik; Senek, Marina; Spira, Jack; Westin, Jerker; Bergquist, Filip.
Afiliação
  • Johansson D; Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. Electronic address: dongni.johansson@gu.se.
  • Thomas I; Department of Micro-data Analysis, Dalarna University, Falun, Sweden.
  • Ericsson A; RISE Acreo, Gothenburg, Sweden.
  • Johansson A; Department of Clinical Neuroscience, Neurology, Karolinska Institutet, Stockholm, Sweden.
  • Medvedev A; Department of Information Technology, Uppsala University, Uppsala, Sweden.
  • Memedi M; Informatics, School of Business, Örebro University, Örebro, Sweden.
  • Nyholm D; Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
  • Ohlsson F; RISE Acreo, Gothenburg, Sweden.
  • Senek M; Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
  • Spira J; Sensidose AB, Sollentuna, Sweden.
  • Westin J; Department of Micro-data Analysis, Dalarna University, Falun, Sweden.
  • Bergquist F; Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Pharmacology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Parkinsonism Relat Disord ; 64: 112-117, 2019 07.
Article em En | MEDLINE | ID: mdl-30935826
INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkinson's disease (PD) and its usefulness for constructing individual dose-response models. METHODS: Twenty-five patients with PD performed a series of tasks throughout a levodopa challenge while wearing sensors. TRIS was used to determine motor changes in pronation-supination tests following a single levodopa dose, and was compared to clinical ratings including the Treatment Response Scale (TRS) and six sub-items of the UPDRS part III. RESULTS: As expected, correlations between TRIS and clinical ratings were lower in the new population than in the initial study. TRIS was still significantly correlated to TRS (rs = 0.23, P < 0.001) with a root mean square error (RMSE) of 1.33. For the patients (n = 17) with a good levodopa response and clear motor fluctuations, a stronger correlation was found (rs = 0.38, RMSE = 1.29, P < 0.001). The mean TRIS increased significantly when patients went from the practically defined off to their best on state (P = 0.024). Individual dose-response models could be fitted for more participants when TRIS was used for modelling than when TRS ratings were used. CONCLUSION: The objective sensor index shows promise for constructing individual dose-response models, but further evaluations and retraining of the TRIS algorithm are desirable to improve its performance and to ensure its clinical effectiveness.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Parkinson / Levodopa / Máquina de Vetores de Suporte / Dispositivos Eletrônicos Vestíveis / Atividade Motora / Antiparkinsonianos Tipo de estudo: Prognostic_studies Limite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Parkinson / Levodopa / Máquina de Vetores de Suporte / Dispositivos Eletrônicos Vestíveis / Atividade Motora / Antiparkinsonianos Tipo de estudo: Prognostic_studies Limite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2019 Tipo de documento: Article