Quantitative assessment of non-motor fluctuations in Parkinson’s disease using the Non-Motor Symptoms Scale (NMSS)

Storch, Alexander; Schneider, Christine; Klingelhöfer, Lisa; Odin, Per; Fuchs, Gerd; Jost, Wolfgang H.; Martinez‐Martín, Pablo; Koch, Rainer; Reichmann, Heinz; Chaudhuri, K. Ray; Ebersbach, Georg

doi:10.1007/s00702-015-1437-x

Cited by 57 publications

(43 citation statements)

References 37 publications

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“…Changes in NMS are not always time‐locked to those of motor manifestations, and fluctuations in NMS do not always correlate with motor function . This finding suggests the possible existence of different pathophysiological mechanisms in the genesis of MF and NMF.…”

Section: Pathophysiology Of Nmfmentioning

confidence: 93%

The hidden sister of motor fluctuations in Parkinson's disease: A review on nonmotor fluctuations

et al. 2016

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Only a few years after the introduction of levodopa, the first descriptions of motor fluctuations and dyskinesia related to dopaminergic therapy appeared. In PD, attention turned to their management, that had dampened the euphoria of the “levodopa miracle.” It soon became clear that neuropsychiatric, autonomic, and sensory features also tend to develop fluctuations after chronic exposure to l‐dopa. The diversity of fluctuating nonmotor symptoms, their largely subjective nature, coupled with a frequent lack of insight led to difficulties in identification and quantification. This may explain why, despite the high impact of nonmotor symptoms on patient autonomy and quality of life, evaluation of nonmotor fluctuations is not part of clinical routine. In view of the lack of specific validated assessment tools, detailed anamnesis should ideally be coupled with an evaluation in both ON and OFF drug conditions. The mechanisms of nonmotor fluctuations are not well understood. It is thought that they share dopaminergic presynaptic pharmacokinetic and postsynaptic pharmacodynamic mechanisms with the classical motor complications, but involve different neural pathways. Although symptoms fluctuate with dopaminergic treatment, serotonine and norepinephrine denervation, as well as interactions between neurotransmitter systems, probably contribute to their diversity. The lack of validated tools for assessment of these phenomena explains the almost complete absence of treatment studies. Management, largely resulting from expert opinion, includes psychiatric follow‐up, nondopaminergic drugs, and advanced dopaminergic treatment, including drug delivery pumps and DBS. This review aims to provide a starting point for the understanding, diagnosis, and management of nonmotor fluctuations. © 2016 International Parkinson and Movement Disorder Society

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Section: Pathophysiology Of Nmfmentioning

confidence: 93%

The hidden sister of motor fluctuations in Parkinson's disease: A review on nonmotor fluctuations

et al. 2016

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“…Two diaries (Parkinson Disease Home Diary and CAPSIT‐PD Diary) have been designated as “recommended” by the MDS Task Force on Rating Scales. Nonetheless, these 2 diaries have the caveat that limited data exist regarding their validity, compliance, and completion, and their assessment is implicitly linked to the presence of motor fluctuations . A systematic literature search found a total of 12 published PD diaries, for which a narrative review (Supplementary material 1) and quality criteria (Supplementary material 2) are available online.…”

Section: Current Gaps In Pd Diaries and Strategies To Address Them Inmentioning

confidence: 99%

The Parkinson's disease e‐diary: Developing a clinical and research tool for the digital age

et al. 2019

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“…001 [Wilcoxon test]; UPDRSIII motor score in On: 13.5±5.5 [5–28] and Off: 26.9±8.8 [10–47]; P <0.001 [paired t -test]; levodopa equivalent dose per day [25]: 1,106±358 mg [410–1,690 mg]; see S1 Table for further information). All patients displayed at least two types of motor complications, median number of motor complication was 4 (10 th /90 th percentile: 1/6).…”

Section: Resultsmentioning

confidence: 99%

“…However, persistent depression measured by the BDI was not a relevant confounder for the correlations of diary and PKG data. Whether or not mood or other non-motor symptom fluctuations that are known to appear in conjunction with motor oscillations fluctuations [27, 28] influence the diary ratings needs to be addressed in future studies. Another limitation of the present study is that ratings derived from PKG and patient diaries were not compared to clinical assessments performed by trained clinicians.…”

Section: Discussionmentioning

confidence: 99%

Correlation of Quantitative Motor State Assessment Using a Kinetograph and Patient Diaries in Advanced PD: Data from an Observational Study

et al. 2016

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IntroductionEffective management and development of new treatment strategies for response fluctuations in advanced Parkinson’s disease (PD) largely depends on clinical rating instruments such as the PD home diary. The Parkinson’s kinetigraph (PKG) measures movement accelerations and analyzes the spectral power of the low frequencies of the accelerometer data. New algorithms convert each hour of continuous PKG data into one of the three motor categories used in the PD home diary, namely motor Off state and On state with and without dyskinesia.ObjectiveTo compare quantitative motor state assessment in fluctuating PD patients using the PKG with motor state ratings from PD home diaries.MethodsObservational cohort study on 24 in-patients with documented motor fluctuations who completed diaries by rating motor Off, On without dyskinesia, On with dyskinesia, and asleep for every hour for 5 consecutive days. Simultaneously collected PKG data (recorded between 6 am and 10 pm) were analyzed and calibrated to the patient’s individual thresholds for Off and dyskinetic state by novel algorithms classifying the continuous accelerometer data into these motor states for every hour between 6 am and 10 pm.ResultsFrom a total of 2,040 hours, 1,752 hours (87.4%) were available for analyses from calibrated PKG data (7.5% sleeping time and 5.1% unclassified motor state time were excluded from analyses). Distributions of total motor state hours per day measured by PKG showed moderate-to-strong correlation to those assessed by diaries for the different motor states (Pearson’s correlations coefficients: 0.404–0.658), but inter-rating method agreements on the single-hour-level were only low-to-moderate (Cohen’s κ: 0.215–0.324).ConclusionThe PKG has been shown to capture motor fluctuations in patients with advanced PD. The limited correlation of hour-to-hour diary and PKG recordings should be addressed in further studies.

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Quantitative assessment of non-motor fluctuations in Parkinson’s disease using the Non-Motor Symptoms Scale (NMSS)

Cited by 57 publications

References 37 publications

The hidden sister of motor fluctuations in Parkinson's disease: A review on nonmotor fluctuations

The hidden sister of motor fluctuations in Parkinson's disease: A review on nonmotor fluctuations

The Parkinson's disease e‐diary: Developing a clinical and research tool for the digital age

Correlation of Quantitative Motor State Assessment Using a Kinetograph and Patient Diaries in Advanced PD: Data from an Observational Study

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