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

Overview of attention for article published in PLOS ONE, August 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

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1 news outlet

Citations

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55 Dimensions

Readers on

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97 Mendeley
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Title
Correlation of Quantitative Motor State Assessment Using a Kinetograph and Patient Diaries in Advanced PD: Data from an Observational Study
Published in
PLOS ONE, August 2016
DOI 10.1371/journal.pone.0161559
Pubmed ID
Authors

Christiana Ossig, Florin Gandor, Mareike Fauser, Cecile Bosredon, Leonid Churilov, Heinz Reichmann, Malcolm K. Horne, Georg Ebersbach, Alexander Storch

Abstract

Effective 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. To compare quantitative motor state assessment in fluctuating PD patients using the PKG with motor state ratings from PD home diaries. Observational 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. From 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). The 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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 97 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 19%
Student > Ph. D. Student 11 11%
Other 7 7%
Student > Bachelor 7 7%
Student > Postgraduate 5 5%
Other 15 15%
Unknown 34 35%
Readers by discipline Count As %
Medicine and Dentistry 16 16%
Neuroscience 10 10%
Engineering 8 8%
Computer Science 5 5%
Agricultural and Biological Sciences 3 3%
Other 15 15%
Unknown 40 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 September 2016.
All research outputs
#4,192,005
of 22,884,315 outputs
Outputs from PLOS ONE
#59,834
of 195,166 outputs
Outputs of similar age
#71,903
of 341,473 outputs
Outputs of similar age from PLOS ONE
#1,099
of 4,277 outputs
Altmetric has tracked 22,884,315 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 195,166 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has gotten more attention than average, scoring higher than 68% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,473 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 4,277 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.