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

The PKG is one of the better examples of wearable tech that is available for monitoring PD. Clearly there remains some improvements to be made, but it has already entered the clinical arena and is being used to supplement patient care. Other studies that used it showed improvements in total 'On' time and reductions in 'dyskinesia time'. One problem with the present study is that the home diary method is not without its flaws. Sometimes it is hard to marry up exactly what one sees objectively and what the patient experiences subjectively...

PLoS One. 2016 Aug 24;11(8):e0161559. doi: 10.1371/journal.pone.0161559. eCollection 2016.

Ossig C, Gandor F, Fauser M, Bosredon C, Churilov L, Reichmann H, Horne MK, Ebersbach G, Storch A.

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0161559

INTRODUCTION:

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.

OBJECTIVE:

To compare quantitative motor state assessment in fluctuating PD patients using the PKG with motor state ratings from PD home diaries.

METHODS:

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.

RESULTS:

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).

CONCLUSION:

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.