Affiliations: [a] KU Leuven, Department of Rehabilitation Sciences, Neurorehabilitation Research Group, Leuven, Belgium
| [b] KU Leuven, Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat), Leuven, Belgium
| [c]
University of Lille, Expert Center for Parkinson Disease, CHU Lille, Inserm UMR, France
| [d] KU Leuven, Department of Neurosciences, Laboratory for Parkinson Research, Leuven, Belgium
Correspondence:
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Correspondence to: Nicholas D’Cruz, MSc, Department of Rehabilitation Sciences, KU Leuven, Tervuursevest 101 Bus 1501, B-3001 Leuven, Belgium. Tel.: +3216376003; E-mail: nicholas.dcruz@kuleuven.be.
Abstract: Background:The onset of freezing of gait (FOG) represents a turning point in the lives of patients with Parkinson’s disease (PD). FOG increases fall risk and is associated with worse physical and mental health related quality of life, thus increasing disease burden. Moreover, therapeutic studies aiming to ameliorate freezing have had limited success. In a step towards pre-emptive therapy to delay or prevent the onset of FOG, this prospective cohort study set out to uncover clinical markers of conversion to FOG. Objective:Investigate clinical markers of conversion to FOG. Methods:Sixty PD patients without FOG were followed up for two years and underwent extensive clinical testing each year. FOG classification was made with the New Freezing of Gait Questionnaire. Clinical predictors of conversion to FOG were investigated using univariate analysis and through building a multivariable model using all measured components. Results:Twelve patients developed FOG during the study (Incidence: 11.5% per year). Due to the large number of predictors, univariate analyses did not survive multiple comparison correction, precluding strong inference on any one predictor. Overall, the effect sizes suggested that motor deficits including difficulties with repetitive movement scaling (AUC: 0.71), coordination (AUC: 0.73) and consistency (AUC: 0.76) as well as gait asymmetry (AUC: 0.79) and variability (AUC: 0.71) were most predictive of conversion. Further, converters reported more subjective cognitive difficulty (AUC: 0.74), although their measured performance was similar to non-converters. Multivariable analyses further showed that the two components most consistently selected in the predictive model were: 1) an MDS-UPDRS component with worse axial motor, hand use and non-motor symptoms; and 2) finger tapping abnormalities. Conclusion:Conversion to FOG was predicted mainly by objective and clinical measures of motor dyscontrol, as non-motor disturbances were surfacing. Although based on a small cohort with limited converters, this novel finding informs future studies aimed at FOG prevention.
