A BST RACT : Background: Freezing of gait is a disabling symptom of Parkinson's disease that ultimately affects approximately 80% of patients, yet very little research has focused on predicting the onset of freezing of gait and tracking the longitudinal progression of symptoms prior to its onset. The objective of the current study was to examine longitudinal data spanning the transition period when patients with PD developed freezing of gait to identify symptoms that may precede freezing and create a prediction model that identifies those "at risk" for developing freezing of gait in the year to follow. Methods: Two hundred and twenty-one patients with PD were divided into 3 groups (88 nonfreezers, 41 transitional freezers, and 92 continuing freezers) based on their responses to the validated Freezing of GaitQuestionnaire item 3 at baseline and follow-up. Critical measures across motor, cognitive, mood, and sleep domains were assessed at 2 times approximately 1 year apart.Results: A logistic regression model that included age, disease duration, gait symptoms, motor phenotype, attentional set-shifting, and mood measures could predict with 70% and 90% accuracy those patients who would and would not develop, respectively, freezing of gait over the next year. Notably, the Freezing of Gait-Questionnaire total and the anxiety section of the Hospital Anxiety and Depression Scale were the strongest predictors and alone could significantly predict if one might develop freezing of gait in the next 15 months with 82% accuracy. Conclusions: Our results suggest that it is possible to identify the majority of patients who will develop freezing of gait in the following year, potentially allowing targeted interventions to delay or possibly even prevent the onset of freezing. Although approximately 80% of patients ultimately develop FOG, 3 predicting who and when is currently not possible, thus thwarting targeted interventions.To date, only 2 studies have followed early-stage PD patients over time to examine the risk factors associated with the development of FOG. 4,5 Findings from the DATATOP cohort suggested that the risk of developing FOG was significantly higher in more advanced PD patients with predominant gait, balance, speech, and bradykinetic motor symptoms rather than tremordominant symptoms.5 A more recent study also identified an akinetic-rigid phenotype as a primary risk factor for FOG along with lower education, not using a dopamine agonist, and higher scores on the mood, cognitive disturbance, and sleep disorder domains of the Hamilton Depression Rating Scale in a Chinese population when followed over 3 years.
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