BackgroundDriving is a complex, everyday task that impacts patient agency, safety, mobility, social connections, and quality of life. Digital tools can provide comprehensive real‐world (RW) data on driver behavior in patients with Parkinson's disease (PD), providing critical data on disease status and treatment efficacy in the patient's own environment.ObjectiveThis pilot study examined the use of driving data as a RW digital biomarker of PD symptom severity and dopaminergic therapy effectiveness.MethodsNaturalistic driving data (3974 drives) were collected for 1 month from 30 idiopathic PD drivers treated with dopaminergic medications. Prescriptions data were used to calculate levodopa equivalent daily dose (LEDD). The association between LEDD and driver mobility (number of drives) was assessed across PD severity, measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS‐UPDRS).ResultsPD drivers with worse motor symptoms based on self‐report (Part II: P = 0.02) and clinical examination (Part III: P < 0.001) showed greater decrements in driver mobility. LEDD levels >400 mg/day were associated with higher driver mobility than those with worse PD symptoms (Part I: P = 0.02, Part II: P < 0.001, Part III: P < 0.001).ConclusionsResults suggest that comprehensive RW driving data on PD patients may index disease status and treatment effectiveness to improve patient symptoms, safety, mobility, and independence. Higher dopaminergic treatment may enhance safe driver mobility in PD patients with worse symptom severity.

BackgroundSleep dysfunction is signature of Alzheimer’s disease and Parkinson’s disease (PD), and can signify incipient disease, disease risk, and worsen symptoms over time. How real‐world sleep dysfunction relates to patient self‐report of sleep and clinical cognitive dysfunction is poorly understood, partly because self ‐report is impaired in patients with cognitive decline. We monitored real‐world sleep with wearable actigraphy devices in patients with PD to test the hypothesis that objective patterns of sleep dysfunction are associated with worse cognitive performance.MethodTwenty‐nine participants with idiopathic PD (age = 67.44 ± 5.79, 20 males) completed the Montreal Cognitive Assessment (MoCA) and Epworth Sleepiness Scale (ESS) to capture clinical cognitive decline and self‐reported daytime sleepiness. Sleep was monitored for 4‐weeks using wrist‐worn ActiGraphs. Sub‐scores and total scores of MoCA were compared with Total Sleep Time (TST), Sleep Efficiency (SE), Wakefulness After Sleep Onset (WASO), and Sleep Fragmentation Index (SFI) measured by actigraphy, as well as ESS total using a Pearson correlation.ResultWorse sleep fragmentation (SFI), the percentage of awakenings and movements during sleep, predicted worse cognitive impairment overall (MoCA score: r = ‐0.38, p < .05) and delayed recall (r = ‐0.44, p < .05). Reduced sleep time (TST) and worse sleep quality (SE, WASO) did not worsen patient cognitive impairment. Patient self‐report of sleepiness (ESS) did not associate with worse cognitive outcomes.ConclusionThis pilot analysis identifies sleep fragmentation as a key risk factor for cognitive dysfunction in PD. Patient self‐report of sleep may not reliably reflect chronic sleep disruption and related cognitive dysfunction. Results underscore that objective measures of real‐world dysfunction can help inform clinical care and intervention for patients at risk for cognitive decline and dementia.

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Background Age-related neurodegenerative disorders, including Alzheimer’s disease and Parkinson’s disease (PD), progressively reduce mobility and quality of life (QoL). Real-world mobility from actigraphy predicts PD disease severity. This pilot analysis assessed utility of actigraphy to screen early physical function-related QoL decline in PD. Method: Mobility was monitored for 4 weeks using wrist-worn ActiGraph recordings in 27 participants with idiopathic PD (age = 67.78 ± 5.64, 19 males). Days with &gt;600 mins of wear time during non-sleep times were analyzed (µ = 29.78 days ± 3.78). Typical activity was quantified as average steps per hour. Participants completed demographic and health assessments. Disease severity and physical function QoL were measured using the clinically-validated Unified PD Rating Scale (MDS-UPDRS) and Short Form-36 (SF-36), respectively. Disease severity, QoL, and typical activity were compared using Spearman correlations. Results Lower typical activity from actigraphy was associated with more severe motor symptoms (MDS-UPDRS; r = -0.40, p = 0.04) and with increased impairment in physical function QoL (r = 0.50, p &lt; 0.01). Daily activity from actigraphy did not predict symptom severity of non-motor and motor-related complications. Discussion: Pilot results show utility of actigraphic metrics for indexing real-world mobility and QoL declines in neurodegenerative disorders, in line with broader efforts to turn real-world data into actionable evidence for healthcare interventions. Ongoing discovery in larger populations should yield robust, clinically-relevant indices of daily activity in aging and neurodegenerative impairment.