Wearable multimodal sensing for quantifying the cardiovascular autonomic effects of levodopa in parkinsonism - Berkebile, John A.; Inan, Omer T.; Beach, Paul A. (Frontiers in Network Physiology, 2025)
Levodopa is the most common therapy to reduce motor symptoms of parkinsonism. However, levodopa has potential to exacerbate cardiovascular autonomic (CVA) dysfunction that may co-occur in patients. Heart rate variability (HRV) is the most common method for assessing CVA function, but broader monitoring of CVA function and levodopa effects is typically limited to clinical settings and symptom reporting, which fail to capture its holistic nature. In this study, we evaluated the feasibility of a multimodal wearable chest patch for monitoring changes in CVA function during clinical and 24-h ambulatory (at home) conditions in 14 patients: 11 with Parkinson’s disease (PD) and 3 with multiple system atrophy (MSA). In-clinic data were analyzed to examine the effects of orally administered levodopa on CVA function using a pre (OFF) and 60-min (ON) post-exposure protocol. Wearable-derived physiological markers related to the electrical and mechanical activity of the heart alongside vascular function were extracted. Pre-ejection period (PEP) and ratio of PEP to left ventricular ejection time index (LVETi) increased significantly (p<0.05) following levodopa, indicating a decrease in cardiac contractility. We further explored dose-response relationships and how CVA responses differed between participants with orthostatic hypotension (OH) from those without OH. Heart rate variability, specifically root-mean-square-of-successive-differences (RMSSD), following levodopa decreased significantly more in participants with OH (n = 7) compared to those without (no-OH, n = 7). The results suggest that the wearable patch’s measures are sensitive to CVA dynamics and provide exploratory insights into levodopa’s potential role in inducing a negative inotropic effect and exacerbating CVA dysfunction. This work encourages further evaluation of these wearable-derived physiomarkers for quantifying CVA and informing individualized care of individuals with parkinsonism.