Spontaneous Hemorrhagic Pericardial Effusion as a Consequence of Apixaban Utilization for New-Onset Atrial Fibrillation.

Although anticoagulation stands as a standardized therapeutic approach for mitigating thrombotic risks in atrial fibrillation, the potential for bleeding associated with direct oral anticoagulants (DOACs) is consistently weighed in the risk/benefit analysis prior to initiating therapy for non-valvular atrial fibrillation. While the typical bleeding risks from DOACs predominantly affect the gastrointestinal system, occurrences of spontaneous hemorrhagic pericardial effusions are rare. This case presentation illustrates a patient developing spontaneous hemorrhagic pericardial effusion four days after commencing apixaban therapy and subsequent management.

Epstein-Barr Acute Viral Hepatitis With Hyperferritinemia Presents as Obstructive Cholangitis.

Epstein-Barr Virus (EBV), also known as human herpesvirus 4, is a rare cause of hepatitis and myocarditis. Severe cases of EBV hepatitis have been documented in immunocompromised cases; however, it is even more uncommonly seen in the immunocompetent population. Our case highlights EBV hepatitis presenting as acute abdominal pain in a young male with no known medical conditions.

Dynamic Monitoring of Probiotics Effect in Parkinson's Disease Patients via Swarm Decomposition and Bispectral Analysis of Electrogastrograms.

People with Parkinson's Disease (PwP) experience a significant deterioration of their daily life quality due to non-motor symptoms, with gastrointestinal dysfunctions manifesting as a vanguard of the latter. Electrogastrography (EGG) is a noninvasive diagnostic tool that can potentially provide biomarkers for the monitoring of dynamic gastric alterations that are related to daily lifestyle and treatment regimens. In this work, a robust analysis of EGG dynamics is introduced to evaluate the effect of probiotic treatment on PwP. The proposed framework, namely biSEGG, introduces a Swarm Decomposition-based enhancement of the EGG, combined with Bispectral feature engineering to model the underlying Quadratic Phase Coupling interactions between the gastric activity oscillatory components of EGG. The biSEGG features are benchmarked against the conventional Power Spectrum-based ones and evaluated through machine learning classifiers. The experimental results, when biSEGG was applied on data epochs from 11 PwP (probiotic vs placebo, AUROC: 0.67, Sensitivity/Specificity: 75/58%), indicate the superiority of biSEGG over Power Spectrum-based approaches and justify the efficiency of biSEGG in capturing and explaining intervention- and meal consumption-related alterations of the gastric activity in PwP.Clinical relevance- biSEGG holds potential for dynamic monitoring of gastrointestinal dysfunction and health status of PwP across diverse daily life scenarios.

Mechanical Thrombectomy of a Submassive Pulmonary Embolism in the Second Trimester of Pregnancy.

Venous thromboembolism (VTE) represents a potentially severe and infrequent complication that can occur in the pregnant population. The nuance in recognizing and diagnosing this condition can be quite difficult due to the changes that occur during pregnancy. This case highlights the importance of diagnosing pulmonary embolism in pregnancy, classifying the degree of disease, and determining the best treatment for both mother and fetus. Although rare, early diagnosis and treatment are crucial in order to reduce morbidity and mortality.

The real-life effect of catechol-O-methyltransferase inhibition on non-motor symptoms in levodopa-treated Parkinson's disease: opicapone versus entacapone.

OBJECTIVE: To evaluate the long-term, real-life effects on non-motor symptoms (NMS) of opicapone compared to entacapone in levodopa-treated people with Parkinson's disease (PwP). METHODS: A retrospective data analysis, with pre- and post-opicapone initiation data of 17 PwP with motor fluctuations compared to a comparable group of 18 PwP introduced on entacapone. The primary outcome was changes in the NMS Scale (NMSS) total score after 1-year follow-up. Secondary outcomes included changes in the NMSS domains, and Parkinson's Disease Sleep Scale (PDSS) total and item scores after the same time span. RESULTS: Groups were comparable for baseline demographics and Parkinson's-related features (p ≥ 0.314) as well as duration of follow-up (1.33 ± 0.66 years for PwP on opicapone and 1.23 ± 0.49 years for those on entacapone; p = 0.858). PwP who were introduced on opicapone showed no changes in NMSS and PDSS total scores after 1 year (p = 0.605 and p = 0.507, respectively), whereas PwP who were introduced on entacapone showed significant worsening of NMSS and PDSS total scores at follow-up (p = 0.005 and p = 0.001, respectively). In neither group changes in individual NMSS domains from baseline to follow-up were observed (p ≥ 0.288 for entacapone and p ≥ 0.816 for opicapone, respectively). In PwP on entacapone significant worsening was seen in the distressing dreams, hallucinations, and limb numbness items of the PDSS (p ≤ 0.05). CONCLUSIONS: Introduction of opicapone in real-life PwP with motor fluctuations seems to stabilise NMS burden and aspects of sleep dysfunction, in contrast to entacapone where there was a worsening of NMS burden and PDSS scores over 1 year follow-up.

NMDA Receptor Antibodies and Neuropsychiatric Symptoms in Parkinson's Disease.

OBJECTIVE: N-methyl-d-aspartate receptor (NMDAR) encephalitis is an autoantibody-mediated neurological syndrome with prominent cognitive and neuropsychiatric symptoms. The clinical relevance of NMDAR antibodies outside the context of encephalitis was assessed in this study. METHODS: Plasma from patients with Parkinson's disease (PD) (N=108) and healthy control subjects (N=89) was screened at baseline for immunoglobulin A (IgA), IgM, and IgG NMDAR antibodies, phosphorylated tau 181 (p-tau181), and the neuroaxonal injury marker neurofilament light (NfL). Clinical assessment of the patients included measures of cognition (Mini-Mental State Examination [MMSE]) and neuropsychiatric symptoms (Hospital Anxiety and Depression Scale; Non-Motor Symptoms Scale for Parkinson's Disease). A subgroup of patients (N=61) was followed annually for up to 6 years. RESULTS: Ten (9%) patients with PD tested positive for NMDAR antibodies (IgA, N=5; IgM, N=6; IgG, N=0), and three (3%) healthy control subjects had IgM NMDAR antibodies; IgA NMDAR antibodies were detected significantly more commonly among patients with PD than healthy control subjects (χ2=4.23, df=1, p=0.04). Age, gender, and disease duration were not associated with NMDAR antibody positivity. Longitudinally, antibody-positive patients had significantly greater decline in annual MMSE scores when the analyses were adjusted for education, age, disease duration, p-tau181, NfL, and follow-up duration (adjusted R2=0.26, p=0.01). Neuropsychiatric symptoms were not associated with antibody status, and no associations were seen between NMDAR antibodies and p-tau181 or NfL levels. CONCLUSIONS: NMDAR antibodies were associated with greater cognitive impairment over time in patients with PD, independent of other pathological biomarkers, suggesting a potential contribution of these antibodies to cognitive decline in PD.

An Aggressive Form of Medullary Thyroid Carcinoma-Melanocytic Subtype: A Case Report.

Medullary thyroid cancer (MTC) represents a small proportion of thyroid cancers. In MTC, melanin production is extremely uncommon. Few case reports have documented this rare variant, and follow-up on these cases has been very limited. Our case studies a 51-year-old female who initially presented with goiter. This tumor recurred multiple times despite surgery with rapid growth and poor response to radiotherapy. Microscopic examination showed high-grade malignant neoplasm with lymphocytic differentiation. Immunohistochemical studies were diffusely positive for S100, SOX10, and Melan-A. Histology confirmed melanocytic medullary carcinoma that had undergone a high-grade transformation with loss of epithelial and neuroendocrine expression. Due to the scarcity and rarity of this subtype, further evaluation and case studies are needed for further categorization and prognostication.

Plasma p-tau181, neurofilament light chain and association with cognition in Parkinson's disease.

Early identification of cognitive impairment in Parkinson's disease (PD) has important clinical and research implications. The aim of our study was to investigate the role of plasma tau phosphorylated at amino acid 181 (p-tau181) and plasma neurofilament light chain (NfL) as biomarkers of cognition in PD. Baseline concentrations of plasma p-tau181 and NfL were measured in a cohort of 136 patients with PD and 63 healthy controls (HC). Forty-seven PD patients were followed up for up to 2 years. Cross-sectional and longitudinal associations between baseline plasma biomarkers and cognitive progression were investigated using linear regression and linear mixed effects models. At baseline, plasma p-tau181 concentration was significantly higher in PD subjects compared with HC (p = 0.026). In PD patients, higher plasma NfL was associated with lower MMSE score at baseline, after adjusting for age, sex and education (p = 0.027). Baseline plasma NfL also predicted MMSE decline over time in the PD group (p = 0.020). No significant association between plasma p-tau181 concentration and baseline or longitudinal cognitive performance was found. While the role of p-tau181 as a diagnostic biomarker for PD and its relationship with cognition need further elucidation, plasma NfL may serve as a feasible, non-invasive biomarker of cognitive progression in PD.

Plasma Neurofilament Light and p-tau181 and Risk of Psychosis in Parkinson's Disease.

BACKGROUND: Neuropsychiatric symptoms are common and important to people with Parkinson's disease (PD), but their etiology is poorly understood. Plasma neurofilament light (NfL) and p-tau181 are biomarkers of neuro-axonal degeneration and tau pathology respectively, which have yet to be explored in association with the affective and psychotic symptoms in PD. OBJECTIVE: To investigate the relationship between plasma NfL and p-tau181 with the affective and psychotic symptoms in PD. METHODS: We assessed the baseline concentration of plasma NfL and p-tau181 in a cohort of 108 patients with PD and 38 healthy controls. A subgroup of patients (n = 63) were assessed annually with clinical measures for up to 7 years. Psychotic symptoms were assessed using the Non-Motor Symptom Scale and affective symptoms were measured in the Hospital Anxiety and Depression Scale. RESULTS: Baseline plasma NfL was a significant predictor of psychotic symptoms longitudinally across the study adjusted for age, Hoehn and Yahr stage, duration of follow up, duration of disease, baseline levodopa and dopamine agonist medication, and baseline cognition: (OR 8.15 [95% CI 1.40-47.4], p = 0.020). There was no association between NfL concentration and the cumulative prevalence of affective symptoms. Plasma p-tau181 concentration was not associated with psychotic or affective symptoms. CONCLUSION: These findings suggest psychotic symptoms are associated with greater neurodegeneration in PD. Further studies are needed to explore NfL as a potential biomarker for psychosis in PD.

Ethnic Disparities in Treatment of Chronic Pain in Individuals with Parkinson's Disease Living in the United Kingdom.

Background: Over 80% people with Parkinson's disease (PD; PwP) live with chronic pain. Objective: Whether ethnic disparities in receipt of appropriate analgesia exist among PwP with chronic pain living in the United Kingdom (UK). Methods: A retrospective datamining of an existing King's PD Pain Questionnaire validation study dataset enrolling 300 PwP. Results: 69 PwP: 23 Black (57% female), 23 Asian (57% female) and 23 White (65% female) had similar pain burden on the King's PD Pain Scale. Significantly more White PwP (83%) received pain relief compared to Black (48%) and Asian (43%) PwP (p = 0.016). The difference was most evident for opioid analgesics (White 43% vs. Black 4% vs. Asian 4%, p ≤ 0.001). Conclusions: Ethnic disparities in the analgesic use among PwP with chronic pain living in the UK are evident in this retrospective analysis, prompting large-scale studies and reinforcement of interventions to tackle the impact ethnicity might have on the successful analgesia.

Parkinson's Disease Detection Based on Running Speech Data From Phone Calls.

OBJECTIVE: Parkinson's Disease (PD) is a progressive neurodegenerative disorder, manifesting with subtle early signs, which, often hinder timely and early diagnosis and treatment. The development of accessible, technology-based methods for longitudinal PD symptoms tracking in daily living, offers the potential for transforming disease assessment and accelerating diagnosis. METHODS: A privacy-aware method for classifying patients and healthy controls (HC), on the grounds of speech impairment present in PD, is proposed. Voice features from running speech signals were extracted from passively-captured recordings over voice calls. Language-aware training of multiple- and single-instance learning classifiers was employed to fuse and predict on voice features and demographic data from a multilingual cohort of 498 subjects (392/106 self-reported HC/PD patients). RESULTS: By means of leave-one-subject-out cross-validation, the best-performing models yielded 0.69/0.68/0.63/0.83 area under the Receiver Operating Characteristic curve (AUC) for the binary classification of PD patient vs. HC in sub-cohorts of English/Greek/German/Portuguese-speaking subjects, respectively. Out-of sample testing of the best performing models was conducted in an additional dataset, generated by 63 clinically-assessed subjects (24/39 HC/early PD patients). Testing has resulted in 0.84/0.93/0.83 AUC for the English/Greek/German-speaking sub-cohorts, respectively. CONCLUSIONS: The proposed approach outperforms other methods proposed for language-aware PD detection considering the ecological validity of the voice data. SIGNIFICANCE: This paper introduces for the first time a high-frequency, privacy-aware and unobtrusive PD screening tool based on analysis of voice samples captured during routine phone calls.

Parkinson's Disease: Personalized Pathway of Care for Device-Aided Therapies (DAT) and the Role of Continuous Objective Monitoring (COM) Using Wearable Sensors.

Parkinson's disease (PD) is a chronic, progressive neurological disorder and the second most common neurodegenerative condition. Advanced PD is complicated by erratic gastric absorption, delayed gastric emptying in turn causing medication overload, and hence the emergence of motor and non-motor fluctuations and dyskinesia, which is initially predictable and then becomes unpredictable. As the patient progresses to the advanced stage, advanced Parkinson's disease (APD) is characterized by refractory motor and non motor fluctuations, unpredictable OFF periods, and troublesome dyskinesias. The management of APD is a complex affair. There is growing recognition that GI dysfunction is common in PD, with virtually the entire GI system (the upper and lower GI tracts) causing problems from dribbling to defecation. The management of PD should focus on personalized care addressing both motor and non-motor symptoms, ideally including not only dopamine replacement but also associated non-dopaminergic circuits, particularly focusing on noradrenergic, serotonergic, and cholinergic therapies bypassing the gastrointestinal tract (GIT) by infusion or device-aided therapies (DAT), including levodopa-carbidopa intestinal gel infusion, apomorphine subcutaneous infusion, and deep brain stimulation, which are available in many countries for the management of the advanced stage of Parkinson's disease (APD). The PKG (KinetiGrap) can be used as a continuous objective monitoring (COM) aid, as a screening tool to help to identify advanced PD (APD) patients suitable for DAT, and can thus improve clinical outcomes.

Digital health technology for non-motor symptoms in people with Parkinson's disease: Futile or future?

INTRODUCTION: There is an ongoing digital revolution in the field of Parkinson's disease (PD) for the objective measurement of motor aspects, to be used in clinical trials and possibly support therapeutic choices. The focus of remote technologies is now also slowly shifting towards the broad but more "hidden" spectrum of non-motor symptoms (NMS). METHODS: A narrative review of digital health technologies for measuring NMS in people with PD was conducted. These digital technologies were defined as assessment tools for NMS offered remotely in the form of a wearable, downloadable as a mobile app, or any other objective measurement of NMS in PD that did not require a hospital visit and could be performed remotely. Searches were performed using peer-reviewed literature indexed databases (MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane CENTRAL Register of Controlled Trials), as well as Google and Google Scholar. RESULTS: Eighteen studies deploying digital health technology in PD were identified, for example for the measurement of sleep disorders, cognitive dysfunction and orthostatic hypotension. In addition, we describe promising developments in other conditions that could be translated for use in PD. CONCLUSION: Unlike motor symptoms, non-motor features of PD are difficult to measure directly using remote digital technologies. Nonetheless, it is currently possible to reliably measure several NMS and further digital technology developments are underway to offer further capture of often under-reported and under-recognised NMS.

The impact of COVID-19 on palliative care for people with Parkinson's and response to future pandemics.

Introduction: Although in some countries, palliative care (PC) still remains poorly implemented, its importance throughout the course of Parkinson's disease (PD) is increasingly being acknowledged. With an emergence of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic, growing emphasis has been placed on the palliative needs of people with Parkinson's (PwP), particularly elderly, frail, and with comorbidities.Areas covered: The ongoing COVID-19 pandemic poses an enormous challenge on aspects of daily living in PwP and might interact negatively with a range of motor and non-motor symptoms (NMS), both directly and indirectly - as a consequence of pandemic-related social and health care restrictions. Here, the authors outline some of the motor and NMS relevant to PC, and propose a pragmatic and rapidly deployable, consensus-based PC approach for PwP during the ongoing COVID-19 pandemic, potentially relevant also for future pandemics.Expert opinion: The ongoing COVID-19 pandemic poses a considerable impact on PwP and their caregivers, ranging from mental health issues to worsening of physical symptoms - both in the short- and long-term, (Long-COVID) and calls for specific, personalized PC strategies relevant in a lockdown setting globally. Validated assessment tools should be applied remotely to flag up particular motor or NMS that require special attention, both in short- and long-term.

Nonmotor symptom burden grading as predictor of cognitive impairment in Parkinson's disease.

BACKGROUND: Identifying predictors of incident cognitive impairment (CI), one of the most problematic long-term outcomes, in Parkinson's disease (PD) is highly relevant for personalized medicine and prognostic counseling. The Nonmotor Symptoms Scale (NMSS) provides a global clinical assessment of a range of NMS, reflecting NMS burden (NMSB), and thus may assist in the identification of an "at-risk" CI group based on overall NMSB cutoff scores. METHODS: To investigate whether specific patterns of PD NMS profiles predict incident CI, we performed a retrospective longitudinal study on a convenience sample of 541 nondemented PD patients taking part in the Nonmotor Longitudinal International Study (NILS) cohort, with Mini-Mental State Examination (MMSE), NMSS, and Scales for Outcomes in PD Motor Scale (SCOPA Motor) scores at baseline and last follow-up (mean 3.2 years) being available. RESULTS: PD patients with incident CI (i.e., MMSE score ≤ 25) at last follow-up (n = 107) had severe overall NMSB level, significantly worse NMSS hallucinations/perceptual problems and higher NMSS attention/memory scores at baseline. Patients with CI also were older and with more advanced disease, but with no differences in disease duration, dopamine replacement therapy, sex, and comorbid depression, anxiety, and sleep disorders. CONCLUSIONS: Our findings suggest that a comprehensive baseline measure of NMS and in particular hallucinations and perceptual problems assessed with a validated single instrument can be used to predict incident CI in PD. This approach provides a simple, holistic strategy to predict future CI in this population.

The impact of advances in percutaneous catheter interventions on redo cardiac surgery.

Toward the end of the twentieth century, redo cardiac surgery accounted for approximately 15-20% of total cardiac surgical volume. Major risk factors for redo cardiac surgery include young age at time of the first operation, progression of native coronary artery disease (CAD), vein graft atherosclerosis, bioprosthetic valve failure and endocarditis, and transplantation for end stage heart failure. Historically, redo coronary artery bypass grafting (CABG) alone carried a mortality risk of around 4%. Factors such as older age, female sex, comorbidities, combined procedures, hemodynamic instability, and emergency procedures contributed to even higher mortality and morbidity. These poor outcomes made it necessary to look for less invasive alternate methods of treatment. Advances in catheter-based interventions have made a major impact on redo cardiac surgeries, making it no longer the first option in a majority of cases. Percutaneous interventions for recurrence following CABG, transcutaneous aortic valve replacement (TAVR) for calcific aortic stenosis, valve in valve (VIV) implantations, device closure of paravalvular leaks (PVL), and thoracic endovascular aortic repair (TEVAR) for residual and recurrent aneurysms and mitral clip to correct mitral regurgitation (MR) in heart failure are rapidly developing or developed, obviating the need for redo cardiac surgery. Our intent is to review these advances and their impact on redo cardiac surgery.

Smartwatch-based Activity Analysis During Sleep for Early Parkinson's Disease Detection.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder with the non-motor symptoms preceding the motor impairment that is needed for clinical diagnosis. In the current study, an angle-based analysis that processes activity data during sleep from a smartwatch for quantification of sleep quality, when applied on controls and PD patients, is proposed. Initially, changes in their arm angle due to activity are captured from the smartwatch triaxial accelerometry data and used for the estimation of the corresponding binary state (awake/sleep). Then, sleep metrics (i.e., sleep efficiency index, total sleep time, sleep fragmentation index, sleep onset latency, and wake after sleep onset) are computed and used for the discrimination between controls and PD patients. A process of validation of the proposed approach when compared with the PSG-based ground truth in an in-the-clinic setting, resulted in comparable state estimation. Moreover, data from 15 early PD patients and 11 healthy controls were used as a test set, including 1,376 valid sleep recordings in-the-wild setting. The univariate analysis of the extracted sleep metrics achieved up to 0.77 AUC in early PD patients vs. healthy controls classification and exhibited a statistically significant correlation (up to 0.46) with the clinical PD Sleep Scale 2 counterpart Items. The findings of the proposed method show the potentiality to capture non-motor behavior from users' nocturnal activity to detect PD in the early stage.

Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients and is now known to be evident in the immediate prodromal stage of the condition. The clinical techniques for detecting FMI may not be robust enough and here, we show that the subtle FMI of early PD patients can be effectively estimated from the analysis of natural smartphone touchscreen typing via deep learning networks, trained in stages of initialization and fine-tuning. In a validation dataset of 36,000 typing sessions from 39 subjects (17 healthy/22 PD patients with medically validated UPDRS Part III single-item scores), the proposed approach achieved values of area under the receiver operating characteristic curve (AUC) of 0.89 (95% confidence interval: 0.80-0.96) with sensitivity/specificity: 0.90/0.83. The derived estimations result in statistically significant ([Formula: see text]) correlation of 0.66/0.73/0.58 with the clinical standard UPDRS Part III items 22/23/31, respectively. Further validation analysis on 9 de novo PD patients vs. 17 healthy controls classification resulted in AUC of 0.97 (0.93-1.00) with 0.93/0.90. For 253 remote study participants, with self-reported health status providing 252.000 typing sessions via a touchscreen typing data acquisition mobile app (iPrognosis), the proposed approach predicted 0.79 AUC (0.66-0.91) with 0.76/0.71. Remote and unobtrusive screening of subtle FMI via natural smartphone usage, may assist in consolidating early and accurate diagnosis of PD.

Assistive HCI-Serious Games Co-design Insights: The Case Study of i-PROGNOSIS Personalized Game Suite for Parkinson's Disease.

Human-Computer Interaction (HCI) and games set a new domain in understanding people's motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people's health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson's Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients' quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.

Non-motor correlates of wrist-worn wearable sensor use in Parkinson's disease: an exploratory analysis.

Wearable sensors are becoming increasingly more available in Parkinson's disease and are used to measure motor function. Whether non-motor symptoms (NMS) can also be measured with these wearable sensors remains unclear. We therefore performed a retrospective, exploratory, analysis of 108 patients with a diagnosis of idiopathic Parkinson's disease enroled in the Non-motor Longitudinal International Study (UKCRN No. 10084) at King's College Hospital, London, to determine the association between the range and nature of NMS and an accelerometer-based outcome measure of bradykinesia (BKS) and dyskinesia (DKS). NMS were assessed by the validated NMS Scale, and included, e.g., cognition, mood and sleep, and gastrointestinal, urinary and sexual problems. Multiple linear regression modelling was used to identify NMS associated with BKS and DKS. We found that BKS was associated with domains 6 (gastrointestinal tract; p = 0.006) and 8 (sexual function; p = 0.003) of the NMS scale. DKS was associated with domains 3 (mood/cognition; p = 0.016), 4 (perceptual problems; p = 0.025), 6 (gastrointestinal tract; p = 0.029) and 9 (miscellaneous, p = 0.003). In the separate domains, constipation was significantly associated with BKS. Delusions, dysphagia, hyposmia, weight change and hyperhidrosis were identified as significantly associated with DKS. None of the NMSS domains were associated with disease duration (p ≥ 0.08). In conclusion, measures of BKS and DKS were mainly associated with gastrointestinal problems, independent of disease duration, showing the potential for wearable devices to pick up on these symptoms. These exploratory results deserve further exploration, and more research on this topic in the form of comprehensive large-scale studies is needed.