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The Unified Parkinson's Disease Rating Scale (UPDRS) is used to recognize patients with Parkinson's disease (PD) and rate its severity. The rating is crucial for disease progression monitoring and treatment adjustment. This study aims to advance the capabilities of PD management by developing an innovative framework that integrates deep learning with wearable sensor technology to enhance the precision of UPDRS assessments. We introduce a series of deep learning models to estimate UPDRS Part III scores, utilizing motion data from wearable sensors. Our approach leverages a novel Multi-shared-task Self-supervised Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) framework that processes raw gyroscope signals and their spectrogram representations. This technique aims to refine the estimation accuracy of PD severity during naturalistic human activities. Utilizing 526 min of data from 24 PD patients engaged in everyday activities, our methodology demonstrates a strong correlation of 0.89 between estimated and clinically assessed UPDRS-III scores. This model outperforms the benchmark set by single and multichannel CNN, LSTM, and CNN-LSTM models and establishes a new standard in UPDRS-III score estimation for free-body movements compared to recent state-of-the-art methods. These results signify a substantial step forward in bioengineering applications for PD monitoring, providing a robust framework for reliable and continuous assessment of PD symptoms in daily living settings.
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The 5-2-1 criteria was developed to facilitate the identification and referral of patients with Parkinson's Disease (PD) inadequately controlled by oral medications. The criterion was not developed to screen patients with PD for device-aided therapy eligibility. The robust design and validation of the 5-2-1 criteria minimizes over or inappropriate referrals, and supports physicians in the timely identification of patients with PD who may warrant further evaluation for treatment optimization. This response letter clarifies concerns raised by Moes et al.
Subject(s)
Parkinson Disease , Parkinson Disease/diagnosis , Humans , Antiparkinson Agents/therapeutic useABSTRACT
Parkinson's Disease (PD) patients frequently transition between the 'ON' state, where medication is effective, and the 'OFF' state, affecting their quality of life. Monitoring these transitions is vital for personalized therapy. We introduced a framework based on Reinforcement Learning (RL) to detect transitions between medication states by learning from continuous movement data. Unlike traditional approaches that typically identify each state based on static data patterns, our approach focuses on understanding the dynamic patterns of change throughout the transitions, providing a more generalizable medication state monitoring method. We integrated a deep Long Short-Term Memory (LSTM) neural network and three one-class unsupervised classifiers to implement an RL-based adaptive classifier. We tested on two PD datasets: Dataset PD1 with 12 subjects (14-minute average recording) and Dataset PD2 with seven subjects (120-minute average recording). Data from wrist and ankle wearables captured transitions during 2 to 4-hour daily activities. The algorithm demonstrated its effectiveness in detecting medication states, achieving an average weighted F1-score of 82.94% when trained and tested on Dataset PD1. It performed well when trained on Dataset PD1 and tested on Dataset PD2, with a weighted F1-score of 76.67%. It surpassed other models, was resilient to severe PD symptoms, and performed well with imbalanced data. Notably, prior work has not addressed the generalizability from one dataset to another, essential for real-world applications with varied sensors. Our innovative framework revolutionizes PD monitoring, setting the stage for advanced therapeutic methods and greatly enhancing the life quality of PD patients.
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BACKGROUND: Deutetrabenazine is approved for adults with tardive dyskinesia (TD). Data based on underlying psychiatric condition and baseline dopamine receptor antagonist (DRA) use are limited. METHODS: Patients with TD who completed parent studies ARM-TD or AIM-TD were eligible for the 3-year, open-label extension study (RIM-TD; NCT02198794). In RIM-TD, deutetrabenazine was titrated based on dyskinesia control and tolerability. In this post hoc analysis of RIM-TD, total motor Abnormal Involuntary Movement Scale (AIMS) score and adverse events (AEs) were analyzed by underlying condition and DRA use at parent study baseline. RESULTS: Of 343 patients enrolled in RIM-TD, 336 were included in the analysis by underlying condition, and 337 were included in the analysis by DRA use. One hundred eighty-nine of 205 (92%) patients with psychotic disorders (schizophrenia/schizoaffective disorder) and 65 of 131 (50%) with mood and other disorders (depression/bipolar disorder/other) were receiving a DRA. Mean (SE) deutetrabenazine doses at week 145 were 40.4 (1.13), 38.5 (1.21), 39.9 (1.00), and 38.5 (1.48) mg/d for patients with psychotic disorders, those with mood and other disorders, and those receiving DRAs or not, respectively. Mean (SD) changes in total motor AIMS score from this study baseline to week 145 were -6.3 (4.53), -7.1 (4.92), -6.1 (4.42), and -7.5 (5.19). Exposure-adjusted incidence rates (number of AEs/patient-years) of AEs were similar across groups: any (1.02, 1.71, 1.08, 1.97), serious (0.10, 0.12, 0.10, 0.12), and leading to discontinuation (0.07, 0.05, 0.06, 0.05). CONCLUSIONS: Long-term deutetrabenazine provided clinically meaningful improvements in TD-related movements, with a favorable benefit-risk profile, regardless of underlying condition or DRA use.
Subject(s)
Dopamine Antagonists , Tardive Dyskinesia , Tetrabenazine , Humans , Tardive Dyskinesia/drug therapy , Tardive Dyskinesia/chemically induced , Male , Female , Tetrabenazine/analogs & derivatives , Tetrabenazine/pharmacology , Tetrabenazine/adverse effects , Tetrabenazine/administration & dosage , Middle Aged , Adult , Dopamine Antagonists/adverse effects , Dopamine Antagonists/administration & dosage , Dopamine Antagonists/pharmacology , Psychotic Disorders/drug therapy , Aged , Antipsychotic Agents/adverse effects , Antipsychotic Agents/administration & dosage , Schizophrenia/drug therapy , Treatment OutcomeABSTRACT
INTRODUCTION: Deutetrabenazine is a vesicular monoamine transporter 2 inhibitor used to treat tardive dyskinesia (TD) and chorea associated with Huntington disease (HD). To enhance detection of safety signals across individual trials, integrated safety analyses of deutetrabenazine in TD and HD chorea were conducted. METHODS: For TD, safety data were integrated from two 12-week pivotal studies (ARM-TD and AIM-TD) and through week 15 of the open-label extension (OLE) study (RIM-TD). Data were analyzed by deutetrabenazine treatment group and placebo. For HD, safety data were integrated from the 12-week pivotal study (First-HD) and through week 15 of the OLE study (ARC-HD) for patients previously receiving placebo. Integrated deutetrabenazine data were compared with placebo from the pivotal study. RESULTS: For TD, deutetrabenazine (n = 384) was generally well tolerated compared with placebo (n = 130). Adverse event (AE) incidence was numerically higher in the response-driven deutetrabenazine vs the fixed-dose deutetrabenazine and placebo groups, respectively (any AE, 59.5% vs 44.4-50.0% and 53.8%; treatment-related AE, 38.1% vs 18.1-25.0% and 30.8%). Serious AEs were reported for 2.8-8.3% of patients in the deutetrabenazine groups and 6.9% in the placebo group. Common AEs (≥ 4%) included headache, somnolence, nausea, anxiety, fatigue, dry mouth, and diarrhea. AE incidence was higher during the titration vs maintenance periods. For HD, AE incidence was numerically higher with deutetrabenazine (n = 84) vs placebo (n = 45; any AE, 64.3% vs 60.0%; treatment-related AE, 38.1% vs 26.7%); serious AEs were reported for similar proportions for the deutetrabenazine and placebo groups, 2.4% and 2.2%, respectively. Common AEs (≥ 4%) included irritability, fall, depression, dry mouth, and fatigue. CONCLUSIONS: Data from an integrated analysis of studies in TD and an integrated analysis of studies of chorea in HD showed that deutetrabenazine has a favorable safety profile and is well tolerated across indications. TRIAL REGISTRATION: ClinicalTrials.gov identifiers, NCT02291861, NCT02195700, NCT01795859, NCT02198794, NCT01897896.
Unintended movements are often the first sign of Huntington disease. This type of unintended movement is called chorea in Huntington disease. Tardive dyskinesia causes unintended body movements. Deutetrabenazine is a medicine used to treat both types of movements. This report summarizes deutetrabenazine safety across five clinical studies. Safety was assessed via adverse events (side effects). Adverse events were compared between deutetrabenazine and inactive treatment (placebo). Serious adverse events were also compared. Serious adverse events cause substantial impairment or disruption. In tardive dyskinesia and chorea in Huntington disease studies, most patients kept taking deutetrabenazine. Adverse events were not a common reason to stop treatment. For tardive dyskinesia, adverse event rates were similar between deutetrabenazine (≤ 60%) and placebo (54%). Serious adverse event rates were also similar for deutetrabenazine (≤ 8%) and placebo (7%). Adverse events tended to be reported earlier in treatment. Common adverse events were headache, sleepiness, nausea, anxiety, fatigue, dry mouth, and diarrhea. For chorea in Huntington disease, adverse event rates were similar for deutetrabenazine (64%) and placebo (60%). Serious adverse event rates were also similar for deutetrabenazine (2%) and placebo (2%). Irritability, fall, depression, dry mouth, and fatigue were common adverse events. Adverse events were similar between deutetrabenazine and placebo in both conditions. Deutetrabenazine was well tolerated for patients with either tardive dyskinesia or chorea in Huntington disease.
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Background: Tourette syndrome (TS) is a neurodevelopmental disorder characterized by motor and phonic tics. Objective: To assess the safety and efficacy of deutetrabenazine (Teva Neuroscience, Inc, Parsippany, NJ), a vesicular monoamine transporter 2 inhibitor, in children and adolescents with TS. Methods: Alternatives for Reducing Tics in TS (ARTISTS) open-label extension (OLE) (NCT03567291) was a 54-week, global, phase 3, open-label extension study of deutetrabenazine (6-48 mg daily) conducted May 28, 2018 to April 3, 2020 with a 2-week randomized withdrawal period. Participants (6-16 years of age) had TS and active tics causing distress or impairment. Safety (primary outcome) was assessed by treatment-emergent adverse events (TEAEs) and clinical laboratory testing. Efficacy was measured by the Yale Global Tic Severity Scale-Total Tic Score (YGTSS-TTS). Results: The intent-to-treat population (228 participants; mean age, 12.0 years; 79.8% male; 86.4% white) had a median (range) duration of exposure of 28.4 (0.3-52.9) weeks. Of 227 participants in the safety analysis, 161 (70.9%) reported ≥1 TEAE (exposure-adjusted incidence rate, 2.77/patient-year), of which 95 (41.9%) were treatment related. The most frequently reported TEAEs were headaches, somnolence, nasopharyngitis, weight increases, and anxiety. No additional safety signals were observed. Worsening of YGTSS-TTS after the 2-week randomized withdrawal was not statistically significant (least squares mean difference, -0.4; P = 0.78). Several exploratory measures showed sustained improvement throughout the treatment periods. Conclusions: In this long-term, open-label trial, deutetrabenazine was well tolerated with low frequency of TEAEs. There was no significant difference in tics between treatment arms during the 2-week randomized withdrawal period, however, descriptive statistics and comparison with baseline showed a numeric improvement in tics, quality of life, and other measures.
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INTRODUCTION: Device-aided therapy may improve the quality of life (QoL) for people with advanced Parkinson's disease (PD) and poorly controlled symptoms with oral therapy. MANAGE-PD is a validated tool classifying patients based on symptom control and advanced treatment eligibility. This study focused on patient/caregiver reported outcomes and healthcare resource utilization among patients grouped by MANAGE-PD categories. METHODS: Device-aided therapy-naïve patients receiving oral treatments were identified from the Adelphi Parkinson's Disease Programme. Patients were categorized (category 1 to 3) using MANAGE-PD. PD-specific QoL (PDQ-39), care partner burden (ZBI), satisfaction with current treatment, healthcare resource utilization, associated healthcare costs, and future treatment discussion with providers were measured. Categories were compared using ANOVA, t-test, chi square and adjusted regression analyses. RESULTS: Of the analytical sample (n = 2709), 18.9% were inadequately controlled on current therapy and potentially eligible for device-aided therapies (category 3). As expected, they had worse patient/caregiver reported outcomes versus patients in categories 1 or 2. However, the degree of difference in healthcare resource utilization, including: greater number of hospitalizations, emergency room (ER) visits and consultations, higher likelihood of being recipients of respite care, and greater PD treatment burden, was unexpected. Importantly, of patients in category 3 and their care partners, >40% did not report discussions with providers about device-aided therapies. CONCLUSION: MANAGE-PD category 3 patients had significantly higher burden on healthcare resources versus patients well-controlled with oral treatment or requiring only oral medication adjustments; yet almost half had no discussion on device-aided therapies with providers. Device-aided therapies may be considered in these patients.
Subject(s)
Parkinson Disease , Humans , Parkinson Disease/drug therapy , Quality of Life , Patient Acceptance of Health Care , Health Care Costs , CaregiversABSTRACT
This paper expands upon a session, entitled, "Special Challenges in Pediatric Drug Development," that was presented as part of a two-day meeting on Pediatric Drug Development at the International Society for Central Nervous System (CNS) Clinical Trials and Methodology (ISCTM) Autumn Conference in Boston, Massachusetts, in October 2020. Drug development in this age group is particularly important because many illnesses have their onset in this age group, many other illnesses that are more common in adults also occur in this time period, and many rare conditions that require special consideration (i.e., orphan conditions) are commonly detected in childhood as well. The special challenges addressed by our speakers in this session were cognitive and functional capacity assessment, challenges of recruitment and assessment of children for research and development of appropriate biomarkers for use in child populations, and the special challenges in training raters to address symptoms in pediatric populations. The speakers have written summaries of their talks. The session's lead chair was Philip D. Harvey, PhD, who wrote introductory and closing comments. This paper should serve as an expert-informed reference to those interested in and involved in addressing the special challenges facing those involved in CNS pediatric drug development.
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OBJECTIVE: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus interna (GPi) have differential therapeutic effects for Parkinson's disease (PD) that drive patient selection. For example, GPi DBS is preferred for dystonic features and dyskinesia, whereas STN DBS has shown faster tremor control and medication reduction. Connectivity studies comparing these two targets, using patient-specific data, are still lacking. The objective was to find STN and GPi structural connectivity patterns in order to better understand differences in DBS-activated brain circuits between these two stimulation targets and to guide optimal contact selection. METHODS: The authors simulated DBS activation along the main axis of both the STN and GPi by using volume of activated tissue (VAT) modeling with known average stimulation parameters (2.8 V and 60 µsec for STN; 3.3 V and 90 µsec for GPi). The authors modeled VATs in the anterior, middle, and posterior STN and the anterior, midanterior, midposterior, and posterior GPi. The authors generated maps of the connections shared by the patients for each VAT by using probabilistic tractography of diffusion-weighted imaging data obtained in 46 PD patients who underwent DBS (26 with STN and 20 with GPi targeting), and differences between VATs for whole-brain and distal regions of interest (prefrontal cortex, supplementary motor area, primary motor cortex, primary sensory cortex, caudate, motor thalamus, and cerebellum) were generated from structural atlases. Differences between maps were quantified and compared. RESULTS: VATs across the STN and GPi had different structural connectivity patterns. The authors found significant connectivity differences between VATs for all regions of interest. Posterior and middle STN showed stronger connectivity to the primary motor cortex and supplementary motor area (SMA) (p < 0.001). Posterior STN had the strongest connectivity to the primary sensory cortex and motor thalamus (p < 0.001). Posterior GPi showed stronger connectivity to the primary motor cortex (p < 0.001). Connectivity to the SMA was similar for the posterior and midposterior GPi (p > 0.05), which was greater than that for the anterior GPi (p < 0.001). When both nuclei were compared, posterior and middle STN had stronger connectivity to the SMA, cerebellum, and motor thalamus than GPi (all p < 0.001). Posterior GPi and STN had similar connectivity to the primary sensory cortex. CONCLUSIONS: On patient-specific imaging, structural connectivity differences existed between GPi and STN DBS, as measured with standardized electrical field modeling of the DBS targets. These connectivity differences may correlate with the differential clinical benefits obtained by targeting each of the two nuclei with DBS for PD. Prospective work is needed to relate these differences to clinical outcomes and to inform targeting and programming.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , White Matter , Humans , Subthalamic Nucleus/diagnostic imaging , Globus Pallidus/diagnostic imaging , Globus Pallidus/physiology , Deep Brain Stimulation/methods , Prospective Studies , Parkinson Disease/diagnostic imaging , Parkinson Disease/therapyABSTRACT
INTRODUCTION: Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD), but its efficacy is tied to DBS programming, which is often time consuming and burdensome for patients, caregivers, and clinicians. Our aim is to test whether the Mobile Application for PD DBS (MAP DBS), a clinical decision support system, can improve programming. METHODS: We conducted an open-label, 1:1 randomized, controlled, multicenter clinical trial comparing six months of SOC standard of care (SOC) to six months of MAP DBS-aided programming. We enrolled patients between 30 and 80 years old who received DBS to treat idiopathic PD at six expert centers across the United States. The primary outcome was time spent DBS programming and secondary outcomes measured changes in motor symptoms, caregiver strain and medication requirements. RESULTS: We found a significant reduction in initial visit time (SOC: 43.8 ± 28.9 min n = 37, MAP DBS: 27.4 ± 13.0 min n = 35, p = 0.001). We did not find a significant difference in total programming time between the groups over the 6-month study duration. MAP DBS-aided patients experienced a significantly larger reduction in UPDRS III on-medication scores (-7.0 ± 7.9) compared to SOC (-2.7 ± 6.9, p = 0.01) at six months. CONCLUSION: MAP DBS was well tolerated and improves key aspects of DBS programming time and clinical efficacy.
Subject(s)
Deep Brain Stimulation , Mobile Applications , Parkinson Disease , Subthalamic Nucleus , Humans , Adult , Middle Aged , Aged , Aged, 80 and over , Parkinson Disease/complications , Treatment OutcomeABSTRACT
Motor complications related to the chronic administration of levodopa and failure to prevent the neurodegenerative disease process counterbalance the pivotal discovery of levodopa as the cornerstone of PD treatment. Excellent motor control is offered early during the course of treatment, but this diminishes as pathological changes in the striatum lead to synaptic dopamine levels becoming completely dependent on exogenous dopamine. This non-physiologic stimulation of dopamine receptors eventually manifests as OFF episodes. As no disease modifying therapy exists for PD that can disrupt these pathological changes, most research and treatment focuses on optimization of dopaminergic stimulation of striatal receptors so that they mimic tonic, physiologic stimulation as closely as possible. Strategies focusing on these challenges have included non-pharmacologic approaches, optimizing levodopa pharmacokinetics, using adjunctive treatments including those with non-dopaminergic mechanisms, and implementing rescue therapies. Device aided therapies, including surgery, are also available. In this review, we will focus on effective management of motor symptoms related to OFF periods, including emerging strategies. Unmet clinical needs will be discussed, including non-motor symptoms, targeted molecular therapies and disease modifying therapy.
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Physical activity recognition in patients with Parkinson's Disease (PwPD) is challenging due to the lack of large-enough and good quality motion data for PwPD. A common approach to this obstacle involves the use of models trained on better quality data from healthy patients. Models can struggle to generalize across these domains due to motor complications affecting the movement patterns in PwPD and differences in sensor axes orientations between data. In this paper, we investigated the generalizability of a deep convolutional neural network (CNN) model trained on a young, healthy population to PD, and the role of data augmentation on alleviating sensor position variability. We used two publicly available healthy datasets - PAMAP2 and MHEALTH. Both datasets had sensor placements on the chest, wrist, and ankle with 9 and 10 subjects, respectively. A private PD dataset was utilized as well. The proposed CNN model was trained on PAMAP2 in k-fold cross-validation based on the number of subjects, with and without data augmentation, and tested directly on MHEALTH and PD data. Without data augmentation, the trained model resulted in 48.16% accuracy on MHEALTH and 0% on the PD data when directly applied with no model adaptation techniques. With data augmentation, the accuracies improved to 87.43% and 44.78%, respectively, indicating that the method compensated for the potential sensor placement variations between data. Clinical Relevance- Wearable sensors and machine learning can provide important information about the activity level of PwPD. This information can be used by the treating physician to make appropriate clinical interventions such as rehabilitation to improve quality of life.
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Parkinson Disease , Healthy Volunteers , Humans , Machine Learning , Neural Networks, Computer , Parkinson Disease/diagnosis , Quality of LifeABSTRACT
The collection of Parkinson's Disease (PD) time-series data usually results in imbalanced and incomplete datasets due to the geometric distribution of PD complications' sever-ity scores. Consequently, when training deep convolutional models on these datasets, the models suffer from overfitting and lack generalizability to unseen data. In this paper, we investigated a new framework of Conditional Generative Ad-versarial Netuwoks (cGANs) as a solution to improve the extrapolation and generalizability of the regression models in such datasets. We used a real-world PD dataset to esti-mate Dyskinesia severity in patients with PD. The developed cGAN demonstrated significantly better generalizability to unseen data samples than a traditional Convolutional Neural Network with an improvement of 34%. This solution can be applied in similar imbalanced time-series data, especially in the healthcare domain, where balanced and uniformly distributed data samples are not readily available.
Subject(s)
Deep Learning , Dyskinesias , Parkinson Disease , Humans , Neural Networks, Computer , Parkinson Disease/diagnosisABSTRACT
Although essential tremor is common, its underlying pathophysiology remains uncertain, and several hypotheses seek to explain the tremor mechanism. The GABA hypothesis states that disinhibition of deep cerebellar neurons due to reduced GABAergic input from Purkinje cells results in increased pacemaker activity, leading to rhythmic output to the thalamo-cortical circuit and resulting in tremor. However, some neuroimaging, spectroscopy, and pathology studies have not shown a clear or consistent GABA deficiency in essential tremor, and animal models have indicated that large reductions of Purkinje cell inhibition may improve tremor. Instead, tremor is increasingly attributable to dysfunction in oscillating networks, where altered (but not necessarily reduced) inhibitory signaling can result in tremor. Hypersynchrony of Purkinje cell activity may account for excessive oscillatory cerebellar output, with potential contributions along multiple sites of the olivocerebellar loop. Although older animal tremor models, such as harmaline tremor, have explored contributions from the inferior olivary body, increasing evidence has pointed to the role of aberrant climbing fiber synaptic organization in oscillatory cerebellar activity and tremor generation. New animal models such as hotfoot17j mice, which exhibit abnormal climbing fiber organization due to mutations in Grid2, have recapitulated many features of ET. Similar abnormal climbing fiber architecture and excessive cerebellar oscillations as measured by EEG have been found in humans with essential tremor. Further understanding of hypersynchrony and excessive oscillatory activity in ET phenotypes may lead to more targeted and effective treatment options.
Subject(s)
Essential Tremor , Animals , Cerebellum/pathology , Humans , Mice , Olivary Nucleus/pathology , Olivary Nucleus/physiology , Purkinje Cells/pathology , Purkinje Cells/physiology , Tremor , gamma-Aminobutyric AcidABSTRACT
Background: Deutetrabenazine is a vesicular monoamine transporter 2 inhibitor approved for the treatment of tardive dyskinesia (TD) in adults. In two 12-week pivotal studies, deutetrabenazine demonstrated statistically significant improvements in Abnormal Involuntary Movement Scale (AIMS) scores, with favorable safety/tolerability in TD patients. This study reports long-term efficacy and safety of deutetrabenazine in a 3-year, single-arm, open-label extension (OLE) study. Methods: Patients who completed the pivotal studies could enroll in this single-arm OLE study, titrating up to 48 mg/day based on dyskinesia control and tolerability. Efficacy was assessed based on change from baseline in total motor AIMS score, Clinical Global Impression of Change (CGIC) and Patient Global Impression of Change (PGIC), and quality of life (QOL) assessments. Safety evaluation included adverse event (AE) incidence, reported using exposure-adjusted incidence rates, and safety scales. Results: 343 patients enrolled in the study (6 patients were excluded). At Week 145 (mean dose: 39.4 ± 0.83 mg/day), mean ± SE change from baseline in total motor AIMS score was -6.6 ± 0.37 and 67% of patients achieved ≥50% improvement in total motor AIMS score. Based on CGIC and PGIC, 73% and 63% of patients achieved treatment success, respectively. QOL improvements were also observed. Deutetrabenazine was generally well tolerated, with low rates of mild-to-moderate AEs and no new safety signals; most safety scales remained unchanged over time. Conclusions: Long-term deutetrabenazine treatment was associated with sustained improvement in AIMS scores, indicative of clinically meaningful long-term benefit, and was generally well tolerated. Results suggest deutetrabenazine may provide increasing benefit over time without increases in dose.
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BACKGROUND: Patient groups traditionally affected by health disparities were less likely to use video teleneurology (TN) care during the initial COVID-19 pandemic surge in the United States. Whether this asymmetry persisted later in the pandemic or was accompanied with a loss of access to care remains unknown. METHODS: We conducted a retrospective cohort study using patient data from a multicenter healthcare system in New York City. We identified all established pediatric or adult neurology patients with at least two prior outpatient visits between June 16th, 2019 and March 15th, 2020 using our electronic medical record. For this established pre-COVID cohort, we identified telephone, in-person, video TN or emergency department visits and hospital admissions for any cause between March 16th and December 15th, 2020 ("COVID period"). We determined clinical, sociodemographic, income, and visit characteristics. Our primary outcome was video TN utilization, and our main secondary outcome was loss to follow-up during the COVID period. We used multivariable logistic regression to model the relationship between patient-level characteristics and both outcomes. RESULTS: We identified 23,714 unique visits during the COVID period, which corresponded to 14,170 established patients from our institutional Neurology clinics during the pre-COVID period. In our cohort, 4,944 (34.9%) utilized TN and 4,997 (35.3%) were entirely lost to follow-up during the COVID period. In the adjusted regression analysis, Black or African-American race [adjusted odds ratio (aOR) 0.60, 97.5%CI 0.52-0.70], non-English preferred language (aOR 0.49, 97.5%CI 0.39-0.61), Medicaid insurance (aOR 0.50, 97.5%CI 0.44-0.57), and Medicare insurance (aOR 0.73, 97.5%CI 0.65-0.83) had decreased odds of TN utilization. Older age (aOR 0.98, 97.5%CI 0.98-0.99), female sex (aOR 0.90 97.5%CI 0.83-0.99), and Medicaid insurance (aOR 0.78, 0.68-0.90) were associated with decreased odds of loss to follow-up. CONCLUSION: In the first 9 months of the COVID-19 pandemic, we found sociodemographic patterns in TN utilization that were similar to those found very early in the pandemic. However, these sociodemographic characteristics were not associated with loss to follow-up, suggesting that lack of TN utilization may not have coincided with loss of access to care.
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BACKGROUND: The burden of Parkinson's disease (PD) worsens with disease progression. However, the lack of objective and uniform disease classification challenges our understanding of the incremental burden in patients with advanced Parkinson's disease (APD) and suboptimal medication control. The 5-2-1 criteria was proposed by clinical consensus to identify patients with advancing PD. Our objective was to evaluate the screening accuracy and incremental clinical burden, healthcare resource utilization (HCRU), and humanistic burden in PD patients meeting the 5-2-1 screening criteria. METHODS: Data were drawn from the Adelphi Parkinson's Disease Specific Program (DSP™), a multi-country point-in-time survey (2017-2020). People with PD who were naive to device-aided therapy and on oral PD therapy were included. Patients meeting the 5-2-1 screening criteria had one or more of the three clinical indicators of APD: (i) ≥5 doses of oral levodopa/day, OR (ii) "off" symptoms for ≥2 h of waking day, OR (iii) ≥1 h of troublesome dyskinesia. Clinician assessment of PD stage was used as the reference in this study. Clinical screening accuracy of the 5-2-1 criteria was assessed using area under the curve and multivariable logistic regression models. Incremental clinical, HCRU, and humanistic burden were assessed by known-group comparisons between 5 and 2-1-positive and negative patients. RESULTS: From the analytic sample (n = 4714), 33% of patients met the 5-2-1 screening criteria. Among physician-classified APD patients, 78.6% were 5-2-1 positive. Concordance between clinician judgment and 5-2-1 screening criteria was > 75%. 5-2-1-positive patients were nearly 7-times more likely to be classified as APD by physician judgment. Compared with the 5-2-1-negative group, 5-2-1-positive patients had significantly higher clinical, HCRU, and humanistic burden across all measures. In particular, 5-2-1-positive patients had 3.8-times more falls, 3.6-times higher annual hospitalization rate, and 3.4-times greater dissatisfaction with PD treatment. 5-2-1-positive patients also had significantly lower quality of life and worse caregiver burden. CONCLUSIONS: 5-2-1 criteria demonstrated potential as a screening tool for identifying people with APD with considerable clinical, humanistic, and HCRU burden. The 5-2-1 screening criteria is an objective and reliable tool that may aid the timely identification and treatment optimization of patients inadequately controlled on oral PD medications.
Subject(s)
Parkinson Disease , Humans , Levodopa/therapeutic use , Parkinson Disease/diagnosis , Parkinson Disease/drug therapy , Patient Acceptance of Health Care , Quality of Life , Surveys and QuestionnairesABSTRACT
OBJECTIVE: Published reports on directional deep brain stimulation (DBS) have been limited to small, single-center investigations. Therapeutic window (TW) is used to describe the range of stimulation amplitudes achieving symptom relief without side effects. This crossover study performed a randomized double-blind assessment of TW for directional and omnidirectional DBS in a large cohort of patients implanted with a DBS system in the subthalamic nucleus for Parkinson's disease. MATERIALS AND METHODS: Participants received omnidirectional stimulation for the first three months after initial study programming, followed by directional DBS for the following three months. The primary endpoint was a double-blind, randomized evaluation of TW for directional vs omnidirectional stimulation at three months after initial study programming. Additional data recorded at three- and six-month follow-ups included stimulation preference, therapeutic current strength, Unified Parkinson's Disease Rating Scale (UPDRS) part III motor score, and quality of life. RESULTS: The study enrolled 234 subjects (62 ± 8 years, 33% female). TW was wider using directional stimulation in 183 of 202 subjects (90.6%). The mean increase in TW with directional stimulation was 41% (2.98 ± 1.38 mA, compared to 2.11 ± 1.33 mA for omnidirectional). UPDRS part III motor score on medication improved 42.4% at three months (after three months of omnidirectional stimulation) and 43.3% at six months (after three months of directional stimulation) with stimulation on, compared to stimulation off. After six months, 52.8% of subjects blinded to stimulation type (102/193) preferred the period with directional stimulation, and 25.9% (50/193) preferred the omnidirectional period. The directional period was preferred by 58.5% of clinicians (113/193) vs 21.2% (41/193) who preferred the omnidirectional period. CONCLUSION: Directional stimulation yielded a wider TW compared to omnidirectional stimulation and was preferred by blinded subjects and clinicians.