Patient diaries as a clinical endpoint in Parkinson's disease clinical trials

Mobile Health Daily Life Monitoring for Parkinson Disease: Development and Validation of Ecological Momentary Assessments

BACKGROUND

Parkinson disease monitoring is currently transitioning from periodic clinical assessments to continuous daily life monitoring in free-living conditions. Traditional Parkinson disease monitoring methods lack intraday fluctuation detection. Electronic diaries (eDiaries) hold the potential to collect subjective experiences on the severity and burden of motor and nonmotor symptoms in free-living conditions.

OBJECTIVE

This study aimed to develop a Parkinson disease-specific eDiary based on ecological momentary assessments (EMAs) and to explore its validation.

METHODS

An observational cohort of 20 patients with Parkinson disease used the smartphone-based EMA eDiary for 14 consecutive days without adjusting free-living routines. The eDiary app presented an identical questionnaire consisting of questions regarding affect, context, motor and nonmotor symptoms, and motor performance 7 times daily at semirandomized moments. In addition, patients were asked to complete a morning and an evening questionnaire.

RESULTS

Mean affect correlated moderate-to-strong and moderate with motor performance (R=0.38 to 0.75; P<.001) and motor symptom (R=0.34 to 0.50; P<.001) items, respectively. The motor performance showed a weak-to-moderate negative correlation with motor symptoms (R=-0.31 to -0.48; P<.001). Mean group answers given for on-medication conditions vs wearing-off-medication conditions differed significantly (P<.05); however, not enough questionnaires were completed for the wearing-off-medication condition to reproduce these findings on individual levels.

CONCLUSIONS

We presented a Parkinson disease-specific EMA eDiary. Correlations between given answers support the internal validity of the eDiary and underline EMA's potential in free-living Parkinson disease monitoring. Careful patient selection and EMA design adjustment to this targeted population and their fluctuations are necessary to generate robust proof of EMA validation in future work. Combining clinical Parkinson disease knowledge with practical EMA experience is inevitable to design and perform studies, which will lead to the successful integration of eDiaries in free-living Parkinson disease monitoring.

Objective measurement in Parkinson's disease: a descriptive analysis of Parkinson's symptom scores from a large population of patients across the world using the Personal KinetiGraph®

Background

The Personal KinetiGraph® (PKG®) Movement Recording System provides continuous, objective, ambulatory movement data during routine daily activities and provides information on medication compliance, motor fluctuations, immobility, and tremor for patients with Parkinson’s disease (PD). Recent evidence has proposed targets for treatable symptoms. Indications for PKG vary by country and patient selection varies by physician.

Methods

The analyses were based upon 27,834 complete and de-identified PKGs from January 2012 to August 2018 used globally for routine clinical care. Median scores for bradykinesia (BKS) and dyskinesia (DKS) as well as percent time with tremor (PTT) and percent time immobile (PTI) were included as well as proportions of PKGs above published PKG summary score target values (BKS > 25, DKS > 9, PTT > 1%, PTI > 10%). Two sub-analyses included subjects who had 2+ PKG records and scores above proposed BKS and DKS targets, respectively, on their first PKG. Median BKS and DKS scores for subsequent PKGs (1st, 2nd, etc.) were summarized and limited to those with 100+ subsequent PKGs for each data point.

Results

Significant differences between countries were found for all 4 PKG parameter median scores (all p < 0.0001). Overall, 54% of BKS scores were > 25 and ranged from 46 to 61% by country. 10% of all DKS scores were > 9 and ranged from 5 to 15% by country. Sub-analysis for BKS showed global median BKS and DKS scores across subsequent PKGs for subjects who had 2+ PKGs and had BKS > 25 on their first PKG. There were significant changes in BKS from 1st to 2nd-6th PKGs (all p < 0.0001). Sub-analysis for DKS showed global median BKS & DKS scores across subsequent PKGs for subjects who had 2+ PKGs and had DKS > 9 on their first PKG. There were significant changes in DKS from 1st to 2nd and 3rd PKGs (both p < 0.0001).

Conclusions

This analysis shows that in every country evaluated a meaningful proportion of patients have sub-optimal PD motor symptoms and substantial variations exist across countries. Continuous objective measurement (COM) in routine care of PD enables identification and quantification of PD motor symptoms, which can be used to enhance clinical decision making, track symptoms over time and improve PD symptom scores. Thus, clinicians can use these PKG scores during routine clinical management to identify PD symptoms and work to move patients into a target range or a more controlled symptom state.

Effectiveness and safety of opicapone in Parkinson's disease patients with motor fluctuations: the OPTIPARK open-label study

BACKGROUND

The efficacy and safety of opicapone, a once-daily catechol-O-methyltransferase inhibitor, have been established in two large randomized, placebo-controlled, multinational pivotal trials. Still, clinical evidence from routine practice is needed to complement the data from the pivotal trials.

METHODS

OPTIPARK (NCT02847442) was a prospective, open-label, single-arm trial conducted in Germany and the UK under clinical practice conditions. Patients with Parkinson's disease and motor fluctuations were treated with opicapone 50 mg for 3 (Germany) or 6 (UK) months in addition to their current levodopa and other antiparkinsonian treatments. The primary endpoint was the Clinician's Global Impression of Change (CGI-C) after 3 months. Secondary assessments included Patient Global Impressions of Change (PGI-C), the Unified Parkinson's Disease Rating Scale (UPDRS), Parkinson's Disease Questionnaire (PDQ-8), and the Non-Motor Symptoms Scale (NMSS). Safety assessments included evaluation of treatment-emergent adverse events (TEAEs) and serious adverse events (SAEs).

RESULTS

Of the 506 patients enrolled, 495 (97.8%) took at least one dose of opicapone. Of these, 393 (79.4%) patients completed 3 months of treatment. Overall, 71.3 and 76.9% of patients experienced any improvement on CGI-C and PGI-C after 3 months, respectively (full analysis set). At 6 months, for UK subgroup only (n = 95), 85.3% of patients were judged by investigators as improved since commencing treatment. UPDRS scores at 3 months showed statistically significant improvements in activities of daily living during OFF (mean ± SD change from baseline: - 3.0 ± 4.6, p < 0.0001) and motor scores during ON (- 4.6 ± 8.1, p < 0.0001). The mean ± SD improvements of - 3.4 ± 12.8 points for PDQ-8 and -6.8 ± 19.7 points for NMSS were statistically significant versus baseline (both p < 0.0001). Most of TEAEs (94.8% of events) were of mild or moderate intensity. TEAEs considered to be at least possibly related to opicapone were reported for 45.1% of patients, with dyskinesia (11.5%) and dry mouth (6.5%) being the most frequently reported. Serious TEAEs considered at least possibly related to opicapone were reported for 1.4% of patients.

CONCLUSIONS

Opicapone 50 mg was effective and generally well-tolerated in PD patients with motor fluctuations treated in clinical practice.

TRIAL REGISTRATION

Registered in July 2016 at clinicaltrials.gov (NCT02847442).

mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's disease

Accurately monitoring motor and non-motor symptoms as well as complications in people with Parkinson's disease (PD) is a major challenge, both during clinical management and when conducting clinical trials investigating new treatments. A variety of strategies have been relied upon including questionnaires, motor diaries, and the serial administration of structured clinical exams like part III of the MDS-UPDRS. To evaluate the potential use of mobile and wearable technologies in clinical trials of new pharmacotherapies targeting PD symptoms, we carried out a project (project BlueSky) encompassing four clinical studies, in which 60 healthy volunteers (aged 23-69; 33 females) and 95 people with PD (aged 42-80; 37 females; years since diagnosis 1-24 years; Hoehn and Yahr 1-3) participated and were monitored in either a laboratory environment, a simulated apartment, or at home and in the community. In this paper, we investigated (i) the utility and reliability of self-reports for describing motor fluctuations; (ii) the agreement between participants and clinical raters on the presence of motor complications; (iii) the ability of video raters to accurately assess motor symptoms, and (iv) the dynamics of tremor, dyskinesia, and bradykinesia as they evolve over the medication cycle. Future papers will explore methods for estimating symptom severity based on sensor data. We found that 38% of participants who were asked to complete an electronic motor diary at home missed ~25% of total possible entries and otherwise made entries with an average delay of >4 h. During clinical evaluations by PD specialists, self-reports of dyskinesia were marked by ~35% false negatives and 15% false positives. Compared with live evaluation, the video evaluation of part III of the MDS-UPDRS significantly underestimated the subtle features of tremor and extremity bradykinesia, suggesting that these aspects of the disease may be underappreciated during remote assessments. On the other hand, live and video raters agreed on aspects of postural instability and gait. Our results highlight the significant opportunity for objective, high-resolution, continuous monitoring afforded by wearable technology to improve upon the monitoring of PD symptoms.

Development of digital biomarkers for resting tremor and bradykinesia using a wrist-worn wearable device

Objective assessment of Parkinson's disease symptoms during daily life can help improve disease management and accelerate the development of new therapies. However, many current approaches require the use of multiple devices, or performance of prescribed motor activities, which makes them ill-suited for free-living conditions. Furthermore, there is a lack of open methods that have demonstrated both criterion and discriminative validity for continuous objective assessment of motor symptoms in this population. Hence, there is a need for systems that can reduce patient burden by using a minimal sensor setup while continuously capturing clinically meaningful measures of motor symptom severity under free-living conditions. We propose a method that sequentially processes epochs of raw sensor data from a single wrist-worn accelerometer by using heuristic and machine learning models in a hierarchical framework to provide continuous monitoring of tremor and bradykinesia. Results show that sensor derived continuous measures of resting tremor and bradykinesia achieve good to strong agreement with clinical assessment of symptom severity and are able to discriminate between treatment-related changes in motor states.

Long-Term Home-Monitoring Sensor Technology in Patients with Parkinson's Disease-Acceptance and Adherence

Parkinson’s disease (PD) is characterized by a highly individual disease-profile as well as fluctuating symptoms. Consequently, 24-h home monitoring in a real-world environment would be an ideal solution for precise symptom diagnostics. In recent years, small lightweight sensors which have assisted in objective, reliable analysis of motor symptoms have attracted a lot of attention. While technical advances are important, patient acceptance of such new systems is just as crucial to increase long-term adherence. So far, there has been a lack of long-term evaluations of PD-patient sensor adherence and acceptance. In a pilot study of PD patients (N = 4), adherence (wearing time) and acceptance (questionnaires) of a multi-part sensor set was evaluated over a 4-week timespan. The evaluated sensor set consisted of 3 body-worn sensors and 7 at-home installed ambient sensors. After one month of continuous monitoring, the overall system usability scale (SUS)-questionnaire score was 71.5%, with an average acceptance score of 87% for the body-worn sensors and 100% for the ambient sensors. On average, sensors were worn 15 h and 4 min per day. All patients reported strong preferences of the sensor set over manual self-reporting methods. Our results coincide with measured high adherence and acceptance rate of similar short-term studies and extend them to long-term monitoring.

Are There Benefits in Adding Catechol-O Methyltransferase Inhibitors in the Pharmacotherapy of Parkinson's Disease Patients? A Systematic Review

BACKGROUND

A qualified consensus suggests that a combination of levodopa with a peripherally acting dopa decarboxylase inhibitor continues to present the gold standard treatment of Parkinson's disease (PD). However, as the disease progresses the therapeutic window of levodopa becomes narrowed. Pharmacological strategies for motor fluctuations are focused on providing less pulsatile and more continuous dopaminergic stimulation. Peripheral catechol-O-methyltransferase (COMT) inhibition improves the bioavailability of levodopa and results in a prolonged response.

OBJECTIVE

The primary aim of this study was to investigate the efficacy and safety of the two available COMT inhibitors; entacapone and tolcapone and the recently introduced opicapone.

METHODS

Electronic databases were systematically searched for original studies published within the last 37 years. In addition, lists of identified studies, reviews and their references were examined.

RESULTS

Twelve studies fulfilled the inclusion criteria. 3701 patients with PD were included in this systematic review.

CONCLUSIONS

Adjuvant treatment of PD patients experiencing motor fluctuations with entacapone resulted in improvement of motor function and was well tolerated. Therefore, entacapone presented an acceptable benefit to risk ratio. Tolcapone appeared to result in a greater therapeutic effect. However, this was not consistent across all motor variables and studies, and thus would not support its use, given the current onerous monitoring that is required. Opicapone was not associated with adverse reactions in a phase III trial but did not present a greater efficacy than entacapone, and thus further studies are required in order to illustrate its cost effectiveness.

Multilevel Features for Sensor-Based Assessment of Motor Fluctuation in Parkinson's Disease Subjects

Motor fluctuations are a frequent complication in patients with Parkinson's disease (PD) where the response to medication fluctuates between ON states (medication working) and OFF states (medication has worn off). This paper describes a new data analysis approach that can be used along with two wearable IMU (inertial measurement units) sensors to continuously assess motor fluctuations in PD patients while moving in their natural environment. We hypothesized that joint analysis of the sensor data in its spectral, temporal and sensor domain could generate multilevel features that can be used to detect PD-related patterns successfully as the subject's motor state fluctuates between medication ON and OFF states. For this purpose, we utilized time-frequency (TF) representation and multiway data analysis tools (i.e., tensor decomposition) to decompose the TF representation of the two sensors' data into its multilevel structures, which were next used to extract multilevel features representing the PD symptoms in different medication states. The extracted multilevel features were used in a classification model based on support vector machine to detect medication ON and OFF states. For comparison purposes, we implemented a traditional feature extraction method. We also developed a hierarchical feature extraction method based on the combination of those two methods. The performances of the three methods were evaluated using a dataset of 19 PD subjects with a total duration of 17.54 hours. The multilevel features achieved 8.25% improvement in the accuracy over the traditional features, and the hierarchical features resulted in 10.73% improvement indicating that our approach holds great promise to continuously detect medication states from continuous monitoring of the subjects' movement. Such information can be used by the treating physician to tailor the adjustments to each subject's unique impairment(s), thereby improving therapeutic decision-making and patient outcomes.

Estimating dyskinesia severity in Parkinson's disease by using a waist-worn sensor: concurrent validity study

Our research team previously developed an accelerometry-based device, which can be worn on the waist during daily life activities and detects the occurrence of dyskinesia in patients with Parkinson’s disease. The goal of this study was to analyze the magnitude of correlation between the numeric output of the device algorithm and the results of the Unified Dyskinesia Rating Scale (UDysRS), administered by a physician. In this study, 13 Parkinson’s patients, who were symptomatic with dyskinesias, were monitored with the device at home, for an average period of 30 minutes, while performing normal daily life activities. Each patient’s activity was simultaneously video-recorded. A physician was in charge of reviewing the recorded videos and determining the severity of dyskinesia through the UDysRS for every patient. The sensor device yielded only one value for dyskinesia severity, which was calculated by averaging the recorded device readings. Correlation between the results of physician’s assessment and the sensor output was analyzed with the Spearman’s correlation coefficient. The correlation coefficient between the sensor output and UDysRS result was 0.70 (CI 95%: 0.33–0.88; p = 0.01). Since the sensor was located on the waist, the correlation between the sensor output and the results of the trunk and legs scale sub-items was calculated: 0.91 (CI 95% 0.76–0.97: p < 0.001). The conclusion is that the magnitude of dyskinesia, as measured by the tested device, presented good correlation with that observed by a physician.

Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience

Objective

Dosing schedules for oral levodopa in advanced stages of Parkinson’s disease (PD) require careful tailoring to fit the needs of each patient. This study proposes a dosing algorithm for oral administration of levodopa and evaluates its integration into a sensor-based dosing system (SBDS).

Materials and methods

In collaboration with two movement disorder experts a knowledge-driven, simulation based algorithm was designed and integrated into a SBDS. The SBDS uses data from wearable sensors to fit individual patient models, which are then used as input to the dosing algorithm. To access the feasibility of using the SBDS in clinical practice its performance was evaluated during a clinical experiment where dosing optimization of oral levodopa was explored. The supervising neurologist made dosing adjustments based on data from the Parkinson’s KinetiGraph™ (PKG) that the patients wore for a week in a free living setting. The dosing suggestions of the SBDS were compared with the PKG-guided adjustments.

Results

The SBDS maintenance and morning dosing suggestions had a Pearson’s correlation of 0.80 and 0.95 (with mean relative errors of 21% and 12.5%), to the PKG-guided dosing adjustments. Paired t test indicated no statistical differences between the algorithmic suggestions and the clinician’s adjustments.

Conclusion

This study shows that it is possible to use algorithmic sensor-based dosing adjustments to optimize treatment with oral medication for PD patients.

Viewpoint: Developing drugs for levodopa-induced dyskinesia in PD: Lessons learnt, what does the future hold?

The drive to develop drugs to treat PD starts and ends with the patient. Herein, we discuss how the experience with drug development for LID has led the field in translational studies in PD with advancing ground-breaking science via rigorous clinical trial design, to deliver clinical proof-of-concepts across multiple therapeutic targets. However, issues remain in advancing drugs efficacious preclinically to the clinic, and future studies need to learn from past successes and failures. Such lessons include implementing better early indicators of tolerability, for instance evaluating non-motor symptoms in preclinical models; improving patient-related outcome measures in clinical trials, as well as considering the unique nature of dyskinesia in an individual patient. The field of translational studies needs to become more patient focused to improve successful outcomes.

Viewpoint and practical recommendations from a movement disorder specialist panel on objective measurement in the clinical management of Parkinson's disease

Motor aspects of Parkinson's disease, such as fluctuations and dyskinesia, can be reliably evaluated using a variety of "wearable" technologies, but practical guidance on objective measurement (OM) and the optimum use of these devices is lacking. Therefore, as a first step, a panel of movement disorder specialists met to provide guidance on how OM could be assessed and incorporated into clinical guidelines. A key aspect of the incorporation of OM into the management of Parkinson's disease (PD) is defining cutoff values that separate "controlled" from "uncontrolled" symptoms that can be modified by therapy and that relate to an outcome that is relevant to the person with PD (such as quality of life). Defining cutoffs by consensus, which can be subsequently tested and refined, is the first step to optimizing OM in the management of PD. OM should be used by all clinicians that treat people with PD but the least experienced may find the most value, but this requires guidance from experts to allow non-experts to apply guidelines. While evidence is gained for devices that produce OM, expert opinion is needed to supplement the evidence base.

A Kinematic Sensor and Algorithm to Detect Motor Fluctuations in Parkinson Disease: Validation Study Under Real Conditions of Use

BACKGROUND

A new algorithm has been developed, which combines information on gait bradykinesia and dyskinesia provided by a single kinematic sensor located on the waist of Parkinson disease (PD) patients to detect motor fluctuations (On- and Off-periods).

OBJECTIVE

The goal of this study was to analyze the accuracy of this algorithm under real conditions of use.

METHODS

This validation study of a motor-fluctuation detection algorithm was conducted on a sample of 23 patients with advanced PD. Patients were asked to wear the kinematic sensor for 1 to 3 days at home, while simultaneously keeping a diary of their On- and Off-periods. During this testing, researchers were not present, and patients continued to carry on their usual daily activities in their natural environment. The algorithm's outputs were compared with the patients' records, which were used as the gold standard.

RESULTS

The algorithm produced 37% more results than the patients' records (671 vs 489). The positive predictive value of the algorithm to detect Off-periods, as compared with the patients' records, was 92% (95% CI 87.33%-97.3%) and the negative predictive value was 94% (95% CI 90.71%-97.1%); the overall classification accuracy was 92.20%.

CONCLUSIONS

The kinematic sensor and the algorithm for detection of motor-fluctuations validated in this study are an accurate and useful tool for monitoring PD patients with difficult-to-control motor fluctuations in the outpatient setting.

Objective measurement in routine care of people with Parkinson's disease improves outcomes

It is common in medicine to titrate therapy according to target ranges of objectively measured parameters. Objective measurement of motor function is available for Parkinson's Disease (PD), making it possible to optimise therapy and clinical outcomes. In this study, an accelerometry based measurement and predefined target ranges were used to assess motor function in a Northern Tasmania PD cohort managed by a Movement Disorder clinic. Approximately 40% (n = 103) of the total PD population participated in this study and motor scores were within target in 22%. In the 78% above target, changes in oral therapy were recommended in 74%, Advanced Therapy in 12% and treatment was contraindicated in 9%. Following changes in oral therapy, there was a further objective measurement and clinical consultation to establish whether scores had reached target range: if so subjects left the study, otherwise further changes of therapy were recommended (unless contraindications were present). Seventy-seven cases completed the study, with 48% achieving target (including 22% at outset), Advanced Therapy recommended in 19% and contraindications preventing any change in therapy in 17%. In the 43% of cases in whom oral therapy was changed, total UPDRS improved significantly (effect size = 8) as did the PDQ39 in cases reaching target. NMS Quest and MOCA scores also improved significantly. This study shows that many people in a representative cohort of PD would benefit from objective assessment and treatment of their PD features against a target.

Wearables in epilepsy and Parkinson's disease-A focus group study

OBJECTIVES

Wearable sensors that measure movement and physiological variables are attractive for clinical evaluation of neurological diseases such as epilepsy and Parkinson's disease (PD). The aim of this study was to explore perceptions regarding the use of wearable technology in disease monitoring and management as reported by individuals with epilepsy and Parkinson's disease as well as health professionals working with these patient groups.

MATERIALS AND METHODS

Six patient groups (n=25) and two groups with health professionals (n=15) participated in this qualitative, descriptive study with focus group interviews. A manifest qualitative content analysis was used.

RESULTS

Four categories and nine subcategories emerged from the analysis. Participants saw possible benefits for improved treatment effect and valued this benefit more than possible inconvenience of wearing the sensors. Discrete design and simplicity were considered as facilitators for improved usability. They emphasized the importance of interactive information between patients and health professionals. However, they were concerned about unclear information and inconclusive recordings and some fears about personal integrity were at odds with the expectations on interactivity.

CONCLUSIONS

Patients need to feel well informed and find an added value in using wearables. Wearables need to be user-friendly, have an attractive design, and show clinical efficacy in improving disease management. Variations in perceptions regarding integrity, benefits, and effectiveness of monitoring indicate possible conflicts of expectations among participants. The engagement of end users, patients, and health professionals, in the design and implementation process, is crucial for the development of wearable devices that enhance and facilitate neurological rehabilitation practice.

Individualization of levodopa treatment using a microtablet dispenser and ambulatory accelerometry

AIM

This 4-week open-label observational study describes the effect of introducing a microtablet dose dispenser and adjusting doses based on objective free-living motor symptom monitoring in individuals with Parkinson's disease (PD).

METHODS

Twenty-eight outpatients with PD on stable levodopa treatment with dose intervals of ≤4 hour had their daytime doses of levodopa replaced with levodopa/carbidopa microtablets, 5/1.25 mg (LC-5) delivered from a dose dispenser device with programmable reminders. After 2 weeks, doses were adjusted based on ambulatory accelerometry and clinical monitoring.

RESULTS

Twenty-four participants completed the study per protocol. The daily levodopa dose was increased by 15% (112 mg, P < 0.001) from period 1 to 2, and the dose interval was reduced by 12% (22 minutes, P = 0.003). The treatment adherence to LC-5 was high in both periods. The MDS-UPDRS parts II and III, disease-specific quality of life (PDQ-8), wearing-off symptoms (WOQ-19), and nonmotor symptoms (NMS Quest) improved after dose titration, but the generic quality-of-life measure EQ-5D-5L did not. Blinded expert evaluation of accelerometry results demonstrated improvement in 60% of subjects and worsening in 25%.

CONCLUSIONS

The introduction of a levodopa microtablet dispenser and accelerometry aided dose adjustments improve PD symptoms and quality of life in the short term.

A "HOLTER" for Parkinson's disease: Validation of the ability to detect on-off states using the REMPARK system

The treatment of Parkinson's disease (PD) with levodopa is very effective. However, over time, motor complications (MCs) appear, restricting the patient from leading a normal life. One of the most disabling MCs is ON-OFF fluctuations. Gathering accurate information about the clinical status of the patient is essential for planning treatment and assessing its effect. Systems such as the REMPARK system, capable of accurately and reliably monitoring ON-OFF fluctuations, are of great interest.

OBJECTIVE

To analyze the ability of the REMPARK System to detect ON-OFF fluctuations.

METHODS

Forty-one patients with moderate to severe idiopathic PD were recruited according to the UK Parkinson's Disease Society Brain Bank criteria. Patients with motor fluctuations, freezing of gait and/or dyskinesia and who were able to walk unassisted in the OFF phase, were included in the study. Patients wore the REMPARK System for 3days and completed a diary of their motor state once every hour.

RESULTS

The record obtained by the REMPARK System, compared with patient-completed diaries, demonstrated 97% sensitivity in detecting OFF states and 88% specificity (i.e., accuracy in detecting ON states).

CONCLUSION

The REMPARK System detects an accurate evaluation of ON-OFF fluctuations in PD; this technology paves the way for an optimisation of the symptomatic control of PD motor symptoms as well as an accurate assessment of medication efficacy.

Analysis of Correlation between an Accelerometer-Based Algorithm for Detecting Parkinsonian Gait and UPDRS Subscales

Background

Our group earlier developed a small monitoring device, which uses accelerometer measurements to accurately detect motor fluctuations in patients with Parkinson’s (On and Off state) based on an algorithm that characterizes gait through the frequency content of strides. To further validate the algorithm, we studied the correlation of its outputs with the motor section of the Unified Parkinson’s Disease Rating Scale part-III (UPDRS-III).

Method

Seventy-five patients suffering from Parkinson’s disease were asked to walk both in the Off and the On state while wearing the inertial sensor on the waist. Additionally, all patients were administered the motor section of the UPDRS in both motor phases. Tests were conducted at the patient’s home. Convergence between the algorithm and the scale was evaluated by using the Spearman’s correlation coefficient.

Results

Correlation with the UPDRS-III was moderate (rho −0.56; p < 0.001). Correlation between the algorithm outputs and the gait item in the UPDRS-III was good (rho −0.73; p < 0.001). The factorial analysis of the UPDRS-III has repeatedly shown that several of its items can be clustered under the so-called Factor 1: “axial function, balance, and gait.” The correlation between the algorithm outputs and this factor of the UPDRS-III was −0.67 (p < 0.01).

Conclusion

The correlation achieved by the algorithm with the UPDRS-III scale suggests that this algorithm might be a useful tool for monitoring patients with Parkinson’s disease and motor fluctuations.

Continuous Assessment of Levodopa Response in Parkinson's Disease Using Wearable Motion Sensors

OBJECTIVE

Fluctuations in response to levodopa in Parkinson's disease (PD) are difficult to treat as tools to monitor temporal patterns of symptoms are hampered by several challenges. The objective was to use wearable sensors to quantify the dose response of tremor, bradykinesia, and dyskinesia in individuals with PD.

METHODS

Thirteen individuals with PD and fluctuating motor benefit were instrumented with wrist and ankle motion sensors and recorded by video. Kinematic data were recorded as subjects completed a series of activities in a simulated home environment through transition from off to on medication. Subjects were evaluated using the unified Parkinson disease rating scale motor exam (UPDRS-III) at the start and end of data collection. Algorithms were applied to the kinematic data to score tremor, bradykinesia, and dyskinesia. A blinded clinician rated severity observed on video. Accuracy of algorithms was evaluated by comparing scores with clinician ratings using a receiver operating characteristic (ROC) analysis.

RESULTS

Algorithm scores for tremor, bradykinesia, and dyskinesia agreed with clinician ratings of video recordings (ROC area > 0.8). Summary metrics extracted from time intervals before and after taking medication provided quantitative measures of therapeutic response (p < 0.01). Radar charts provided intuitive visualization, with graphical features correlated with UPDRS-III scores (R = 0.81).

CONCLUSION

A system with wrist and ankle motion sensors can provide accurate measures of tremor, bradykinesia, and dyskinesia as patients complete routine activities.

SIGNIFICANCE

This technology could provide insight on motor fluctuations in the context of daily life to guide clinical management and aid in development of new therapies.

Drug-Induced Dyskinesia, Part 1: Treatment of Levodopa-Induced Dyskinesia

Dyskinesias encompass a variety of different hyperkinetic phenomenologies, particularly chorea, dystonia, stereotypies, and akathisia. Levodopa-induced dyskinesia (LID) is one of the main types of drug-induced dyskinesia, occurring in patients with Parkinson's disease (PD) who have been treated with levodopa for long time, but this side effect may be encountered even within a few weeks or months after initiation of levodopa therapy. Based on the temporal pattern in relationship to levodopa dosing, LIDs are divided into "peak-dose dyskinesia," "diphasic dyskinesia," and "wearing off" or "off-period" dyskinesia, of which peak-dose dyskinesia is the most common, followed by off-period, and then diphasic dyskinesia. Treatment strategy includes identifying the kind of dyskinesia and tailoring treatment accordingly. Peak-dose dyskinesia is treated mainly by reducing individual doses of levodopa and adding amantadine and dopamine agonists, whereas off-period dystonia often responds to baclofen and botulinum toxin injections. Diphasic dyskinesias, occurring particularly in patients with young-onset PD, are the most difficult to treat. While fractionation of levodopa dosage is the most frequently utilized strategy, many patients require deep brain stimulation to control their troublesome motor fluctuations and LIDs. A variety of emerging (experimental) drugs currently in development promise to provide better control of LIDs and other levodopa-related complications in the near future.

Clinical Assessments in Parkinson's Disease: Scales and Monitoring

Measurement of disease state is essential in both clinical practice and research in order to assess the severity and progression of a patient's disease status, effect of treatment, and alterations in other relevant factors. Parkinson's disease (PD) is a complex disorder expressed through many motor and nonmotor manifestations, which cause disabilities that can vary both gradually over time or come on suddenly. In addition, there is a wide interpatient variability making the appraisal of the many facets of this disease difficult. Two kinds of measure are used for the evaluation of PD. The first is subjective, inferential, based on rater-based interview and examination or patient self-assessment, and consist of rating scales and questionnaires. These evaluations provide estimations of conceptual, nonobservable factors (e.g., symptoms), usually scored on an ordinal scale. The second type of measure is objective, factual, based on technology-based devices capturing physical characteristics of the pathological phenomena (e.g., sensors to measure the frequency and amplitude of tremor). These instrumental evaluations furnish appraisals with real numbers on an interval scale for which a unit exists. In both categories of measures, a broad variety of tools exist. This chapter aims to present an up-to-date summary of the most relevant characteristics of the most widely used scales, questionnaires, and technological resources currently applied to the assessment of PD. The review concludes that, in our opinion: (1) no assessment methods can substitute the clinical judgment and (2) subjective and objective measures in PD complement each other, each method having strengths and weaknesses.

Home detection of freezing of gait using support vector machines through a single waist-worn triaxial accelerometer

Among Parkinson’s disease (PD) symptoms, freezing of gait (FoG) is one of the most debilitating. To assess FoG, current clinical practice mostly employs repeated evaluations over weeks and months based on questionnaires, which may not accurately map the severity of this symptom. The use of a non-invasive system to monitor the activities of daily living (ADL) and the PD symptoms experienced by patients throughout the day could provide a more accurate and objective evaluation of FoG in order to better understand the evolution of the disease and allow for a more informed decision-making process in making adjustments to the patient’s treatment plan. This paper presents a new algorithm to detect FoG with a machine learning approach based on Support Vector Machines (SVM) and a single tri-axial accelerometer worn at the waist. The method is evaluated through the acceleration signals in an outpatient setting gathered from 21 PD patients at their home and evaluated under two different conditions: first, a generic model is tested by using a leave-one-out approach and, second, a personalised model that also uses part of the dataset from each patient. Results show a significant improvement in the accuracy of the personalised model compared to the generic model, showing enhancement in the specificity and sensitivity geometric mean (GM) of 7.2%. Furthermore, the SVM approach adopted has been compared to the most comprehensive FoG detection method currently in use (referred to as MBFA in this paper). Results of our novel generic method provide an enhancement of 11.2% in the GM compared to the MBFA generic model and, in the case of the personalised model, a 10% of improvement with respect to the MBFA personalised model. Thus, our results show that a machine learning approach can be used to monitor FoG during the daily life of PD patients and, furthermore, personalised models for FoG detection can be used to improve monitoring accuracy.

Association of Helicobacter pylori with Parkinson's Disease

Background and Purpose

Parkinson's disease (PD) is a major neurological disorder that requires lifelong treatment, and the combined presence of Helicobacter pylori (H. pylori) infection can increase the required anti-PD medications. We aim to investigate the effect of H. pylori infection in Indian PD patients.

Methods

We prospectively recruited 36 PD patients from December 2007 to January 2011. All patients underwent a detailed neurological evaluation and serological examination for H. pylori infection. Seropositive and seronegative patients were considered to be the cases and controls, respectively. All patients who were seropositive received triple therapy for 2 weeks. Outcome measures of the mean ‘off’ Unified Parkinson's Disease Rating Scale (UPDRS)-III score, mean ‘on’ UPDRS-III score, mean onset time, mean ‘on’ duration, and mean daily ‘on’ time were measured at baseline and at a 3-week follow-up.

Results

H. pylori-IgG positivity was present in 18 (50%) PD patients. The prevalence of men (72.2% vs. 33.3%), mean duration of disease (13.8 vs. 12.5) and mean levodopa equivalent daily dose (824 mg vs. 707 mg) were significantly higher among H. pylori positive patients than in controls (p<0.0001). Controls had a significantly longer ‘on’ duration and daily ‘on’ time, and better ‘on’ UPDRS-III scores. Seropositive patients took a significantly longer time to turn ‘on’ after a levodopa challenge. At the 3-week follow-up, H. pylori eradication significantly improved the mean ‘on’ UPDRS-III score, onset time, ‘on’ duration, and daily ‘on’ time.

Conclusions

H. pylori infection was present in 50% of Indian PD patients. H. pylori seropositivity was associated with a poor response to levodopa and increased medication usage, while eradication therapy was associated with better patient outcomes.

Assessing Motor Fluctuations in Parkinson's Disease Patients Based on a Single Inertial Sensor

Altered movement control is typically the first noticeable symptom manifested by Parkinson's disease (PD) patients. Once under treatment, the effect of the medication is very patent and patients often recover correct movement control over several hours. Nonetheless, as the disease advances, patients present motor complications. Obtaining precise information on the long-term evolution of these motor complications and their short-term fluctuations is crucial to provide optimal therapy to PD patients and to properly measure the outcome of clinical trials. This paper presents an algorithm based on the accelerometer signals provided by a waist sensor that has been validated in the automatic assessment of patient's motor fluctuations (ON and OFF motor states) during their activities of daily living. A total of 15 patients have participated in the experiments in ambulatory conditions during 1 to 3 days. The state recognised by the algorithm and the motor state annotated by patients in standard diaries are contrasted. Results show that the average specificity and sensitivity are higher than 90%, while their values are higher than 80% of all patients, thereby showing that PD motor status is able to be monitored through a single sensor during daily life of patients in a precise and objective way.

Correlation of Quantitative Motor State Assessment Using a Kinetograph and Patient Diaries in Advanced PD: Data from an Observational Study

Introduction

Effective management and development of new treatment strategies for response fluctuations in advanced Parkinson’s disease (PD) largely depends on clinical rating instruments such as the PD home diary. The Parkinson’s kinetigraph (PKG) measures movement accelerations and analyzes the spectral power of the low frequencies of the accelerometer data. New algorithms convert each hour of continuous PKG data into one of the three motor categories used in the PD home diary, namely motor Off state and On state with and without dyskinesia.

Objective

To compare quantitative motor state assessment in fluctuating PD patients using the PKG with motor state ratings from PD home diaries.

Methods

Observational cohort study on 24 in-patients with documented motor fluctuations who completed diaries by rating motor Off, On without dyskinesia, On with dyskinesia, and asleep for every hour for 5 consecutive days. Simultaneously collected PKG data (recorded between 6 am and 10 pm) were analyzed and calibrated to the patient’s individual thresholds for Off and dyskinetic state by novel algorithms classifying the continuous accelerometer data into these motor states for every hour between 6 am and 10 pm.

Results

From a total of 2,040 hours, 1,752 hours (87.4%) were available for analyses from calibrated PKG data (7.5% sleeping time and 5.1% unclassified motor state time were excluded from analyses). Distributions of total motor state hours per day measured by PKG showed moderate-to-strong correlation to those assessed by diaries for the different motor states (Pearson’s correlations coefficients: 0.404–0.658), but inter-rating method agreements on the single-hour-level were only low-to-moderate (Cohen’s κ: 0.215–0.324).

Conclusion

The PKG has been shown to capture motor fluctuations in patients with advanced PD. The limited correlation of hour-to-hour diary and PKG recordings should be addressed in further studies.

A clinical view on the development of technology-based tools in managing Parkinson's disease

Recently, quantitative, objective, and easy-to-use technology-based tools that can assess PD features over long time periods have been developed and generate clinically relevant and comparable patient information. Herein, we present a clinician's view on technological developments that have the potential to revolutionize clinical management concepts in PD. According to prominent examples in clinical medicine (e.g., blood glycosylated hemoglobin and blood pressure), we argue that the consideration of technology-based assessment in the clinical management of PD must be based on specific assumptions: (1) It provides a valid and accurate parameter of a clinically relevant feature of the disease; (2) there is confirmed evidence that the parameter has an ecologically relevant effect on the specific clinical application; (3) a target range can be defined wherein the parameter reflects the adequate treatment response; and (4) implementation is simple to allow repetitive use. Currently, there are no technology-based tools available that fulfil all these assumptions; however, assessments of akinesia, dyskinesia, motor fluctuations, physical inactivity, gait impairment, and postural instability seem relatively close to the specifications described. An iterative process of integration is recommended to bring technology-based tools into clinical practice. © 2016 International Parkinson and Movement Disorder Society.

Medication Therapy Management Service for Patients with Parkinson's Disease: A Before-and-After Study

Background

Parkinson’s disease (PD) is a neurodegenerative disease characterized by motor manifestations, autonomic and neurological disorders and sensorial symptoms. Medication therapy management (MTM) consists of a service undertaken by pharmacists to optimize pharmacological therapy results. This way, the pharmacist monitors the treatment prescribed by the doctor and formulates a healthcare plan to guarantee the treatment’s effectiveness, safety and convenience, thereby improving the patient’s quality of life (QoL).

Objective

To analyze the effect of MTM upon medicine-related problems, motor symptoms, autonomic disorders and QoL of patients with Parkinson’s disease, and describe the pharmaceutical interventions.

Methods

Quasi-experimental uncontrolled before-and-after study carried out between September 2012 and March 2013 in a community pharmacy. Pharmacotherapy data were collected from medical prescriptions, patient diaries, medical charts and all the medicines (over-the-counter and prescription) brought by the patients to the appointment with the pharmacist. The medicine-related problems were classified as indication, effectiveness, safety and adherence. Adherence was measured through clinical interviews and the Morisky questionnaire. PD symptoms were assessed according to the patients’ and/or caregivers’ perceptions about the On/Off state of the motor symptoms and relief of the nonmotor symptoms. QoL was assessed using the PDQ-39 scores. The interventions were targeted to patients/caregivers and/or doctors, with pharmacological and non-pharmacological measures.

Results

Seventy patients were followed up, showing a decrease in medicine-related problems (1.67 ± 1.34 to 0.8 ± 0.9 (p < 0.001), positive impact on adherence (from 37 to 10 non-adherent patients, p < 0.001), QoL improvement related to emotional wellbeing (p = 0.012) and autonomic disorder. Most interventions were performed directly with the patients (73.8%), including non-pharmacological guidance (28.5%), pharmacological guidance (24.3%) and rescheduling (13.6%).

Conclusions

To carry out MTM with PD patients, the pharmacist’s expertise needs to transcend the technical knowledge about the PD pharmacological treatment. The study showed a positive effect with a decrease in the medicine-related problems after the interventions, especially improving adherence and patients’ QoL.

An objective fluctuation score for Parkinson's disease

Introduction

Establishing the presence and severity of fluctuations is important in managing Parkinson’s Disease yet there is no reliable, objective means of doing this. In this study we have evaluated a Fluctuation Score derived from variations in dyskinesia and bradykinesia scores produced by an accelerometry based system.

Methods

The Fluctuation Score was produced by summing the interquartile range of bradykinesia scores and dyskinesia scores produced every 2 minutes between 0900-1800 for at least 6 days by the accelerometry based system and expressing it as an algorithm.

Results

This Score could distinguish between fluctuating and non-fluctuating patients with high sensitivity and selectivity and was significant lower following activation of deep brain stimulators. The scores following deep brain stimulation lay in a band just above the score separating fluctuators from non-fluctuators, suggesting a range representing adequate motor control. When compared with control subjects the score of newly diagnosed patients show a loss of fluctuation with onset of PD. The score was calculated in subjects whose duration of disease was known and this showed that newly diagnosed patients soon develop higher scores which either fall under or within the range representing adequate motor control or instead go on to develop more severe fluctuations.

Conclusion

The Fluctuation Score described here promises to be a useful tool for identifying patients whose fluctuations are progressing and may require therapeutic changes. It also shows promise as a useful research tool. Further studies are required to more accurately identify therapeutic targets and ranges.

Validation of a portable device for mapping motor and gait disturbances in Parkinson's disease

BACKGROUND

Patients with severe idiopathic Parkinson's disease experience motor fluctuations, which are often difficult to control. Accurate mapping of such motor fluctuations could help improve patients' treatment.

OBJECTIVE

The objective of the study was to focus on developing and validating an automatic detector of motor fluctuations. The device is small, wearable, and detects the motor phase while the patients walk in their daily activities.

METHODS

Algorithms for detection of motor fluctuations were developed on the basis of experimental data from 20 patients who were asked to wear the detector while performing different daily life activities, both in controlled (laboratory) and noncontrolled environments. Patients with motor fluctuations completed the experimental protocol twice: (1) once in the ON, and (2) once in the OFF phase. The validity of the algorithms was tested on 15 different patients who were asked to wear the detector for several hours while performing daily activities in their habitual environments. In order to assess the validity of detector measurements, the results of the algorithms were compared with data collected by trained observers who were accompanying the patients all the time.

RESULTS

The motor fluctuation detector showed a mean sensitivity of 0.96 (median 1; interquartile range, IQR, 0.93-1) and specificity of 0.94 (median 0.96; IQR, 0.90-1).

CONCLUSIONS

ON/OFF motor fluctuations in Parkinson's patients can be detected with a single sensor, which can be worn in everyday life.

Clinician versus machine: reliability and responsiveness of motor endpoints in Parkinson's disease

BACKGROUND

Enhancing the reliability and responsiveness of motor assessments required to demonstrate therapeutic efficacy is a priority for Parkinson's disease (PD) clinical trials. The objective of this study is to determine the reliability and responsiveness of a portable kinematic system for quantifying PD motor deficits as compared to clinical ratings.

METHODS

Eighteen PD patients with subthalamic nucleus deep-brain stimulation (DBS) performed three tasks for evaluating resting tremor, postural tremor, and finger-tapping speed, amplitude, and rhythm while wearing a wireless motion-sensor unit (Kinesia) on the more-affected index finger. These tasks were repeated three times with DBS turned off and at each of 10 different stimulation amplitudes chosen to yield small changes in treatment response. Each task performance was video-recorded for subsequent clinician rating in blinded, randomized order. Test-retest reliability was calculated as intraclass correlation (ICC) and sensitivity was calculated as minimal detectable change (MDC) for each DBS amplitude.

RESULTS

ICCs for Kinesia were significantly higher than those for clinician ratings of finger-tapping speed (p < 0.0001), amplitude (p < 0.0001), and rhythm (p < 0.05), but were not significantly different for evaluations of resting or postural tremor. Similarly, Kinesia scores yielded a lower MDC as compared with clinician scores across all finger-tapping subscores (p < 0.0001), but did not differ significantly for resting and postural tremor.

CONCLUSIONS

The Kinesia portable kinematic system can provide greater test-retest reliability and sensitivity to change than conventional clinical ratings for measuring bradykinesia, hypokinesia, and dysrhythmia in PD patients.

Carbidopa/levodopa dose elevation and safety concerns in Parkinson's patients: a cross-sectional and cohort design

OBJECTIVE

Sinemet, a combination drug containing carbidopa and levodopa is considered the gold standard therapy for the treatment of Parkinson's disease (PD). When approved by the Food and Drug Administration (FDA) in 1988, a maximum daily dosage limit of 800 mg (eight tablets) of the 25/100 carbidopa/levodopa formulation was introduced. Overall, the FDA approval was a historic success; however, the pill limit has been hardcoded into many online medical record systems. This study investigates the 800 mg threshold by using a prospectively collected database of patient information.

DESIGN

A retrospective cohort study: (Part I) cross-sectional, (Part II) longitudinal.

SETTING AND PARTICIPANTS

PD patients at a Movement Disorders Center in a large academic, tertiary medical setting.

OUTCOME MEASURES

An analysis was performed using carbidopa/levodopa at dosages below and above the 800 mg threshold. A secondary analysis was then performed using two consecutive clinic visits to determine the effects of crossing the 800 mg threshold. Comparisons were made on standardised scales.

RESULTS

There was no significant difference in motor, mood and quality-of-life scores in patients consuming below and above the 800 mg carbidopa/levodopa threshold, though a mild worsening in dyskinesia duration was noted without worsening in dyskinesia pain and disability. In PD patients who crossed the 800 mg threshold between two consecutive clinic visits, a significant improvement in depressive symptoms and quality-of-life measures was demonstrated, and in these patients there was no worsening of motor fluctuations or dyskinesia.

CONCLUSIONS

The data suggest that PD patients have the potential for enhanced clinical benefits when eclipsing the 800 mg carbidopa/levodopa threshold. Many patients will likely need to eclipse the 800 mg threshold and pharmacies and insurance companies should be aware of the requirements that may extend beyond approval limits.