The effect of continuous levodopa treatment during the afternoon hours.

OBJECTIVE: The aim of this retrospective study was to investigate whether patients with Parkinson's disease, who are treated with levodopa-carbidopa intestinal gel (LCIG), clinically worsen during the afternoon hours and if so, to evaluate whether this occurs in all LCIG-treated patients or in a subgroup of patients. METHODS: Three published studies were identified and included in the analysis. All studies provided individual response data assessed on the treatment response scale (TRS), and patients were treated with continuous LCIG. Ninety-eight patients from the three studies fulfilled the criteria. t tests were performed to find differences on the TRS values between the morning and the afternoon hours, linear mixed effect models were fitted on the afternoon hours' evaluations to find trends of wearing-off, and patients were classified into three TRS categories (meaningful increase in TRS, meaningful decrease in TRS, non-meaningful increase or decrease). RESULTS: In all three studies, significant statistical differences were found between the morning TRS values and the afternoon TRS values (P-value <=0.001 in all studies). The linear mixed effect models had significant negative coefficients for time in two studies, and 48 out of 98 patients (49%) showed a meaningful decrease in TRS during the afternoon hours. CONCLUSION: The results from all studies were consistent, both in the proportion of patients in the three groups and in the value of TRS decrease in the afternoon hours. Based on these findings, there seems to be a group of patients with predictable "off" behavior in the later parts of the day.

Profiling Online Poker Players: Are Executive Functions Correlated with Poker Ability and Problem Gambling?

Poker playing and responsible gambling both entail the use of the executive functions (EF), which are higher-level cognitive abilities. This study investigated if online poker players of different ability showed different performances in their EF and if so, which functions were the most discriminating for their playing ability. Furthermore, it assessed if the EF performance was correlated to the quality of gambling, according to self-reported questionnaires (PGSI, SOGS, GRCS). Three poker experts evaluated anonymized poker hand history files and, then, a trained professional administered an extensive neuropsychological test battery. Data analysis determined which variables of the tests correlated with poker ability and gambling quality scores. The highest correlations between EF test results and poker ability and between EF test results and gambling quality assessment showed that mostly different clusters of executive functions characterize the profile of the strong(er) poker player and those ones of the problem gamblers (PGSI and SOGS) and the one of the cognitions related to gambling (GRCS). Taking into consideration only the variables overlapping between PGSI and SOGS, we found some key predictive factors for a more risky and harmful online poker playing: a lower performance in the emotional intelligence competences (Emotional Quotient inventory Short) and, in particular, those grouped in the Intrapersonal scale (emotional self-awareness, assertiveness, self-regard, independence and self-actualization).

Levodopa/carbidopa microtablets in Parkinson's disease: a study of pharmacokinetics and blinded motor assessment.

BACKGROUND: Motor function assessments with rating scales in relation to the pharmacokinetics of levodopa may increase the understanding of how to individualize and fine-tune treatments. OBJECTIVES: This study aimed to investigate the pharmacokinetic profiles of levodopa-carbidopa and the motor function following a single-dose microtablet administration in Parkinson's disease. METHODS: This was a single-center, open-label, single-dose study in 19 patients experiencing motor fluctuations. Patients received 150% of their individual levodopa equivalent morning dose in levodopa-carbidopa microtablets. Blood samples were collected at pre-specified time points. Patients were video recorded and motor function was assessed with six UPDRS part III motor items, dyskinesia score, and the treatment response scale (TRS), rated by three blinded movement disorder specialists. RESULTS: AUC0-4/dose and C max/dose for levodopa was found to be higher in Parkinson's disease patients compared with healthy subjects from a previous study, (p = 0.0008 and p = 0.026, respectively). The mean time to maximum improvement in sum of six UPDRS items score was 78 min (±59) (n = 16), and the mean time to TRS score maximum effect was 54 min (±51) (n = 15). Mean time to onset of dyskinesia was 41 min (±38) (n = 13). CONCLUSIONS: In the PD population, following levodopa/carbidopa microtablet administration in fasting state, the Cmax and AUC0-4/dose were found to be higher compared with results from a previous study in young, healthy subjects. A large between subject variability in response and duration of effect was observed, highlighting the importance of a continuous and individual assessment of motor function in order to optimize treatment effect.

Verification of a Method for Measuring Parkinson's Disease Related Temporal Irregularity in Spiral Drawings.

Parkinson's disease (PD) is a progressive movement disorder caused by the death of dopamine-producing cells in the midbrain. There is a need for frequent symptom assessment, since the treatment needs to be individualized as the disease progresses. The aim of this paper was to verify and further investigate the clinimetric properties of an entropy-based method for measuring PD-related upper limb temporal irregularities during spiral drawing tasks. More specifically, properties of a temporal irregularity score (TIS) for patients at different stages of PD, and medication time points were investigated. Nineteen PD patients and 22 healthy controls performed repeated spiral drawing tasks on a smartphone. Patients performed the tests before a single levodopa dose and at specific time intervals after the dose was given. Three movement disorder specialists rated videos of the patients based on the unified PD rating scale (UPDRS) and the Dyskinesia scale. Differences in mean TIS between the groups of patients and healthy subjects were assessed. Test-retest reliability of the TIS was measured. The ability of TIS to detect changes from baseline (before medication) to later time points was investigated. Correlations between TIS and clinical rating scores were assessed. The mean TIS was significantly different between healthy subjects and patients in advanced groups (p-value = 0.02). Test-retest reliability of TIS was good with Intra-class Correlation Coefficient of 0.81. When assessing changes in relation to treatment, TIS contained some information to capture changes from Off to On and wearing off effects. However, the correlations between TIS and clinical scores (UPDRS and Dyskinesia) were weak. TIS was able to differentiate spiral drawings drawn by patients in an advanced stage from those drawn by healthy subjects, and TIS had good test-retest reliability. TIS was somewhat responsive to single-dose levodopa treatment. Since TIS is an upper limb high-frequency-based measure, it cannot be detected during clinical assessment.

Automatic and objective assessment of alternating tapping performance in Parkinson's disease.

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson's disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions ('speed', 'accuracy', 'fatigue' and 'arrhythmia') and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson's Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

Validation of a home environment test battery for supporting assessments in advanced Parkinson's disease.

Test sequences in a test battery for Parkinson's disease patients, consisting of self-assessments and motor tests, were carried out repeatedly in a telemedicine setting, during week-long test periods and results were summarized in an 'overall score'. 35 patients in stable and fluctuating conditions (15 age- and gender-matched pairs) used the test battery for 1 week, and were then assessed with UPDRS and PDQ-39. This procedure was repeated 1 week later, without treatment changes. Reliability was assessed by intraclass correlation coefficients and Cronbach's alpha. Convergent validity was assessed by Spearman rank correlations and known-groups' validity, by the Mann-Whitney test. According to anonymous usability questionnaires, the patients could easily complete the tasks. Median compliance (93%) and test-retest reliability (0.88) were good. The correlations between overall score and total UPDRS (-0.64) and PDQ-39 (-0.72) were adequate. Median overall score was 18% better in the stable compared to the fluctuating group (p = 0.0014).

Investigating Stochastic Differential Equations Modelling for Levodopa Infusion in Patients with Parkinson's Disease.

BACKGROUND AND OBJECTIVES: Levodopa concentration in patients with Parkinson's disease is frequently modelled with ordinary differential equations (ODEs). Here, we investigate a pharmacokinetic model of plasma levodopa concentration in patients with Parkinson's disease by introducing stochasticity to separate the intra-individual variability into measurement and system noise, and to account for auto-correlated errors. We also investigate whether the induced stochasticity provides a better fit than the ODE approach. METHODS: In this study, a system noise variable is added to the pharmacokinetic model for duodenal levodopa/carbidopa gel (LCIG) infusion described by three ODEs through a standard Wiener process, leading to a stochastic differential equations (SDE) model. The R package population stochastic modelling (PSM) was used for model fitting with data from previous studies for modelling plasma levodopa concentration and parameter estimation. First, the diffusion scale parameter (σw), measurement noise variance, and bioavailability are estimated with the SDE model. Second, σw is fixed to certain values from 0 to 1 and bioavailability is estimated. Cross-validation was performed to compare the average root mean square errors (RMSE) of predicted plasma levodopa concentration. RESULTS: Both the ODE and the SDE models estimated bioavailability to be approximately 75%. The SDE model converged at different values of σw that were significantly different from zero. The average RMSE for the ODE model was 0.313, and the lowest average RMSE for the SDE model was 0.297 when σw was fixed to 0.9, and these two values are significantly different. CONCLUSIONS: The SDE model provided a better fit for LCIG plasma levodopa concentration by approximately 5.5% in terms of mean percentage change of RMSE.

A multiple motion sensors index for motor state quantification in Parkinson's disease.

AIM: To construct a Treatment Response Index from Multiple Sensors (TRIMS) for quantification of motor state in patients with Parkinson's disease (PD) during a single levodopa dose. Another aim was to compare TRIMS to sensor indexes derived from individual motor tasks. METHOD: Nineteen PD patients performed three motor tests including leg agility, pronation-supination movement of hands, and walking in a clinic while wearing inertial measurement unit sensors on their wrists and ankles. They performed the tests repeatedly before and after taking 150% of their individual oral levodopa-carbidopa equivalent morning dose.Three neurologists blinded to treatment status, viewed patients' videos and rated their motor symptoms, dyskinesia, overall motor state based on selected items of Unified PD Rating Scale (UPDRS) part III, Dyskinesia scale, and Treatment Response Scale (TRS). To build TRIMS, out of initially 178 extracted features from upper- and lower-limbs data, 39 features were selected by stepwise regression method and were used as input to support vector machines to be mapped to mean reference TRS scores using 10-fold cross-validation method. Test-retest reliability, responsiveness to medication, and correlation to TRS as well as other UPDRS items were evaluated for TRIMS. RESULTS: The correlation of TRIMS with TRS was 0.93. TRIMS had good test-retest reliability (ICC = 0.83). Responsiveness of the TRIMS to medication was good compared to TRS indicating its power in capturing the treatment effects. TRIMS was highly correlated to dyskinesia (R = 0.85), bradykinesia (R = 0.84) and gait (R = 0.79) UPDRS items. Correlation of sensor index from the upper-limb to TRS was 0.89. CONCLUSION: Using the fusion of upper- and lower-limbs sensor data to construct TRIMS provided accurate PD motor states estimation and responsive to treatment. In addition, quantification of upper-limb sensor data during walking test provided strong results.

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.

Evaluation of a sensor algorithm for motor state rating in Parkinson's disease.

INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkinson's disease (PD) and its usefulness for constructing individual dose-response models. METHODS: Twenty-five patients with PD performed a series of tasks throughout a levodopa challenge while wearing sensors. TRIS was used to determine motor changes in pronation-supination tests following a single levodopa dose, and was compared to clinical ratings including the Treatment Response Scale (TRS) and six sub-items of the UPDRS part III. RESULTS: As expected, correlations between TRIS and clinical ratings were lower in the new population than in the initial study. TRIS was still significantly correlated to TRS (rs = 0.23, P < 0.001) with a root mean square error (RMSE) of 1.33. For the patients (n = 17) with a good levodopa response and clear motor fluctuations, a stronger correlation was found (rs = 0.38, RMSE = 1.29, P < 0.001). The mean TRIS increased significantly when patients went from the practically defined off to their best on state (P = 0.024). Individual dose-response models could be fitted for more participants when TRIS was used for modelling than when TRS ratings were used. CONCLUSION: The objective sensor index shows promise for constructing individual dose-response models, but further evaluations and retraining of the TRIS algorithm are desirable to improve its performance and to ensure its clinical effectiveness.

Individual dose-response models for levodopa infusion dose optimization.

BACKGROUND AND OBJECTIVE: To achieve optimal effect with continuous infusion treatment in Parkinson's disease (PD), the individual doses (morning dose and continuous infusion rate) are titrated by trained medical personnel. This study describes an algorithmic method to derive optimized dosing suggestions for infusion treatment of PD, by fitting individual dose-response models. The feasibility of the proposed method was investigated using patient chart data. METHODS: Patient records were collected at Uppsala University hospital which provided dosing information and dose-response evaluations. Mathematical optimization was used to fit individual patient models using the records' information, by minimizing an objective function. The individual models were passed to a dose optimization algorithm, which derived an optimized dosing suggestion for each patient model. RESULTS: Using data from a single day's admission the algorithm showed great ability to fit appropriate individual patient models and derive optimized doses. The infusion rate dosing suggestions had 0.88 correlation and 10% absolute mean relative error compared to the optimal doses as determined by the hospital's treating team. The morning dose suggestions were consistency lower that the optimal morning doses, which could be attributed to different dosing strategies and/or lack of on-off evaluations in the morning. CONCLUSION: The proposed method showed promise and could be applied in clinical practice, to provide the hospital personnel with additional information when making dose adjustment decisions.

A Treatment-Response Index From Wearable Sensors for Quantifying Parkinson's Disease Motor States.

The goal of this study was to develop an algorithm that automatically quantifies motor states (off, on, dyskinesia) in Parkinson's disease (PD), based on accelerometry during a hand pronation-supination test. Clinician's ratings using the Treatment Response Scale (TRS), ranging from -3 (very Off) to 0 (On) to +3 (very dyskinetic), were used as target. For that purpose, 19 participants with advanced PD and 22 healthy persons were recruited in a single center open label clinical trial in Uppsala, Sweden. The trial consisted of single levodopa dose experiments for the people with PD (PwP), where participants were asked to perform standardized wrist rotation tests, using each hand, before and at prespecified time points after the dose. The participants used wrist sensors containing a three-dimensional accelerometer and gyroscope. Features to quantify the level, variation, and asymmetry of the sensor signals, three-level discrete wavelet transform features, and approximate entropy measures were extracted from the sensors data. At the time of the tests, the PwP were video recorded. Three movement disorder specialists rated the participants' state on the TRS. A Treatment Response Index from Sensors (TRIS) was constructed to quantify the motor states based on the wrist rotation tests. Different machine learning algorithms were evaluated to map the features derived from the sensor data to the ratings provided by the three specialists. Results from cross validation, both in tenfold and a leave-one-individual out setting, showed good predictive power of a support vector machine model and high correlation to the TRS. Values at the end tails of the TRS were under and over predicted due to the lack of observations at those values but the model managed to accurately capture the dose-effect profiles of the patients. In addition, the TRIS had good test-retest reliability on the baseline levels of the PD participants (Intraclass correlation coefficient of 0.83) and reasonable sensitivity to levodopa treatment (0.33 for the TRIS). For a series of test occasions, the proposed algorithms provided dose-effect time profiles for participants with PD, which could be useful during therapy individualization of people suffering from advanced PD.

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.

Validity and Responsiveness of At-Home Touch Screen Assessments in Advanced Parkinson's Disease.

The aim of this study was to investigate if a telemetry test battery can be used to measure effects of Parkinson's disease (PD) treatment intervention and disease progression in patients with fluctuations. Sixty-five patients diagnosed with advanced PD were recruited in an open longitudinal 36-month study; 35 treated with levodopa-carbidopa intestinal gel (LCIG) and 30 were candidates for switching from oral PD treatment to LCIG. They utilized a test battery, consisting of self-assessments of symptoms and fine motor tests (tapping and spiral drawings), four times per day in their homes during week-long test periods. The repeated measurements were summarized into an overall test score (OTS) to represent the global condition of the patient during a test period. Clinical assessments included ratings on unified PD rating scale (UPDRS) and 39-item PD questionnaire (PDQ-39) scales. In LCIG-naïve patients, the mean OTS compared to baseline was significantly improved from the first test period on LCIG treatment until month 24. In LCIG-nonnaïve patients, there were no significant changes in the mean OTS until month 36. The OTS correlated adequately with total UPDRS (rho = 0.59) and total PDQ-39 (0.59). Responsiveness measured as effect size was 0.696 and 0.536 for OTS and UPDRS, respectively. The trends of the test scores were similar to the trends of clinical rating scores but the dropout rate was high. Correlations between OTS and clinical rating scales were adequate indicating that the test battery contains important elements of the information of well-established scales. The responsiveness and reproducibility were better for OTS than for total UPDRS.

A computer vision framework for finger-tapping evaluation in Parkinson's disease.

OBJECTIVES: The rapid finger-tapping test (RFT) is an important method for clinical evaluation of movement disorders, including Parkinson's disease (PD). In clinical practice, the naked-eye evaluation of RFT results in a coarse judgment of symptom scores. We introduce a novel computer-vision (CV) method for quantification of tapping symptoms through motion analysis of index-fingers. The method is unique as it utilizes facial features to calibrate tapping amplitude for normalization of distance variation between the camera and subject. METHODS: The study involved 387 video footages of RFT recorded from 13 patients diagnosed with advanced PD. Tapping performance in these videos was rated by two clinicians between the symptom severity levels ('0: normal' to '3: severe') using the unified Parkinson's disease rating scale motor examination of finger-tapping (UPDRS-FT). Another set of recordings in this study consisted of 84 videos of RFT recorded from 6 healthy controls. These videos were processed by a CV algorithm that tracks the index-finger motion between the video-frames to produce a tapping time-series. Different features were computed from this time series to estimate speed, amplitude, rhythm and fatigue in tapping. The features were trained in a support vector machine (1) to categorize the patient group between UPDRS-FT symptom severity levels, and (2) to discriminate between PD patients and healthy controls. RESULTS: A new representative feature of tapping rhythm, 'cross-correlation between the normalized peaks' showed strong Guttman correlation (µ2=-0.80) with the clinical ratings. The classification of tapping features using the support vector machine classifier and 10-fold cross validation categorized the patient samples between UPDRS-FT levels with an accuracy of 88%. The same classification scheme discriminated between RFT samples of healthy controls and PD patients with an accuracy of 95%. CONCLUSION: The work supports the feasibility of the approach, which is presumed suitable for PD monitoring in the home environment. The system offers advantages over other technologies (e.g. magnetic sensors, accelerometers, etc.) previously developed for objective assessment of tapping symptoms.

Spiral drawing during self-rated dyskinesia is more impaired than during self-rated Off.

OBJECTIVE: The purpose of this study was to examine repeated measures of fine motor function in relation to self-assessed motor conditions in Parkinson's disease (PD). METHODS: One-hundred PD patients, 65 with advanced PD and 35 patients with different disease stages have utilized a test battery in a telemedicine setting. On each test occasion, they initially self-assessed their motor condition (from 'very off' to 'very dyskinetic') and then performed a set of fine motor tests (tapping and spiral drawings). RESULTS: The motor tests scores were found to be the best during self-rated On. Self-rated dyskinesias caused more impaired spiral drawing performance (mean = 9.8% worse, P < 0.001) but at the same time tapping speed was faster (mean = 5.0% increase, P < 0.001), compared to scores in self-rated Off. CONCLUSIONS: The fine motor tests of the test battery capture different symptoms; the spiral impairment primarily relates to dyskinesias whereas the tapping speed captures the Off symptoms.

Motion cue analysis for parkinsonian gait recognition.

This paper presents a computer-vision based marker-free method for gait-impairment detection in Patients with Parkinson's disease (PWP). The system is based upon the idea that a normal human body attains equilibrium during the gait by aligning the body posture with Axis-of-Gravity (AOG) using feet as the base of support. In contrast, PWP appear to be falling forward as they are less-able to align their body with AOG due to rigid muscular tone. A normal gait exhibits periodic stride-cycles with stride-angle around 45o between the legs, whereas PWP walk with shortened stride-angle with high variability between the stride-cycles. In order to analyze Parkinsonian-gait (PG), subjects were videotaped with several gait-cycles. The subject's body was segmented using a color-segmentation method to form a silhouette. The silhouette was skeletonized for motion cues extraction. The motion cues analyzed were stride-cycles (based on the cyclic leg motion of skeleton) and posture lean (based on the angle between leaned torso of skeleton and AOG). Cosine similarity between an imaginary perfect gait pattern and the subject gait patterns produced 100% recognition rate of PG for 4 normal-controls and 3 PWP. Results suggested that the method is a promising tool to be used for PG assessment in home-environment.

A web application for follow-up of results from a mobile device test battery for Parkinson's disease patients.

This paper describes a web-based system for enabling remote monitoring of patients with Parkinson's disease (PD) and supporting clinicians in treating their patients. The system consists of a patient node for subjective and objective data collection based on a handheld computer, a service node for data storage and processing, and a web application for data presentation. Using statistical and machine learning methods, time series of raw data are summarized into scores for conceptual symptom dimensions and an "overall test score" providing a comprehensive profile of patient's health during a test period of about one week. The handheld unit was used quarterly or biannually by 65 patients with advanced PD for up to four years at nine clinics in Sweden. The IBM Computer System Usability Questionnaire was administered to assess nurses' satisfaction with the web application. Results showed that a majority of the nurses were quite satisfied with the usability although a sizeable minority were not. Our findings support that this system can become an efficient tool to easily access relevant symptom information from the home environment of PD patients.

A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion.

OBJECTIVE: The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of a levodopa/carbidopa gel (Duodopa) to examine pharmacological properties of this treatment. METHODS: The modeling involved pooling data from 3 studies (on advanced Parkinson disease) and fixing some parameters to values found in literature. The first study involved 12 patients studied on 3 occasions each and was previously published. The second study involved 3 patients on 2 occasions. A bolus dose was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function on a 7-point treatment response scale ranging from "very off" to "very hyperkinetic") were collected until the clinical effect returned to baseline. The third study involved 5 patients on 3 occasions receiving 5 different dose levels. Different structural models were evaluated using the nonlinear mixed-effects modeling program NONMEM VI. Population mean parameter values, and interindividual, interoccasion, and residual variabilities were estimated. RESULTS: Absorption of the levodopa/carbidopa gel can be adequately described with first-order absorption with bioavailability and lag time. Estimated population parameter values were a mean absorption time of 28.5 minutes, a lag time of 2.9 minutes, and a bioavailability of 88%. The pharmacodynamic model for motor ratings had the following population values: a half-life of effect delay of 21 minutes, a concentration at 50% effect of 1.55 mg/L, an Emax of 2.39 U on the treatment response scale, and a sigmoidicity of the Emax function of 11.6. CONCLUSIONS: For the typical unmedicated subject, it will take 51.4 minutes until the peak levodopa effect is reached after a bolus dose. This delay is, like the magnitude of the effect, highly variable in this patient group. The residual error magnitudes of 20% for levodopa concentrations and 0.92 U (SD) for motor ratings indicate that the models developed provide predictions of a relevant quality. The developed model may be a first step toward model-guided treatment individualization of duodenal infusion of levodopa.

A home environment test battery for status assessment in patients with advanced Parkinson's disease.

A test battery for assessing patient state in advanced Parkinson's disease, consisting of self-assessments and motor tests, was constructed and implemented on a hand computer with touch screen in a telemedicine setting. The aim of this work was to construct an assessment device, applicable during motor fluctuations in the patient's home environment. Selection of self-assessment questions was based on questions from an e-diary, previously used in a clinical trial. Both un-cued and cued tapping tests and spiral drawing tests were designed for capturing upper limb stiffnes, slowness and involuntary movements. The patient interface gave an audible signal at scheduled response times and was locked otherwise. Data messages in an XML-format were sent from the hand unit to a central server for storage, processing and presentation. In tapping tests, speed and accuracy were calculated and in spiral tests, standard deviation of frequency filtered radial drawing velocity was calculated. An overall test score, combining repeated assessments of the different test items during a test period, was defined based on principal component analysis and linear regression. An evaluation with two pilot patients before and after receiving new types of treatments was performed. Compliance and usability was assessed in a clinical trial (65 patients with advanced Parkinson's disease) and correlations between different test items and internal consistency were investigated. The test battery could detect treatment effect in the two pilot patients, both in self-assessments, tapping tests' results and spiral scores. It had good patient compliance and acceptable usability according to nine nurses. Correlation analysis showed that tapping results provided different information as compared to diary responses. Internal consistency of the test battery was good and learning effects in the tapping tests were small.