Smaller Cerebellar Lobule VIIb is Associated with Tremor Severity in Parkinson's Disease.

Alterations in the cerebellum's morphology in Parkinson's disease (PD) point to its pathophysiological involvement in this movement disorder. Such abnormalities have previously been attributed to different PD motor subtypes. The aim of the study was to relate volumes of specific cerebellar lobules to motor symptom severity, in particular tremor (TR), bradykinesia/rigidity (BR), and postural instability and gait disorders (PIGD) in PD. We performed a volumetric analysis based on T1-weighted MRI images of 55 participants with PD (22 females, median age 65 years, Hoehn and Yahr stage 2). Multiple regression models were fitted to investigate associations between volumes of cerebellar lobules with clinical symptom severity based on MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III score and sub-scores for TR, BR, and PIGD; adjusted for age, sex, disease duration, and intercranial volume as cofactors. Smaller volume of lobule VIIb was associated with higher tremor severity (P = 0.004). No structure-function relationships were detected for other lobules or other motor symptoms. This distinct structural association denotes the involvement of the cerebellum in PD tremor. Characterizing morphological features of the cerebellum leads to a better understanding of its role in the spectrum of motor symptoms in PD and contributes further to identifying potential biological markers.

Sensor-Based Quantification of MDS-UPDRS III Subitems in Parkinson's Disease Using Machine Learning.

Wearable sensors could be beneficial for the continuous quantification of upper limb motor symptoms in people with Parkinson's disease (PD). This work evaluates the use of two inertial measurement units combined with supervised machine learning models to classify and predict a subset of MDS-UPDRS III subitems in PD. We attached the two compact wearable sensors on the dorsal part of each hand of 33 people with PD and 12 controls. Each participant performed six clinical movement tasks in parallel with an assessment of the MDS-UPDRS III. Random forest (RF) models were trained on the sensor data and motor scores. An overall accuracy of 94% was achieved in classifying the movement tasks. When employed for classifying the motor scores, the averaged area under the receiver operating characteristic values ranged from 68% to 92%. Motor scores were additionally predicted using an RF regression model. In a comparative analysis, trained support vector machine models outperformed the RF models for specific tasks. Furthermore, our results surpass the literature in certain cases. The methods developed in this work serve as a base for future studies, where home-based assessments of pharmacological effects on motor function could complement regular clinical assessments.

Blood neurofilament light chain in Parkinson's disease.

Blood neurofilament light chain (NfL) is an easily accessible, highly sensitive and reliable biomarker for neuroaxonal damage. Currently, its role in Parkinson's disease (PD) remains unclear. Here, we demonstrate that blood NfL can distinguish idiopathic PD from atypical parkinsonian syndromes (APS) with high sensitivity and specificity. In cross-sectional studies, some found significant correlations between blood NfL with motor and cognitive function, whereas others did not. In contrast, prospective studies reported very consistent associations between baseline blood NfL with motor progression and cognitive worsening. Amongst PD subtypes, especially postural instability and gait disorder (PIGD) subtype, symptoms and scores are reliably linked with blood NfL. Different non-motor PD comorbidities have also been associated with high blood NfL levels suggesting that the neuroaxonal damage of the autonomic nervous system as well as serotonergic, cholinergic and noradrenergic neurons is quantifiable. Numerous absolute NfL cutoff levels have been suggested in different cohort studies; however, validation across cohorts remains weak. However, age-adjusted percentiles and intra-individual blood NfL changes might represent more valid and consistent parameters compared with absolute NfL concentrations. In summary, blood NfL has the potential as biomarker in PD patients to be used in clinical practice for prediction of disease severity and especially progression.

White matter hyperintensity burden predicts cognitive but not motor decline in Parkinson's disease: results from the Ontario Neurodegenerative Diseases Research Initiative.

BACKGROUND AND PURPOSE: The pathophysiology of Parkinson's disease (PD) negatively affects brain network connectivity, and in the presence of brain white matter hyperintensities (WMHs) cognitive and motor impairments seem to be aggravated. However, the role of WMHs in predicting accelerating symptom worsening remains controversial. The objective was to investigate whether location and segmental brain WMH burden at baseline predict cognitive and motor declines in PD after 2 years. METHODS: Ninety-eight older adults followed longitudinally from Ontario Neurodegenerative Diseases Research Initiative with PD of 3-8 years in duration were included. Percentages of WMH volumes at baseline were calculated by location (deep and periventricular) and by brain region (frontal, temporal, parietal, occipital lobes and basal ganglia + thalamus). Cognitive and motor changes were assessed from baseline to 2-year follow-up. Specifically, global cognition, attention, executive function, memory, visuospatial abilities and language were assessed as were motor symptoms evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III, spatial-temporal gait variables, Freezing of Gait Questionnaire and Activities Specific Balance Confidence Scale. RESULTS: Regression analysis adjusted for potential confounders showed that total and periventricular WMHs at baseline predicted decline in global cognition (p < 0.05). Also, total WMH burden predicted the decline of executive function (p < 0.05). Occipital WMH volumes also predicted decline in global cognition, visuomotor attention and visuospatial memory declines (p < 0.05). WMH volumes at baseline did not predict motor decline. CONCLUSION: White matter hyperintensity burden at baseline predicted cognitive but not motor decline in early to mid-stage PD. The motor decline observed after 2 years in these older adults with PD is probably related to the primary neurodegenerative process than comorbid white matter pathology.

Serum neurofilament light chain and postural instability/gait difficulty (PIGD) subtypes of Parkinson's disease in the MARK-PD study.

The PIGD (postural instability / gait difficulty) subtype of Parkinson´s disease (PD) is associated with faster cognitive and motor decline. So far, there are no quantifiable biomarkers to aid clinical subtyping. Neurofilament light chain (NfL) is a highly specific marker of neuro-axonal damage and can be assessed in blood. Here, we investigated if serum NfL concentrations are associated with PIGD subtype and PIGD scores in PD patients at advanced disease stages. Furthermore, we evaluated if serum NfL is associated with motor and cognitive function assessed with MDS-UPDRS part III and Montreal cognitive assessment (MoCA). Serum NfL levels were analyzed with Single Molecule Assays (Simoa) in blood of 223 PD patients from the bioMARKers in Parkinson's Disease (MARK-PD) study. Serum NfL concentrations were higher in PIGD patients independent of age, sex and disease duration. In linear regression analysis, serum NfL levels were associated with MoCA, MDS-UPDRS III and PIGD scores in unadjusted models, but remained significant after adjustment only with PIGD scores. In conclusion, increased serum NfL levels were associated with PIGD subtype and PIGD scores in patients with advanced PD.

Can Gait Features Help in Differentiating Parkinson's Disease Medication States and Severity Levels? A Machine Learning Approach.

Parkinson's disease (PD) is one of the most prevalent neurological diseases, described by complex clinical phenotypes. The manifestations of PD include both motor and non-motor symptoms. We constituted an experimental protocol for the assessment of PD motor signs of lower extremities. Using a pair of sensor insoles, data were recorded from PD patients, Elderly and Adult groups. Assessment of PD patients has been performed by neurologists specialized in movement disorders using the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS)-Part III: Motor Examination, on both ON and OFF medication states. Using as a reference point the quantified metrics of MDS-UPDRS-Part III, severity levels were explored by classifying normal, mild, moderate, and severe levels of PD. Elaborating the recorded gait data, 18 temporal and spatial characteristics have been extracted. Subsequently, feature selection techniques were applied to reveal the dominant features to be used for four classification tasks. Specifically, for identifying relations between the spatial and temporal gait features on: PD and non-PD groups; PD, Elderly and Adults groups; PD and ON/OFF medication states; MDS-UPDRS: Part III and PD severity levels. AdaBoost, Extra Trees, and Random Forest classifiers, were trained and tested. Results showed a recognition accuracy of 88%, 73% and 81% for, the PD and non-PD groups, PD-related medication states, and PD severity levels relevant to MDS-UPDRS: Part III ratings, respectively.

Item Response Theory Analysis of the MDS-UPDRS Motor Examination: Tremor vs. Nontremor Items.

BACKGROUND: In PD, tremor severity behaves differently from other core motor features. However, the most commonly used assessment of overall motor severity, total MDS-UPDRS Motor Examination (Part 3) score, does not account for this distinction. OBJECTIVES: To investigate the Motor Examination (Part 3) using Item Response Theory approaches focusing on sample-independent strategies that assess how well items measure latent models of PD motor severity. METHODS: Data from 6,298 PD patients were analyzed with graded response model Item Response Theory approaches involving two analyses all 33 Part 3 items versus the 10 tremor items and 23 bradykinesia, rigidity, gait, and posture items considered separately. The strength of relationship between items and the latent measure of parkinsonian motor severity (discrimination parameter) and calculated thresholds (location parameters) were assessed using the mirt program implemented in R (R Foundation for Statistical Computing, Vienna, Austria). RESULTS: Analyzing all Part 3 items together, nontremor items demonstrated good discrimination parameters (mean = 1.83 ± 0.37) and range of thresholds (-1.73 to +4.42), but tremor items had poor discrimination (mean = 0.52 ± 0.76) and thresholds (-0.69 to 14.29). Segregating nontremor from tremor items in two independent analyses provided markedly improved discrimination and location parameters for both. CONCLUSIONS: MDS-UPDRS Part 3 tremor and nontremor items have very different relations to the construct of PD severity. Strongly improved clinimetric properties for Part 3 are obtained when tremor and nontremor items are considered separately. We suggest that evaluating PD motor severity, as an operationalized summary measure, is best attained through separate analyses with tremor and nontremor motor scores. © 2020 International Parkinson and Movement Disorder Society.

Assessing the relationship between non-motor symptoms and health-related quality of life in Parkinson's disease: a retrospective observational cohort study.

OBJECTIVES: Non-motor symptoms (NMSs) negatively impact the health-related quality of life (HrQOL) of patients with Parkinson's disease (PD). The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is a comprehensive scale for evaluating PD. It remains unclear whether the NMSs evaluated with MDS-UPDRS are predictive of HrQOL. This study aimed to investigate whether NMSs, as evaluated with the MDS-UPDRS, could predict the HrQOL of patients with PD. MATERIALS AND METHODS: We conducted a 2-year retrospective observational cohort study assessing 108 patients with PD who were recruited from a single tertiary center between January 2015 and December 2017. MDS-UPDRS was used to assess NMSs and motor symptoms and Parkinson's Disease Questionnaire-39 (PDQ-39) to measure patients' HrQOL. RESULTS: The median age of patients was 69 years, and 65.7% were female. The median MDS-UPDRS part I, part II, part III, and PDQ-39-summary index scores were 8, 10, 22, and 25, respectively. The final stepwise multiple linear regression model showed that female sex (standard partial regression coefficient ß = 0.131, P < 0.05) and baseline MDS-UPDRS part I (ß = 0.272, P < 0.01) and part II (ß = 0.571, P < 0.01) scores significantly predicted the PDQ-39-SI scores at the 2-year follow-up. CONCLUSIONS: In addition to motor symptoms, NMSs at the 2-year follow-up may be useful for predicting the HrQOL of patients with PD. In clinical practice, MDS-UPDRS-guided assessment and treatment of motor symptoms and NMSs may contribute to improving HrQOL in patients with PD.

Validation of the Polish version of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS).

BACKGROUND: In 2008, the Movement Disorders Society (MDS) published a new Unified Parkinson's Disease Rating Scale (MDS-UPDRS) as the official benchmark scale for Parkinson's Disease (PD). We have translated and validated the Polish version of the MDS-UPDRS, explored its dimensionality, and compared it to the original English one. METHODS: The MDS-UPDRS was translated into Polish by a team of Polish investigators led by JS and GO. The back-translation was completed by colleagues fluent in both languages (Polish and English) who were not involved in the original translation, and was reviewed by members of the MDS Rating Scales Programme. Then the translated version of the MDS-UPDRS underwent cognitive pretesting, and the translation was modified based on the results. The final translation was approved as the Official Working Document of the MDS-UPDRS Polish version, and was tested on 355 Polish PD patients recruited at movement disorders centres all over Poland (at Katowice, Gdansk, Lódz, Warsaw, Wroclaw, and Kraków). Confirmatory and explanatory factor analyses were applied to determine whether the factor structure of the English version could be confirmed in the Polish version. RESULTS: The Polish version of the MDS-UPDRS showed satisfactory clinimetric properties. The internal consistency of the Polish version was satisfactory. In the confirmatory factor analysis, all four parts had greater than 0.90 comparative fit index (CFI) compared to the original English MDS-UPDRS. Explanatory factor analysis suggested that the Polish version differed from the English version only within an acceptable range. CONCLUSIONS AND CLINICAL IMPLICATIONS: The Polish version of the MDS-UPDRS meets the requirements to be designated as the Official Polish Version of the MDS-UPDRS, and is available on the MDS web page. We strongly recommend using the MDS-UPDRS instead of the UPDRS for research purposes and in everyday clinical practice.

Measuring Parkinson's disease over time: The real-world within-subject reliability of the MDS-UPDRS.

BACKGROUND: An important challenge in Parkinson's disease research is how to measure disease progression, ideally at the individual patient level. The MDS-UPDRS, a clinical assessment of motor and nonmotor impairments, is widely used in longitudinal studies. However, its ability to assess within-subject changes is not well known. The objective of this study was to estimate the reliability of the MDS-UPDRS when used to measure within-subject changes in disease progression under real-world conditions. METHODS: Data were obtained from the Parkinson's Progression Markers Initiative cohort and included repeated MDS-UPDRS measurements from 423 de novo Parkinson's disease patients (median follow-up: 54 months). Subtotals were calculated for parts I, II, and III (in on and off states). In addition, factor scores were extracted from each part. A linear Gaussian state space model was used to differentiate variance introduced by long-lasting changes from variance introduced by measurement error and short-term fluctuations. Based on this, we determined the within-subject reliability of 1-year change scores. RESULTS: Overall, the within-subject reliability ranged from 0.13 to 0.62. Of the subscales, parts II and III (OFF) demonstrated the highest within-subject reliability (both 0.50). Of the factor scores, the scores related to gait/posture (0.62), mobility (0.45), and rest tremor (0.43) showed the most consistent behavior. CONCLUSIONS: Our results highlight that MDS-UPDRS change scores contain a substantial amount of error variance, underscoring the need for more reliable instruments to forward our understanding of the heterogeneity in PD progression. Focusing on gait and rest tremor may be a promising approach for an early Parkinson's disease population. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Accuracy of MDS-UPDRS section IV for detecting motor fluctuations in Parkinson's disease.

BACKGROUND: In a precedent paper, we validated part IV of the Unified Parkinson's Disease Rating Scale (UPDRS) for detecting motor fluctuations in Parkinson's Disease (PD) patients using a 12-h Waking-Day Motor Assessment (WDMA) as gold standard, showing a high sensitivity (> 80%) and a lower specificity (< 45%). The aim of this study was to validate the Movement Disorder Society-UPDRS (MDS-UPDRS) part IV, especially items 4.3 and 4.5, using the same methodology. METHODS: PD patients attending the Movement Disorders Clinic at the University Hospital in Catania were consecutively enrolled in the study. A diurnal WDMA was performed to detect motor fluctuations. At each time interval, the motor impairment was evaluated using the motor section of the MDS-UPDRS. Presence or absence of motor fluctuations and the type of motor fluctuation were assessed by four blinded expert raters in movement disorders, by evaluating the graphical representations of the WDMA. We evaluated sensitivity and specificity together with 95% Confidence Interval (CI) of items 4.3 and 4.5, using WDMA as gold standard. RESULTS: We estimated for item 4.3 of the MDS-UPDRS a sensitivity of 74.3% (95% CI 56.7-87.5) and a specificity of 70.6% (95% CI 44-89.7), while for item 4.5, a sensitivity of 67.9% (95% CI 47.6-84.1) and a specificity of 66.7% (95% CI 44.7-84.4). CONCLUSIONS: The present showed a higher specificity level for MDS-UPDRS with respect to the UPDRS, while a slightly lower sensitivity mainly for predictable OFF.

A low-cost vision system based on the analysis of motor features for recognition and severity rating of Parkinson's Disease.

BACKGROUND: Assessment and rating of Parkinson's Disease (PD) are commonly based on the medical observation of several clinical manifestations, including the analysis of motor activities. In particular, medical specialists refer to the MDS-UPDRS (Movement Disorder Society - sponsored revision of Unified Parkinson's Disease Rating Scale) that is the most widely used clinical scale for PD rating. However, clinical scales rely on the observation of some subtle motor phenomena that are either difficult to capture with human eyes or could be misclassified. This limitation motivated several researchers to develop intelligent systems based on machine learning algorithms able to automatically recognize the PD. Nevertheless, most of the previous studies investigated the classification between healthy subjects and PD patients without considering the automatic rating of different levels of severity. METHODS: In this context, we implemented a simple and low-cost clinical tool that can extract postural and kinematic features with the Microsoft Kinect v2 sensor in order to classify and rate PD. Thirty participants were enrolled for the purpose of the present study: sixteen PD patients rated according to MDS-UPDRS and fourteen healthy paired subjects. In order to investigate the motor abilities of the upper and lower body, we acquired and analyzed three main motor tasks: (1) gait, (2) finger tapping, and (3) foot tapping. After preliminary feature selection, different classifiers based on Support Vector Machine (SVM) and Artificial Neural Networks (ANN) were trained and evaluated for the best solution. RESULTS: Concerning the gait analysis, results showed that the ANN classifier performed the best by reaching 89.4% of accuracy with only nine features in diagnosis PD and 95.0% of accuracy with only six features in rating PD severity. Regarding the finger and foot tapping analysis, results showed that an SVM using the extracted features was able to classify healthy subjects versus PD patients with great performances by reaching 87.1% of accuracy. The results of the classification between mild and moderate PD patients indicated that the foot tapping features were the most representative ones to discriminate (81.0% of accuracy). CONCLUSIONS: The results of this study have shown how a low-cost vision-based system can automatically detect subtle phenomena featuring the PD. Our findings suggest that the proposed tool can support medical specialists in the assessment and rating of PD patients in a real clinical scenario.

Low-fat versus ketogenic diet in Parkinson's disease: A pilot randomized controlled trial.

BACKGROUND: Preliminary evidence suggests that diet manipulation may influence motor and nonmotor symptoms in PD, but conflict exists regarding the ideal fat to carbohydrate ratio. OBJECTIVES: We designed a pilot randomized, controlled trial to compare the plausibility, safety, and efficacy of a low-fat, high-carbohydrate diet versus a ketogenic diet in a hospital clinic of PD patients. METHODS: We developed a protocol to support PD patients in a diet study and randomly assigned patients to a low-fat or ketogenic diet. Primary outcomes were within- and between-group changes in MDS-UPDRS Parts 1 to 4 over 8 weeks. RESULTS: We randomized 47 patients, of which 44 commenced the diets and 38 completed the study (86% completion rate for patients commencing the diets). The ketogenic diet group maintained physiological ketosis. Both groups significantly decreased their MDS-UPDRS scores, but the ketogenic group decreased more in Part 1 (-4.58 ± 2.17 points, representing a 41% improvement in baseline Part 1 scores) compared to the low-fat group (-0.99 ± 3.63 points, representing an 11% improvement) (P < 0.001), with the largest between-group decreases observed for urinary problems, pain and other sensations, fatigue, daytime sleepiness, and cognitive impairment. There were no between-group differences in the magnitude of decrease for Parts 2 to 4. The most common adverse effects were excessive hunger in the low-fat group and intermittent exacerbation of the PD tremor and/or rigidity in the ketogenic group. CONCLUSIONS: It is plausible and safe for PD patients to maintain a low-fat or ketogenic diet for 8 weeks. Both diet groups significantly improved in motor and nonmotor symptoms; however, the ketogenic group showed greater improvements in nonmotor symptoms. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson's Disease Patients.

PURPOSE: This manuscript aims to precisely describe the natural disease progression of Parkinson's disease (PD) patients and evaluate approaches to increase the drug effect detection power. METHODS: An item response theory (IRT) longitudinal model was built to describe the natural disease progression of 423 de novo PD patients followed during 48 months while taking into account the heterogeneous nature of the MDS-UPDRS. Clinical trial simulations were then used to compare drug effect detection power from IRT and sum of item scores based analysis under different analysis endpoints and drug effects. RESULTS: The IRT longitudinal model accurately describes the evolution of patients with and without PD medications while estimating different progression rates for the subscales. When comparing analysis methods, the IRT-based one consistently provided the highest power. CONCLUSION: IRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.

Gender-, age-, and race/ethnicity-based differential item functioning analysis of the movement disorder society-sponsored revision of the Unified Parkinson's disease rating scale.

OBJECTIVE: Assess MDS-UPDRS items for gender-, age-, and race/ethnicity-based differential item functioning. BACKGROUND: Assessing differential item functioning is a core rating scale validation step. For the MDS-UPDRS, differential item functioning occurs if item-score probability among people with similar levels of parkinsonism differ according to selected covariates (gender, age, race/ethnicity). If the magnitude of differential item functioning is clinically relevant, item-score interpretation must consider influences by these covariates. Differential item functioning can be nonuniform (covariate variably influences an item-score across different levels of parkinsonism) or uniform (covariate influences an item-score consistently over all levels of parkinsonism). METHODS: Using the MDS-UPDRS translation database of more than 5,000 PD patients from 14 languages, we tested gender-, age-, and race/ethnicity-based differential item functioning. To designate an item as having clinically relevant differential item functioning, we required statistical confirmation by 2 independent methods, along with a McFadden pseudo-R2 magnitude statistic greater than "negligible." RESULTS: Most items showed no gender-, age- or race/ethnicity-based differential item functioning. When differential item functioning was identified, the magnitude statistic was always in the "negligible" range, and the scale-level impact was minimal. CONCLUSIONS: The absence of clinically relevant differential item functioning across all items and all parts of the MDS-UPDRS is strong evidence that the scale can be used confidently. As studies of Parkinson's disease increasingly involve multinational efforts and the MDS-UPDRS has several validated non-English translations, the findings support the scale's broad applicability in populations with varying gender, age, and race/ethnicity distributions. © 2016 International Parkinson and Movement Disorder Society.

MDS-UPDRS to assess non-motor symptoms after STN DBS for Parkinson's disease.

OBJECTIVE: To determine if the non-motor sections of the Movement Disorder Society's (MDS) version of the Unified Parkinson's Disease Rating Scale (UPDRS) could supplement the original UPDRS as a patient completed assessment of changes in non-motor symptoms in Parkinson's disease (PD) patients after bilateral subthalamic nucleus (STN) deep brain stimulation (DBS). METHODS: Thirty PD patients who underwent bilateral STN DBS were assessed using the total UPDRS and the non-motor sections of the MDS-UPDRS prior to surgery and one year following surgery. This study focuses on non-motor symptoms as assessed by Part I of the UPDRS and Part 1A and 1B of the MDS-UPDRS. RESULTS: One year following surgery, no individual non-motor symptoms or the total mentation score of the UPDRS were significantly changed. In comparison, the MDS-UPDRS showed significant improvements in sleep and urinary problems and a trend towards improvement in anxiety, constipation, daytime sleepiness, fatigue and pain. CONCLUSIONS: This study provides evidence that the MDS-UPDRS non-motor sections, when completed by the patients, can supplement the original version of the UPDRS as an effective method of measuring changes in non-motor symptoms after DBS. It also reinforces the benefits of bilateral STN DBS on non-motor symptoms of PD.

Proposing a Parkinson's disease-specific tremor scale from the MDS-UPDRS.

BACKGROUND: This article proposes an International Parkinson and Movement Disorder Society (MDS)-UPDRS tremor-based scale and describes its measurement properties, with a view to developing an improved scale for assessing tremor in Parkinson's disease (PD). METHODS: This was a cross-sectional, multicenter study of 435 PD patients. Rasch analysis was performed on the 11 MDS-UPDRS tremor items. Construct validity, precision, and test-retest reliability were also analyzed. RESULTS: After some modifications, which included removal of an item owing to redundancy, the obtained MDS-UPDRS tremor scale showed moderate reliability, unidimensionality, absence of differential item functioning, satisfactory convergent validity with medication, and better precision than the raw sum score. However, the scale displayed a floor effect and a need for more items measuring lower levels of tremor. CONCLUSIONS: The MDS-UPDRS tremor scale provides linear scores that can be used to assess tremor in PD in a valid, reliable way. The scale might benefit from modifications and studies that analyze its responsiveness.

Handling missing values in the MDS-UPDRS.

This study was undertaken to define the number of missing values permissible to render valid total scores for each Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part. To handle missing values, imputation strategies serve as guidelines to reject an incomplete rating or create a surrogate score. We tested a rigorous, scale-specific, data-based approach to handling missing values for the MDS-UPDRS. From two large MDS-UPDRS datasets, we sequentially deleted item scores, either consistently (same items) or randomly (different items) across all subjects. Lin's Concordance Correlation Coefficient (CCC) compared scores calculated without missing values with prorated scores based on sequentially increasing missing values. The maximal number of missing values retaining a CCC greater than 0.95 determined the threshold for rendering a valid prorated score. A second confirmatory sample was selected from the MDS-UPDRS international translation program. To provide valid part scores applicable across all Hoehn and Yahr (H&Y) stages when the same items are consistently missing, one missing item from Part I, one from Part II, three from Part III, but none from Part IV can be allowed. To provide valid part scores applicable across all H&Y stages when random item entries are missing, one missing item from Part I, two from Part II, seven from Part III, but none from Part IV can be allowed. All cutoff values were confirmed in the validation sample. These analyses are useful for constructing valid surrogate part scores for MDS-UPDRS when missing items fall within the identified threshold and give scientific justification for rejecting partially completed ratings that fall below the threshold.

Assessing the non-motor symptoms of Parkinson's disease: MDS-UPDRS and NMS Scale.

BACKGROUND AND PURPOSE: Although Parkinson's disease (PD) is characterized by typical motor manifestations, non-motor symptoms (NMS) are an outstanding part of the disease. At present, several specific instruments for assessment of NMS are available. The objective of our study was to determine the performance of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS): Part I - Non-Motor Aspects of Experiences of Daily Living (nM-EDL) compared with the Non-Motor Symptoms Scale (NMSS). METHODS: To this purpose, 434 consecutive patients with PD were included in an international, observational, cross-sectional study. The association between scores of both scales was determined by the Spearman rank correlation coefficient. Equations for transformation of total score of a scale to the other were constructed from weighted regression models and both, transformed and observed score, contrasted by means of the Lin's Concordance Correlation Coefficient (LCCC) and Bland-Altman plot. RESULTS: As a whole, the prevalence of the NMS according to each scale was quite similar, and most of the correlations between their corresponding components were high (r(S) > 0.60). The total score correlation of the MDS-UPDRS Part I with the NMSS was high (r(S) = 0.81). Concerning the transformed scores, estimated scores only partially approach the observed ones (sharing about 60-64% of the variance) because residual variance increased with increasing magnitudes of the scores, i.e. the most severe patients (Bland-Altman plot; LCCC < 0.60 for severe patients). CONCLUSIONS: (i) MDS-UPDRS Part I (nM-EDL) and NMSS showed a strong convergent validity; (ii) however, transformed scores using the equations from weighted regression models showed that for patients with the most severe NMS they are not concordant.