Cognitive Impairment-Associated Risk Factors of Parkinson's Disease: A Hospital-Based Study in a Cohort of Upper Egypt Parkinson's Patients.

Objective To explore the correlated factors and clinical features of cognitive impariment in parkinson's disease (PD). Methods A total of 419 patients with PD were collected from Xiangya Hospital of Centre-South University during Mar 1st, 2017 to Nov 30th, 2017. The cognitive functions of patients were assessed with the Mini-Mental State Examination (MMSE), and the basic information and the motor symptoms of 419 PD patients were selected at the same time. The PD patients were classified into three groups according to the MMSE score: PD with no cognitive impairment (PD-NC), mild cognitive impairment in PD (PD-MCI), and Dementia in PD (PD-D). The data were analyzed by SPSS 20.0. Results There were 156 patients with PD-MCI (37.2%) and 64 patients with PD-D (15.3%). The difference of sex and disease duration among three groups were not statistically significant (P>0.05). The significant difference was found among PD-D, PD-MCI, and PD-NC groups in age of onset, age, educational attainment, Unified Parkinson's disease Rating Scale (UPDRS)-Ⅱscore, UPDRS-Ⅲ score and Hoehn-Yahr stage (P<0.05). There were significant differences among three groups in MMSE score and its items (P<0.01). Logistics regression analysis found that the age of onset, educational attainment, and Hoehn-Yahr stage were the risk factors of cognitive impairment in PD patients (P<0.05). Conclusions Cognitive im-pairment is common in PD patients, and it is relevant to the age of onset, educational attainment and the severity of illness of PD patients. Key words: Parkinson disease/CO; Cognition disorders/CO

Little is known about the impact of the dopamine system on development of cognitive impairment (CI) in Parkinson disease (PD). We used data from a multi-site, international, prospective cohort study to explore the impact of dopamine system-related biomarkers on CI in PD. PD participants were assessed annually from disease onset out to 7 years, and CI determined by applying cut-offs to four measures: (1) Montreal Cognitive Assessment; (2) detailed neuropsychological test battery; (3) Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) cognition score; and (4) site investigator diagnosis of CI (mild cognitive impairment or dementia). The dopamine system was assessed by serial Iodine-123 Ioflupane dopamine transporter (DAT) imaging, genotyping, and levodopa equivalent daily dose (LEDD) recorded at each assessment. Multivariate longitudinal analyses, with adjustment for multiple comparisons, determined the association between dopamine system-related biomarkers and CI, including persistent impairment. Demographic and clinical variables associated with CI were higher age, male sex, lower education, non-White race, higher depression and anxiety scores and higher MDS-UPDRS motor score. For the dopamine system, lower baseline mean striatum dopamine transporter values (P range 0.003-0.005) and higher LEDD over time (P range <0.001-0.01) were significantly associated with increased risk for CI. Our results provide preliminary evidence that alterations in the dopamine system predict development of clinically-relevant, cognitive impairment in Parkinson's disease. If replicated and determined to be causative, they demonstrate that the dopamine system is instrumental to cognitive health status throughout the disease course. Parkinson's Progression Markers Initiative is registered with ClinicalTrials.gov (NCT01141023).

The Cats‐and‐Dogs test: A tool to identify visuoperceptual deficits in Parkinson's disease

Formulas were developed to define tremor dominant (TD) and postural instability/gait difficulty (PIGD) phenotypes of Parkinson's Disease (PD) using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). TD and PIGD designations, based on the original Unified Parkinson's Disease Rating Scale (UPDRS), provided useful designations for classifying different phenotypes of PD. With the advent of the MDS-UPDRS, a valid set of calculations for these phenotypes is needed. UPDRS and MDS-UPDRS scores were collected on 877 PD patients. TD/PIGD scores were calculated using the UPDRS formula for all patients. Comparable TD and PIGD items from the MDS-UPDRS were used to calculate new ratios. Data were analyzed using receiver operating characteristic models. The new MDS-UPDRS TD/PIGD ratios accounted for a significant area under the curve compared with the UPDRS classification. Optimal sensitivity and specificity were obtained with MDS-UPDRS cutoff scores of ≥1.15 for TD classification and ≤0.90 for PIGD. The development of comparable and valid PIGD and TD scores from the MDS-UPDRS provides a clear method for clinicians and researchers to transition from the original UPDRS to the new MDS-UPDRS in categorizing patients with different clinical phenotypes. © 2013 Movement Disorder Society.

Cognitive impairment is a common non-motor symptom of Parkinson's disease (PD) that significantly impacts patients' quality of life and disease progression. Despite its clinical importance, the underlying mechanisms linking motor and cognitive dysfunction in PD remain poorly understood. Wearable sensor technology offers an innovative approach to quantifying gait parameters and exploring their relationship with cognitive decline, providing a non-invasive, objective method to identify individuals at risk of cognitive impairment. This study aimed to develop and validate a diagnostic model using gait parameters derived from wearable sensors to predict cognitive impairment in PD patients. Additionally, it sought to integrate these findings with machine learning methods to enhance prediction accuracy. A cross-sectional study was conducted on early-to-mid-stage PD patients, with approximately 28.8% diagnosed with cognitive impairment. A total of 38 clinically relevant variables were collected, including demographic data, medical history, cognitive scale scores, and gait data captured by wearable sensors. Baseline comparisons, univariate, and multivariate logistic regression analyses were performed to identify independent risk factors for cognitive impairment. Selected variables were used to train and evaluate six machine-learning models. The models' predictive performance was comprehensively assessed using receiver operating characteristic (ROC) curves, area under the curve (AUC) values, decision curve analysis (DCA), calibration curves, precision-recall (PR) curves, and forest plots. Shapley Additive Explanations (SHAP) analysis was also employed to enable personalized risk assessment. Finally, correlations between cognitive scores (MoCA and MMSE) and key gait parameters were analyzed. Among the 38 clinical variables, seven were identified as independent risk factors for cognitive impairment in PD, including Duration of PD, UPDRS-III score, Step Length, Walk speed, Stride time, Peak arm angular velocity, Peak angular velocity during steering. The logistic regression model demonstrated superior predictive performance (test set AUC: 0.957), outperforming other machine learning algorithms. SHAP analysis revealed that Step Length, UPDRS-III score, Duration of PD, and Peak angular velocity during steering were the most influential predictors in the logistic regression model. Additionally, correlation analysis showed a significant association between lower cognitive scores and deteriorating gait parameters. This study highlights the potential of gait parameters derived from wearable sensors as biomarkers for cognitive impairment in PD patients. It also underscores the intricate interplay between motor and cognitive dysfunction in PD. The integration of gait analysis with machine learning models, particularly logistic regression, provides a robust, non-invasive, and scalable approach for early identification and risk stratification of cognitive decline in PD. By leveraging wearable technology, this work paves the way for innovative diagnostic strategies to enhance clinical decision-making and improve patient outcomes.

Multimodal magnetic resonance imaging studies on non-motor symptoms of Parkinson's disease.

Cognitive impairment (CI) is common in Parkinson's disease (PD) and an important cause of disability. Screening facilitates early detection of CI and has implications for management. Preclinical disability is when patients have functional limitations but maintain independence through compensatory measures. The objective of this study was to investigate the relationship between scores on the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) with levels of PD severity and disability. PD patients (n = 2,234) in a large observational study were stratified by disease severity, based on Total Unified Parkinson's Disease Rating Scale (Total UPDRS) and Hoehn and Yahr (HY) stage. Using MMSE (n = 1,184) or MoCA (n = 1,050) and basic (ADL) and instrumental activities of daily living (IADL) scales for disability, linear regression analysis examined associations between cognitive status and disability. Cognition and disability were highly correlated, with the strongest correlation between IADL and MoCA. Only 16.0% of mean MMSE scores were below threshold for CI (28) and only in advanced PD (Total UPDRS 60+, HY≥3). MoCA scores fell below CI threshold (26) in 66.2% of the sample and earlier in disease (Total UPDRS 30+, HY≥2), corresponding with impairments in ADLs. In a large clinical dataset, a small fraction of MMSE scores fell below cutoff for CI, reinforcing that MMSE is an insensitive screening tool in PD. MoCA scores indicated CI earlier in disease and coincided with disability. This study shows that MoCA, but not MMSE is sensitive to the emergence of early cognitive impairment in PD and correlates with the concomitant onset of disability.

Cognitive pretesting, a qualitative step in scale development, precedes field testing and assesses the difficulty of instrument completion for examiners and respondents. Cognitive pretesting assesses respondent interest, attention span, discomfort, and comprehension, and highlights problems with the logical structure of questions/response options that can affect understanding. In the past this approach was not consistently used in the development or revision of movement disorders scales. We applied qualitative cognitive pretesting using testing guides in development of the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). The guides were based on qualitative techniques, verbal probing and "think-aloud" interviewing, to identify problems with the scale from the patient and rater perspectives. English-speaking Parkinson's disease patients and movement disorders specialists (raters) from multiple specialty clinics in the United States, Western Europe and Canada used the MDS-UPDRS and completed the testing guides. Two rounds of cognitive pretesting were necessary before proceeding to field testing of the revised scale to assess clinimetric properties. Scale revisions based on cognitive pretesting included changes in phrasing, simplification of some questions, and addition of a reassuring statement explaining that not all PD patients experience the symptoms described in the questions. The strategy of incorporating cognitive pretesting into scale development and revision provides a model for other movement disorders scales. Cognitive pretesting is being used in translating the MDS-UPDRS into multiple languages to improve comprehension and acceptance and in the development of a new Unified Dyskinesia Rating Scale for Parkinson's disease patients.

BackgroundWorsening motor symptoms are associated with deteriorations in health‐related quality of life (HrQOL) in patients with Parkinson's disease (PD).AimBecause few studies have examined whether non‐motor symptoms (NMSs) predict worsening of overall NMSs and HrQOL, we investigated whether NMSs are associated with the changes in these outcomes in patients with PD.MethodsWe used data from J‐FIRST, a 52‐week study of patients with PD, ≥1 NMS, and wearing‐off under levodopa treatment. Changes in Movement Disorders Society–Unified Parkinson's Disease Rating Scale (MDS‐UPDRS) Part I and 8‐item Parkinson's Disease Questionnaire (PDQ‐8) total scores during the observation period were compared between patients with and without individual NMSs at baseline. Relationships among NMSs were analyzed by cluster analysis.ResultsThe analyses comprised 996 patients. The MDS‐UPDRS Part I total scores significantly increased in patients with cognitive impairment, depressed mood, and apathy, but significantly decreased in patients with features of dopamine dysregulation syndrome, relative to the changes in patients without these NMSs at baseline. The PDQ‐8 total scores significantly increased in patients with cognitive impairment, hallucinations and psychosis, depressed mood, apathy, pain and other sensations, urinary problems, and fatigue relative to the changes in patients without these NMSs at baseline. NMSs were broadly clustered into cognitive/mental functions, and autonomic functions and sleep. Light headedness on standing, fatigue, and pain and other sensations were closely related.ConclusionWe observed significant deteriorations in the NMS burden and HrQOL in patients with cognitive, mental, or autonomic‐related NMSs.

Telemedicine has become standard in clinical care and research during the coronavirus disease 2019 pandemic. Remote administration of Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III (Motor Examination) precludes ratings of all items, because Rigidity and Postural Stability (six scores) require in-person rating. The objective of this study was to determine imputation accuracy for total-sum and item-specific MDS-UPDRS Motor Examination scores in remote administration. We applied multivariate imputation by chained equations techniques in a cross-sectional dataset where patients had one MDS-UPDRS rating (International Translational Program, n=8,588) and in a longitudinal dataset where patients had multiple ratings (Rush Program, n=396). Successful imputation was stringently defined as (1) generalized Lin's concordance correlation coefficient>0.95, reflecting near-perfect agreement between total-sum score with complete data and surrogate score, calculated without patients' actual Rigidity and Postural Stability scores; and (2) perfect agreement for item-level scores for Rigidity and Postural Stability items. For total-sum score when Rigidity and Postural Stability scores were withdrawn, using one or multiple visits, multivariate imputation by chained equations imputation reached near-perfect agreement with the original total-sum score. However, at the item level, the degree of perfect agreement between the surrogate and actual Rigidity items and Postural Stability scores always fell below threshold. The MDS-UPDRS Part III total-sum score, a key clinical outcome in research and in clinical practice, can be accurately imputed without the Rigidity and Postural Stability items that cannot be rated by telemedicine. No formula, however, allows for specific item-level imputation. When Rigidity and Postural Stability item scores are of key clinical or research interest, patients with PD must be scored in person. © 2022 International Parkinson and Movement Disorder Society.

Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Unified Dyskinesia Rating Scale (UDysRS) were developed as standard tools to rate Parkinson's disease (PD) and drug-induced dyskinesias of PD. As these scales have become widely used, there is a need for translation to non-English languages. Here we present the standardization for the Turkish translations. The scales were translated into Turkish and then back-translated to English. These back-translations were reviewed by the MDS team. After cognitive pretesting, movement disorder specialists from nine centers tested 352 patients for MDS-UPDRS, and 250 patients for UDysRS. Confirmatory factor analyses (CFAs) were used to determine if the factor structures for the reference standards could be confirmed in the Turkish data. The comparative fit indexes (CFIs) for the scales were required to be 0.90 or higher. Exploratory factor analyses (EFAs) were conducted to explore the underlying factor structure without the constraint of a pre-specified factor structure. For both scales, the CFIs were 0.94 or greater as compared to the reference standard factor structures. The factor structures were consistent with that of reference standards, although there were some differences in some areas as compared to the EFA of the reference standard dataset. This may be due to the inclusion of patients with different stages of PD and different cultural properties of raters and patients. These results demonstrate that the Turkish translations of MDS-UPDRS and UDysRS have adequate clinimetric properties. They are established as the official translations and can be reliably used in Turkish speaking populations.

Regulatory recommendations favor outcomes combining objective and patient input. The Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), the most commonly used scale in Parkinson's disease (PD), includes patient and investigator ratings in distinct parts, but original clinimetric analyses failed to confirm the validity of combining parts by simple summing. The aim was to develop clinimetrically valid constructs for combining patient-reported Part 2 and investigator-rated Part 3 MDS-UPDRS scores. Using 7888 MDS-UPDRS scores, we assessed construct validity of combined Part 2 and Part 3 items using exploratory factor analysis (EFA) and graded item response theory (IRT) with threshold criteria: comparative fit index≥0.9 (EFA) and discrimination parameters≥0.65 (IRT). The direct sum of Parts 2+3 failed to meet the threshold for a valid outcome of PD severity (comparative fit index, CFI=0.855). However, a two-domain construct combining item scores for tremor and non-tremor domains from Parts 2 and 3 confirmed validity, meeting both EFA and IRT criteria as distinct but correlated indices of disease severity (CFI=0.923; discrimination mean 2.197 ± 0.480 [tremor] and 1.737 ± 0.344 [non-tremor] domains). The sum of Parts 2+3 is not clinimetrically sound. However, considering tremor and non-tremor items of both Parts 2 and 3 as two outcomes results in a valid summary of PD motor severity that leverages simultaneous patient- and investigator-derived measures. This analytic application addresses regulatory prioritizations and retains the well-validated MDS-UPDRS items. In future interventional trials, we suggest that tremor and non-tremor components of PD motor severity from Parts 2+3 be monitored and analyzed to accurately detect objective changes that integrate the patient's voice. © 2023 International Parkinson and Movement Disorder Society.

Cognitive impairment in Parkinson's disease: Association between patient-reported and clinically measured outcomes

Cognitive impairment (CI) is common in Parkinson's disease (PD). Multiple brain regions and their interactions are involved in PD associated CI. Magnetic resonance imaging (MRI) technology is a non-invasive method in investigating brain structure and inter-regional connections. In this study, by comparing cortical thickness, subcortical volume, and brain network topology properties in PD patients with and without CI, we aimed to understand the changes of brain structure and structural covariance network properties in PD associated CI. A total of 18 PD patients with CI and 33 PD patients without CI were recruited. Movement Disorder Society Unified Parkinson's Disease Rating Scale, Hoehn and Yahr stage, Mini Mental State Examination Scale, Non-motor Symptom Rating Scale, Hamilton Anxiety Scale, and Hamilton Depression Scale were assessed. All participants underwent structural 3T MRI. Cortical thickness, subcortical volume, global and nodal network topology properties were measured. Compared with PD patients without CI, the volumes of white matter, thalamus and hippocampus were lower in PD patients with CI. And decreased whole-brain local efficiency is associated with CI in PD patients. While the cortical thickness and nodal network topology properties were comparable between PD patients with and without CI. Our findings support the alterations of brain structure and disruption of structural covariance network are involved in PD associated CI, providing a new insight into the association between graph properties and PD associated CI.

The exact mechanism of cognitive impairment in PD is not known. Repetitive transcranial magnetic stimulation (rTMS) has been proposed as a possible treatment for cognitive impairment and to treat the motor symptoms in Parkinson's disease (PD) where its effects seem additive to those of dopaminergic medications. In this pilot study we investigated whether repeated sessions of rTMS have an effect on measures of cognitive impairment in patients with PD dementia. 33 patients with PD dementia were randomly assigned sham or real rTMS (2000 pulses; 20 Hz; 90% RMT; 10 trains of 10 s with 25 s between each train) over the hand area of each motor cortex (5 min between hemispheres) for 10 days (5 days/week) followed by 5 booster sessions every month for 3 months. Assessments included the Unified Parkinson's Disease Rating Scale part III (UPDRS), Montreal Cognitive Assessment (MoCA); Mini Mental State Examination (MMSE), Clinical Dementia Rating Scale (CDR); Memory and Executive Screening (MES) and Instrumental activity of Daily Living (IADL). Event related potentials (P300) and cortical excitability were measured before treatment and after the last session. There were no significant differences in the effects of rTMS between groups. Although rTMS improved motor function in the active group it had only a minor effect on two of the dementia rating scores (the MMSE and MoCA) but not the others (CDR and MES). There was also a reduction in the latency of the P300 in the active group. rTMS over M1 is useful for motor function and may have a small positive effect on cognition. However, better approaches for the latter are necessary, may be require multisite rTMS to target both motor and frontal cortical region.