New­onset non­motor symptoms in patients with Parkinson's disease and post­COVID­19 syndrome: A prospective cross­sectional study.

The clinical range of post-coronavirus disease 2019 (COVID-19) symptoms in patients with Parkinson's disease (PD) has not yet been thoroughly characterized, with the exception of a few small case studies. The aim of the present study was to investigate the motor and non-motor progression of patients with PD (PWP) and post-COVID-19 syndrome (PCS) at baseline and at 6 months after infection with COVID-19. A cross-sectional prospective study of 38 PWP+/PCS+ and 20 PWP+/PCS- matched for age, sex and disease duration was conducted. All patients were assessed at baseline and at 6 months using a structured clinicodemographic questionnaire, the Unified Parkinson's Disease Rating Scale Part III (the UPDRS III), the Montreal Cognitive Assessment, the Hoehn and Yahr scale, the Geriatric Depression Scale and the levodopa equivalent daily dose (LEDD). There was a statistically significant difference in the LEDD (P=0.039) and UPDRS III (P=0.001) at baseline and at 6 months after infection with COVID-19 between the PWP with PCS groups. The most common non-motor PCS symptoms were anosmia/hyposmia, sore throat, dysgeusia and skin rashes. There was no statistically significant difference in demographics or specific scores between the two groups, indicating that no prognostic factor for PCS in PWP could be identified. The novelty of the present study is that it suggests the new onset of non-motor PCS symptoms of PWP with a mild to moderate stage.

Determination of the motor status of patients with advanced Parkinson's disease under levodopa-carbidopa intestinal gel using a machine learning model.

BACKGROUND: Despite the careful selection of candidate patients, the levodopa-carbidopa intestinal gel (LCIG) treatment of advanced Parkinson's disease (PD) remains challenging due to a complex interplay between motor and non-motor symptoms. We developed a random forest (RF) model to determine the postoperative motor outcome of patients with advanced PD at 2 years under the LCIG therapy by using motor and non-motor data from a Greek multicenter, observational registry (ForHealth S.A.). METHODS: This was a prospective 24-month, observational study of 59 patients with advanced PD under LCIG treatment from September 2019 to September 2021. Motor status was assessed with the Unified Parkinson's Disease Rating Scale (UPDRS) parts III and IV. Non-motor symptoms (NMS) were assessed by the Non-Motor Symptoms Questionnaire (NMSQ) and the Geriatric Depression Scale (GDS). RESULTS: We demonstrated that the proper combination of motor and non-motor measures significantly determines the motor outcome (UPDRS-III year 2: 23.57 ± 14.22 p < 0.001), reducing the RMSE (root-mean-square-error) from 3.487279 to 3.066292, suggesting that the optimized model performed well. Based on the "IncNodePurity," the major determinant factors of UPDRS-III (year 2) were, in descending order: UPDRS-III (year 0), disease duration, NMSQ (year 2), age, NMSQ (year 0), time off (hours) (year 2), time dyskinesia (year 0), quality of life (year 2) after the LCIG implementation. CONCLUSIONS: The novelty of this model is the possibility to determine the motor outcome after two years of LCIG. This model could be also useful for not specialized Parkinson's neurologists, to improve patient counseling, expectation management, and patient satisfaction with LCIG therapy.

Asymptomatic carriers of the p.A53T SNCA mutation: Data from the PPMI study.

We assessed non motor characteristics of 12 asymptomatic p.A53T mutation carriers (A53T-AC) compared with 36 healthy controls (HC) enrolled in the Parkinson's Progression Markers Initiative (PPMI) study. Olfaction score was lower and anxiety was marginally more prevalent in A53T- AC. These findings suggest distinct prodromal features in this group of subjects.

A Novel Machine Learning Algorithm Predicts Dementia With Lewy Bodies Versus Parkinson's Disease Dementia Based on Clinical and Neuropsychological Scores.

OBJECTIVE: Our aim was to develop a machine learning algorithm based only on non-invasively clinic collectable predictors, for the accurate diagnosis of these disorders. METHODS: This is an ongoing prospective cohort study (ClinicalTrials.gov identifier NCT number NCT04448340) of 78 PDD and 62 DLB subjects whose diagnostic follow-up is available for at least 3 years after the baseline assessment. We used predictors such as clinico-demographic characteristics, 6 neuropsychological tests (mini mental, PD Cognitive Rating Scale, Brief Visuospatial Memory test, Symbol digit written, Wechsler adult intelligence scale, trail making A and B). We investigated logistic regression, K-Nearest Neighbors (K-NNs) Support Vector Machine (SVM), Naïve Bayes classifier, and Ensemble Model for their ability to predict successfully PDD or DLB diagnosis. RESULTS: The K-NN classification model had an accuracy 91.2% of overall cases based on 15 best clinical and cognitive scores achieving 96.42% sensitivity and 81% specificity on discriminating between DLB and PDD. The binomial logistic regression classification model achieved an accuracy of 87.5% based on 15 best features, showing 93.93% sensitivity and 87% specificity. The SVM classification model had an accuracy 84.6% of overall cases based on 15 best features achieving 90.62% sensitivity and 78.58% specificity. A model created on Naïve Bayes classification had 82.05% accuracy, 93.10% sensitivity and 74.41% specificity. Finally, an Ensemble model, synthesized by the individual ones, achieved 89.74% accuracy, 93.75% sensitivity and 85.73% specificity. CONCLUSION: Machine learning method predicted with high accuracy, sensitivity and specificity PDD or DLB diagnosis based on non-invasively and easily in-the-clinic and neuropsychological tests.

Clock-Drawing Tasks as Predictive Measurements for Disease Classification Among Patients With Parkinson's Disease and Essential Tremor.

Background Nonmotor cognitive symptoms are widely being recognized in both Parkinson's Disease (PD) and Essential Tremor (ET), the two most common movement disorders. Clock-drawing (CD) test seems to be impaired early in the process of cognitive (executive) decline in PD. However, the optimal measures for detecting cognitive changes in ET patients have not been established. Examining whether the CD test is a quick test could identify frontal and visuospatial deficits in patients with Parkinson's disease (PD) and essential tremor (ET). Methods Visuospatial performance was assessed in 58 consecutive patients with ET and 75 with PD and 22 healthy controls (HC) who visited two neurological clinics of Athens in Greece. The CD and copy (CC) items of the PD-Cognitive Rating Scale were used as a test of visuospatial function. Results Both CD and CC scores were lower for ET compared to PD patients and HC (p=<0.001 for both comparisons). A binomial logistic regression showed that both CD and CC items predict if participants had ET or PD with high sensitivity 94.7% and specificity 87.9% and an area under the curve (AUC) 0.980 (95% confidence interval, 0.962-0.997). The model explained 86.1% (Nagelkerke R2) of the variance in the disease variable (ET/PD) and correctly classified 91.7% of the cases. Conclusion Patients with ET have more visuospatial deficits compared to PD and HC. CD task may be an easy, useful tool to track cognitive changes in nondemented patients with ET in clinical practice.

Clinical, neuropsychological and imaging characteristics of Alzheimer's disease patients presenting as corticobasal syndrome.

BACKGROUND: Corticobasal syndrome (CBS) can harbor diverse pathologies, such as corticobasal degeneration (CBD) and Alzheimer's disease (AD). CSF biochemical analysis in CBS patients can confidently distinguish between an AD (CBS-AD) and a non-AD (CBS-nAD) pathology. OBJECTIVE: We utilized classical CSF biomarkers to make a distinction between the two groups and examine their clinical, neuropsychological, neuropsychiatric and imaging differences. METHODS: Seventeen patients with a CBS phenotype were included. Detailed clinical history, and neurological examination data were recorded. A thorough neuropsychological and neuropsychiatric test battery was performed, including Goldenberg apraxia test. Simple linear MRI measurements and planimetry data were utilized. CSF biomarkers for AD were ascertained. RESULTS: Five of seventeen CBS patients had a CSF AD profile. Patients with a CSF AD profile (CBS-AD; n = 5) were older and had a greater age at disease onset compared to CBS-nAD. CBS-AD patients had more frequently alien hand phenomena at examination and greater hippocampi surface asymmetry at MRI. CBS-nAD patients (n = 12) had lower superior colliculi width values. CONCLUSION: Clinical, neuropsychological and imaging data cannot confidently differentiate CBS-AD from CBS-nAD patients.

The effect of cortical and subcortical lesions on spontaneous expression of memory-encoded and emotionally infused information: Evidence for a role of the ventral stream.

The ventral stream of language processing has been implicated in the spontaneous expression of memory-encoded and emotionally infused information. The present study investigated whether left hemispheric lesions in post-stroke right-handed aphasic patients may be selectively associated with specific language functions. Speech rate was assessed with two tasks, one based on autobiographical memory of an emotionally infused event (stroke story narration) and the other based on information that is visually available at the time of speech generation ("cookie theft" picture description). CT and/or MRI scans were obtained for each patient and lesions located in 16 regions of the left hemisphere were identified and coded. The total number of cortical and subcortical areas affected served as a measure of lesion extent. While mean speech rates were similar across conditions, there were different patterns of association between each index and specific lesion sites. Non-parametric quantile regression statistical models constructed to assess dependence of both speech rate indices on each lesion locus indicated that the speech rate in the stroke story had significant inverse associations with total number of lesioned areas, as well as lesions in the inferior frontal gyrus and the external/extreme capsule region. The cookie theft speech rate had significant inverse associations with total number of lesioned areas as well as lesion in the inferior frontal gyrus, but not with the external/extreme capsule region. In sum, integrity of the extreme/external capsule region appears to be important selectively for the Stroke Story task, supporting the hypothesis that the ventral stream plays a central role in spontaneous expression of memory-encoded and emotionally infused information.