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Growing evidence suggests that non-motor symptoms (NMS) in Parkinson’s disease (PD) have differential progression patterns that have a different natural history from motor progression and may be geographically influenced. We conducted a cross-sectional analysis of 1607 PD patients of whom 1327 were from Europe, 208 from the Americas, and 72 from Asia. The primary objective was to assess baseline non-motor burden, defined by Non-Motor Symptoms Scale (NMSS) total scores. Other aims included identifying the factors predicting quality of life, differences in non-motor burden between drug-naïve and non-drug-naïve treated patients, and non-motor phenotypes across different geographical locations. Mean age was 65.9 ± 10.8 years, mean disease duration 6.3 ± 5.6 years, median Hoehn and Yahr stage was 2 (2–3), and 64.2% were male. In this cohort, mean NMSS scores were 46.7 ± 37.2. Differences in non-motor burden and patterns differed significantly between drug-naïve participants, those with a disease duration of less than five years, and those with a duration of five years or over (p ≤ 0.018). Significant differences were observed in geographical distribution (NMSS Europe: 46.4 ± 36.3; Americas: 55.3 ± 42.8; Asia: 26.6 ± 25.1; p < 0.001), with differences in sleep/fatigue, urinary, sexual, and miscellaneous domains (p ≤ 0.020). The best predictor of quality of life was the mood/apathy domain (β = 0.308, p < 0.001). This global study reveals that while non-motor symptoms are globally present with severe NMS burden impacting quality of life in PD, there appear to be differences depending on disease duration and geographical distribution.

In people with Parkinson's disease, neuropsychiatric signs and symptoms are common throughout the disease course. These symptoms can be disabling and as clinically relevant as motor symptoms, and their presentation can be similar to, or distinct from, their counterparts in the general population. Correlates and risk factors for developing neuropsychiatric signs and symptoms include demographic, clinical, and psychosocial characteristics. The underlying neurobiology of these presentations is complex and not well understood, with the strongest evidence for neuropathological changes associated with Parkinson's disease, mechanisms linked to dopaminergic therapy, and effects not specific to Parkinson's disease. Assessment instruments and formal diagnostic criteria exist, but there is little routine screening of these signs and symptoms in clinical practice. Mounting evidence supports a range of pharmacological and non-pharmacological interventions, but relatively few efficacious treatment options exist. Optimising the management of neuropsychiatric presentations in people with Parkinson's disease will require additional research, raised awareness, specialised training, and development of innovative models of care.

Objectives Impulse control disorders (ICDs) are common among patients with Parkinson's disease (PD). Risk factors identified for developing ICDs include young age, family history, and impulsive personality traits. However, the association of these potentially disabling disorders with nondopaminergic drugs and sleep disorders has been understudied. Our objective was to examine the association between ICDs and nondopaminergic medications and sleep disorders. Methods We conducted an observational study of 53 patients with PD from the National Institute of Neurology and Neurosurgery. ICDs were diagnosed using the Questionnaire for Impulsive–Compulsive Disorders in Parkinson's Disease Rating Scale (QUIP‐RS). Patients underwent polysomnography screening to diagnose the presence of sleep disorders. We documented the presence of dopaminergic and nondopaminergic medications, including monoamine oxidase type B inhibitors (MAOBIs), antidepressants, sleep inductors, and antipsychotics. Results ICDs were reported in 18.9% of the patients (n = 10), and sleep disorders were diagnosed in 81.1% of patients (n = 43). 32.1% of the patients were on antidepressants, 17% on MAOBIs, 15.1% on sleep inductors, and 1.9% on antipsychotics. We observed that QUIP‐RS A–D subscore depended on the presence of antidepressants (p = .03) and sleep inductors (p = .02). Sleep disorders were not associated with the total QUIP‐RS score (p = .93) or QUIP‐RS A–D subscore (p = .81). Conclusion Antidepressants and sleep inductors were significant predictors for individual QUIP‐RS items and subscores. Our results suggest that nondopaminergic drugs commonly used for PD may be associated with impulse control disorders. We did not identify a relationship between ICDs and polysomnography‐confirmed sleep disorders in patients with PD. Larger and longitudinal studies are needed to confirm our results. This study examines the association between impulse control disorders (ICDs) and nondopaminergic medications and sleep disorders in patients with Parkinson's disease (PD). Our results suggest that nondopaminergic drugs commonly used for PD may be associated with ICDs. We did not identify a relationship between ICDs and polysomnography‐confirmed sleep disorders in patients with PD.

•Neuropsychiatric symptoms are common in dystonia.•44 patients with craniocervical dystonia and 44 matched controls were included.•Depression and anxiety were frequent in subjects with craniocervical dystonia.•Dementia and pseudobulbar affect were more prevalent in subjects with dystonia.•Mental and physical scores of quality of life were worst in the dystonia group. Depression, anxiety, and obsessive-compulsive disorder have been widely reported in patients with dystonia. On the other hand, cognitive impairment, frontal lobe function, impulsiveness and pseudobulbar affect are less studied. The objective of the study is to assess these neuropsychiatric symptoms along with the quality of life of subjects with craniocervical dystonia. A cross-sectional study was carried out in patients with craniocervical dystonia. Sex- and age-matched healthy controls were included. Neuropsychiatric assessment included the Montreal Cognitive Assessment (MoCA), Frontal Assessment Battery (FAB), Barrat Impulsiveness Scale (BIS-11), Center for Neurologic Study-Lability Scale (CNS-LS), Anxiety Rating Scale (HAM-A), Hamilton Depression Rating Scale (HAM-D), and the 12-item Short Form Health Survey (SF-12). A total of 44 patients with craniocervical dystonia and 44 controls were included. The mean age was 57 ± 13.7 years. Depression (56.1 % vs 9.1 %, p < 0.001), anxiety (56.8 % vs 6.8 %, p < 0.001), and pseudobulbar affect (31.8 % vs 9.1 %, p = 0.02) were more common in the dystonia group in comparison to controls. No difference between groups was found in impulsiveness (p = 0.65), MoCA score (p = 0.14) or executive dysfunction (p = 0.42). Quality of life was worst in the dystonia group with 90.9 % (p = 0.03) and 61.4 % (p < 0.001) of the subjects scoring under average in the Physical Composite Score (PCS) and Mental Composite Score (MCS) of the SF-12. MoCA scores ≤18, pseudobulbar affect, depression and anxiety are more prevalent in subjects with craniocervical dystonia in comparison to sex- and age-matched healthy controls. Regarding quality of life, MCS is more affected that the PCS in subjects with dystonia.

Movement disorders are often a prominent part of the phenotype of many neurologic rare diseases. In order to promote awareness and diagnosis of these rare diseases, the International Parkinson's and Movement Disorders Society Rare Movement Disorders Study Group provides updates on rare movement disorders. In this narrative review, we discuss the differential diagnosis of the rare disorders that can cause chorea. Although the most common causes of chorea are hereditary, it is critical to identify acquired or symptomatic choreas since these are potentially treatable conditions. Disorders of metabolism and mitochondrial cytopathies can also be associated with chorea. The present review discusses clues to the diagnosis of chorea of various etiologies. Authors propose algorithms to help the clinician in the diagnosis of these rare disorders.

Parkinson’s disease (PD) urgently requires blood-based markers that flag pathology before disabling motor decline. This study measured absolute concentrations of 144 plasma metabolites in 20 neurologically healthy adults and in 40 PD patients clinically classified as intermediate (PD-I) or progressive (PD-II). A multinomial logistic regression model was built to examine how changes in metabolite concentrations relate to disease stage and to assess their exploratory discriminative performance in this cohort. Five metabolites: glutamine, butyric acid, indoleacetic acid, phosphatidylcholine aa C40:2, and acylcarnitine C12:1 emerged as the smallest biomarker set that consistently separated controls, PD-I, and PD-II. When three non-motor manifestations often present in the prodromal phase (drooling, REM behavior disorder and depression) were added, the combined profile clearly distinguished controls from early-stage patients and improved classification of intermediate versus progressive disease. The selected metabolites play roles in gut-derived signaling, mitochondrial -oxidation, and membrane lipid homeostasis, while the clinical variables mirror the recognized early spread of -synuclein pathology, together offering a coherent snapshot of systemic changes across PD progression. Because the panel can be quantified from a single small plasma aliquot and a brief clinical interview, it represents a promising exploratory finding that requires validation in larger, independent cohorts before any consideration for clinical application or pre-symptomatic screening.

Purpose. Autonomic dysfunction is a common nonmotor feature and early manifestation of Parkinsons disease (PD). Autonomic dysfunction in PD is associated with a worse prognosis. We sought to characterize autonomic dysfunction and identify associated factors in patients with early PD. Methods. An observational, cross-sectional, descriptive, and analytical study was conducted to evaluate patients with early PD from the Parkinsons Progression Markers Initiative. We utilized the Scales for Outcomes in Parkinsons Disease-Autonomic dysfunction questionnaire to determine the prevalence and frequencies of autonomic symptomatology. The cohort was grouped into high and low dysautonomic scores. A regression model identified variables that independently explained dysautonomic scores in our early PD cohort. Results. 414 PD patients had a mean age of 61.1 (SD 9.7) years at diagnosis and mean disease duration of 6.7 (SD 6.6) months. Among all patients, 43.7% (181/414) had high dysautonomic scores. Urinary and gastrointestinal symptoms were the most prevalent and frequently reported dysautonomic symptoms. Patients with fatigue (beta = 4.28, p<0.001), probable rapid eye movement sleep behavior disorder (beta = 2.71, p<0.001), excessive daytime sleepiness (beta = 1.88,p=0.039), impulsivity and compulsivity (beta = 2.42, p<0.001), and increasing age (beta = 1.05, p<0.001) were more likely to have high dysautonomic scores. Conclusion. Lower urinary tract and gastrointestinal symptoms are prevalent and frequent in early PD patients. Fatigue, sleep disorders, impulsivity and compulsivity, and age are predictors of autonomic dysfunction. Autonomic symptoms predominated in this group of early PD patients in the disease course and were associated with more severe disease.

Background: Parkinson’s disease (PD) presents a significant challenge due to its wide range of motor, non-motor, and treatment-related symptoms. Non-invasive interventions like transcranial magnetic stimulation (TMS) are being explored for potential therapeutic benefits. This study aimed to assess if a high-frequency repetitive TMS protocol (HF-rTMS) consisting of 10 trains of 100 pulses of rTMS at 25 Hz over the motor cortex (M1) at 80% of the resting motor threshold could be effective in treating motor or non-motor symptoms in patients with PD with levodopa-induced dyskinesias. Methods: A randomized, single-blinded, placebo-controlled pilot trial was conducted with eleven PD patients. Nine patients received HF-rTMS, while two received sham stimulation. Patients were exhaustively evaluated using validated clinical scales to assess motor and non-motor symptoms. The study followed a rigorous protocol to avoid bias, with assessments conducted by a neurologist specialized in single-blinded movement disorder. Results: The HF-rTMS group experienced a statistically significant slight worsening in both motor and non-motor symptoms, particularly in the mood/cognition and gastrointestinal domains. However, positive effects were observed in some non-motor symptoms, specifically reduced excessive sweating and weight. No adverse effects were reported. Conclusions: Although HF-rTMS did not produce significant motor improvements, its potential benefit on specific non-motor symptoms, such as autonomic regulation, warrants further investigation.

•Subjects with PD and healthy subjects were included.•Premotor symptoms prevalence was 77.7% in the PD group vs 41.3% in controls.•The presence of non-motor symptoms yield a prediction success of 71.2%. To assess the prevalence of pre-motor symptoms and estimate the risk for developing Parkinson’s disease in Mexican population. A case-control study was carried out with consecutive subjects with Parkinson’s disease from two different referral centers in Mexico. Gender- and age-matched controls were randomly selected from the participating hospitals. All subjects were assessed using a structured questionnaire for the assessment of pre-motor symptoms (hyposmia, depression, anxiety, constipation, and sleep disorders). Odds ratios (OR) were calculated using logistic regression analysis. A total of 430 subjects with PD and 430 healthy subjects were included. Premotor symptoms prevalence was 77.7% (n=334) for the PD group, compared to 41.3% (n=178) in the control group (p<0.001). After logistic multivariate analysis, previous history of hyposmia (OR 2.02 [95% CI 1.33–3.06]), depression (OR 2.52 [95% CI 1.67–3.84]), anxiety (OR 4.37 [95% CI 2.73–6.98]) and sleep disorders (OR 2.03 [95% CI 1.41–2.93]) were independently associated with Parkinson’s disease. Overall prediction success of the model was 81.2% for controls and 61.2% for subjects with PD. All five premotor symptoms assessed were more commonly reported in PD subjects than healthy controls. The presence of non-motor symptoms yield a prediction success of 71.2% to discriminate between PD subjects and healthy controls.