BACKGROUND: Early, simple predictors for long-term survival in Parkinson\'s disease (PD) may help identify patients at elevated risk and are crucial for more personalized treatment.
METHODS: This large, retrospective study examined whether higher levodopa equivalent daily dose (LEDD) a year after diagnosis predicts long-term survival.
RESULTS: Mortality risk was increased among 292 patients receiving ≥ 600 mg LEDD versus 2233 patients receiving < 600 mg LEDD (hazard ratio 1.5; 95% confidence interval 1.3-1.7), particularly among patients aged < 75 years (1.8; 1.4-2.4).
CONCLUSIONS: In PD, higher LEDD can be an early risk marker of increased mortality, probably because it reflects more severe disease.

The ability to perform activities of daily living (ADL) function is a multifaceted construct that reflects functionality in different daily life situations. The loss of ADL function due to cognitive impairment is the core feature for the diagnosis of Parkinson\'s disease dementia (PDD). In contrast to Alzheimer\'s disease, ADL impairment in PD can be compromised by various factors, including motor and non-motor aspects. This narrative review summarizes the current state of knowledge on the association of cognition and ADL function in people with PD and introduces the concept of \"cognitive ADL\" impairment for those problems in everyday life that are associated with cognitive deterioration as their primary cause. Assessment of cognitive ADL impairment is challenging because self-ratings, informant-ratings, and performance-based assessments seldomly differentiate between \"cognitive\" and \"motor\" aspects of ADL. ADL function in PD is related to multiple cognitive domains, with attention, executive function, and memory being particularly relevant. Cognitive ADL impairment is characterized by behavioral anomalies such as trial-and-error behavior or task step omissions, and is associated with lower engagement in everyday behaviors, as suggested by physical activity levels and prolonged sedentary behavior. First evidence shows that physical and multi-domain interventions may improve ADL function, in general, but the evidence is confounded by motor aspects. Large multicenter randomized controlled trials with cognitive ADL function as primary outcome are needed to investigate which pharmacological and non-pharmacological interventions can effectively prevent or delay deterioration of cognitive ADL function, and ultimately the progression and conversion to PDD.

UNASSIGNED: High-quality evidence shows that exercise helps people with Parkinson\'s disease improve functional abilities including balance. However, few studies have investigated whether the setting and format through which balance-focused exercise programs are provided matters. This systematic review investigated group exercise compared to individual exercise, and to no-exercise control (CTL), on clinical measures of balance for people with Parkinson\'s disease.
UNASSIGNED: MEDLINE, EMBASE, CINAHL and Cochrane CENTRAL databases were searched through March 24, 2024, on terms for Parkinson\'s disease; exercise or physical activity; community-based or group classes; balance or postural control. Citations, abstracts and full-text articles were independently reviewed, and included studies were rated on risk of bias by two authors.
UNASSIGNED: Twenty-seven randomized controlled trials (30 reports) with 1200 participants met criteria. Meta-analysis using mean difference (MD) compared group exercise to CTL on seven clinical measures of balance. Three yielded significant differences favoring group exercise: Timed Up and Go = -2.29 (MD), -3.56 to -1.02 (95% Confidence interval) (95% CI); Mini-BEST = 2.72 (MD), 1.88 to 3.57 (95% CI); Berg Balance Scale = 4.31 (MD), 1.33 to 7.29 (95% CI). Meta-analyses were also conducted on six clinical measures of balance, comparing group exercise to individual exercise, yielding no significant differences.
UNASSIGNED: For people with Parkinson\'s disease, group exercise may be more effective than CTL on some clinical measures of balance and it yields similar results to individual exercise. People with Parkinson\'s disease are encouraged to participate regularly in group or individual exercise based on preference and accessibility.

Parkinson\'s disease (PD) is a common and slow-progressing neurodegenerative disorder characterized by motor and non-motor symptoms, including gastrointestinal (GI) dysfunctions. Over the last years, the microbiota-gut-brain (MGB) axis is emerging as a bacterial-neuro-immune ascending pathway that contributes to the progression of PD. Indeed, PD patients are characterized by changes in gut microbiota composition, alterations of intestinal epithelial barrier (IEB) and enteric neurogenic/inflammatory responses that, besides determining intestinal disturbances, contribute to brain pathology. In this context, despite the causal relationship between gut dysbiosis, impaired MGB axis and PD remains to be elucidated, emerging evidence shows that MGB axis modulation can represent a suitable therapeutical strategy for the treatment of PD. This review provides an overview of the available knowledge about the beneficial effects of gut-directed therapies, including dietary interventions, prebiotics, probiotics, synbiotics and fecal microbiota transplantation (FMT), in both PD patients and animal models. In this context, particular attention has been devoted to the mechanisms by which the modulation of MGB axis could halt or slow down PD pathology and, most importantly, how these approaches can be included in the clinical practice.

UNASSIGNED: Intersectionality approaches to examining differences in Parkinson\'s disease (PD) based on racialized group, gender identity, and socioeconomic status (SES) are not well covered in the literature. Additionally, the differences in daily cognitive activities for persons diagnosed with PD by racialized group, gender, and SES are undetermined. This study was conducted to explore the differences in PD daily cognitive activities for diverse racialized groups by gender and SES.
UNASSIGNED: This study was a secondary analysis of the Michael J. Fox Foundation\'s Fox Insight online clinical dataset. Persons with PD were partitioned into 16 racialized by gender groups (Black women, Indigenous men, Latina/x women, Asian men, etc.) that were used in within-group comparisons of low-, middle-, and high-SES-a new variable comprising education and income.
UNASSIGNED: Intersectional analyses revealed most items differed between low-SES and high-SES except for items associated with Black and Indigenous men, for whom significant differential item functioning was found between mid-SES and high-SES.
UNASSIGNED: These findings revealed that within-group differences exist and may be missed in research in which social factors are adjusted for instead of included in the model.

Parkinson\'s disease (PD) is the second most common neurodegenerative disorder, globally affecting men and women at an exponentially growing rate, with currently no cure. Disease progression starts when dopaminergic neurons begin to die. In PD, the loss of neurotransmitter, dopamine is responsible for the overall communication of neural cells throughout the body. Clinical symptoms of PD are slowness of movement, involuntary muscular contractions, speech & writing changes, lessened automatic movement, and chronic tremors in the body. PD occurs in both familial and sporadic forms and modifiable and non-modifiable risk factors and socioeconomic conditions cause PD. Early detectable diagnostics and treatments have been developed in the last several decades. However, we still do not have precise early detectable biomarkers and therapeutic agents/drugs that prevent and/or delay the disease process. Recently, artificial intelligence (AI) science and machine learning tools have been promising in identifying early detectable markers with a greater rate of accuracy compared to past forms of treatment and diagnostic processes. Artificial intelligence refers to the intelligence exhibited by machines or software, distinct from the intelligence observed in humans that is based on neural networks in a form and can be used to diagnose the longevity and disease severity of disease. The term Machine Learning or Neural Networks is a blanket term used to identify an emerging technology that is created to work in the way of a \"human brain\" using many intertwined neurons to achieve the same level of raw intelligence as that of a brain. These processes have been used for neurodegenerative diseases such as Parkinson\'s disease and Alzheimer\'s disease, to assess the severity of the patient\'s condition. In the current article, we discuss the prevalence and incidence of PD, and currently available diagnostic biomarkers and therapeutic strategies. We also highlighted currently available artificial intelligence science and machine learning tools and their applications to detect disease and develop therapeutic interventions.

BACKGROUND: In 2023, the German Society of Neurology published a new guideline on Parkinson\'s disease. An important section dealt with PD care concepts, which represent a particularly dynamic field of PD research, including their implementation in clinical practice. Parkinson\'s disease is the second most common age-associated neurodegenerative disease. Current estimates of the number of cases in the population describe a significant increase in prevalence in Germany by 2030 with higher proportions in rural areas, which also have a lack of sufficient PD care resources.
CONCLUSIONS: In comparison with other international guidelines, which have so far mentioned palliative care and Parkinson\'s nurses in particular, the German S2k guideline expands the recommended concepts of PD care to include PD day clinics, inpatient complex treatment, and PD networks.
CONCLUSIONS: Concepts of PD care guidelines are necessary because of the complex and rapidly evolving field of PD care provision. If applied appropriately, the potential for optimized care can be exploited and both the patient burden and the economic burden can be reduced. Given that modern care concepts have so far only been applied in a few regions, it is often impossible to generate broad evidence-based data, so that the evaluation of PD care concepts is partly dependent on expert opinion.

OBJECTIVE: Deep brain stimulation (DBS) targeting the globus pallidus interna (GPi) has been shown to significantly improve motor symptoms for the treatment of medication-refractory Parkinson\'s disease. Yet, heterogeneity in clinical outcomes persists, possibly due to suboptimal target identification within the GPi. By leveraging robust sampling of the GPi and 6-month postsurgical outcomes, this study aims to determine optimal symptom-specific GPi DBS targets.
METHODS: In this study, the authors analyzed the anatomical lead location and 6-month postsurgical, double-blinded outcome measures of 86 patients who underwent bilateral GPi DBS. These patients were selected from the multicenter Veterans Affairs (VA)/National Institutes of Neurological Disorders and Stroke (NINDS) Cooperative Studies Program (CSP) 468 study to identify the optimal target zones (\"sweet spots\") for the control of overall motor (United Parkinson\'s Disease Rating Scale [UPDRS]-III), axial, tremor, rigidity, and bradykinesia symptoms. Lead coordinates were normalized to Montreal Neurological Institute space and the optimal target zones were identified and validated using a leave-one-patient-out approach.
RESULTS: The authors\' findings revealed statistically significant optimal target zones for UPDRS-III (R = 0.37, p < 0.001), axial (R = 0.22, p = 0.042), rigidity (R = 0.20, p = 0.021), and bradykinesia (R = 0.23, p = 0.004) symptoms. These zones were localized within the primary motor and premotor subdivisions of the GPi. Interestingly, these zones extended beyond the GPi lateral border into the GPi-globus pallidus externa (GPe) lamina and into the GPe, but they did not reach the GPi ventral border, challenging traditional surgical approaches based on pallidotomies.
CONCLUSIONS: Drawing upon a robust dataset, this research effectively delineates specific optimal target zones for not only overall motor improvement but also symptom subscores. These insights hold the potential to enhance the precision of targeting in subsequent bilateral GPi DBS surgical procedures.

This manuscript reviews the significant skin manifestations of Lewy body disease, including Parkinson\'s disease and dementia with Lewy bodies, and the diagnostic utility of skin biopsy. Besides classic motor and cognitive symptoms, non-motor manifestations, particularly dermatologic disorders, can play a crucial role in disease presentation and diagnosis. This review explores the intricate relationship between the skin and Lewy body disease. Seborrheic dermatitis, autoimmune blistering diseases (bullous pemphigoid and pemphigus), rosacea, and melanoma are scrutinized for their unique associations with Parkinson\'s disease, revealing potential links through shared pathophysiological mechanisms. Advances in diagnostic techniques allow the identification of promising biomarkers such as α-synuclein in samples obtained by skin punch biopsy. Understanding the dermatologic aspects of Lewy body disease not only contributes to its holistic characterization but also holds implications for innovative diagnostic approaches.

Brain-derived neurotrophic factor (BDNF) and glycolipid metabolism have been implicated in cognitive impairments and depression among Parkinson\'s disease (PD). However, the role of sex differences in this relationship remains elusive. This study aimed to investigate the potential sex differences in the link between serum BDNF levels, glycolipid metabolism and cognitive performance among depressive PD patients. PD patients comprising 108 individuals with depression and 108 without depression were recruited for this study. Cognitive function was assessed using the Montreal Cognitive Assessment Beijing version (MOCA-BJ). The severity of depressive symptoms was assessed using the Hamilton Depression Rating Scale (HAMD-17), while motor symptoms were evaluated using the Revised Hoehn and Yahr rating scale (H-Y) and the Unified Parkinson\'s Disease Rating Scale Part III (UPDRS-III). Laboratory testing and enzyme-linked immunosorbent assay (ELISA) are used to measure serum levels of glycolipid metabolism and BDNF. Females showed superior performance in delayed recall (all p < 0.05), male PD patients exhibited higher scores in naming tasks compared to females in non-depression group. There was no sex differences in serum BDNF levels between depression and non-depression groups. Liner regression analysis indicated BDNF as an independent risk factor for language deficits in male PD patients with depression (p < 0.05), while cholesterol (CHOL) emerged as a cognitive influencing factor, particularly in delayed recall among male PD patients with depression (p < 0.05). Our study reveals extensive cognitive impairments in PD patients with depression. Moreover, BDNF and CHOL may contribute to the pathological mechanisms underlying cognitive deficits, particularly in male patients with depression.