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Parkinson's Disease: Diagnosis, Treatment, and Management
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Parkinson's Disease: Diagnosis, Treatment, and Management

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Neurology".

Deadline for manuscript submissions: closed (25 February 2025) | Viewed by 1451

Special Issue Editor

Dr. Ranjeet Kumar

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Guest Editor
Department of Pharmacology, Physiology, Neuroscience, NJMS, Rutgers University, Newark, NJ 07103, USA
Interests: neurodegenerative disorders; Parkinson’s disease; autophagy; diagnostics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neurodegenerative disorders are very common in aged people, which severely affect their quality life as well as that of their caretakers. Parkinson’s is one of the most common diseases in aged populations after Alzheimer’s disease. More than 10 million people have Parkinson’s around the globe. However, each year, more than 90,000 patients are diagnosed with PD alone in United States only. Incidences of Parkinson’s increases with age, mostly 65 years or older. Parkinsonian symptoms include motor (tremor, muscle stiffness, impaired balance, and coordination) as well as non-motor symptoms (speaking, swallowing, chewing, constipation, etc.). With disease progression and duration of treatment drugs, response also decreases, which results into very serious conditions for patients as well as for their caretakers.

This Special Issue will focus on the Parkinson’s disease research, specifically in the area of biomarker development for early detection and therapeutic progression, new active compounds, and molecular interventions for the treatment and management of Parkinson’s disease. Both original research papers and review papers are welcome.

Dr. Ranjeet Kumar
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Parkinson’s
  • early diagnosis of Parkinson’s
  • therapeutics
  • molecular interventions

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Published Papers (2 papers)

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Research

17 pages, 430 KiB  
Article
Predicting Freezing of Gait in Parkinson’s Disease: A Machine-Learning-Based Approach in ON and OFF Medication States
by Georgios Bouchouras, Georgios Sofianidis and Konstantinos Kotis
J. Clin. Med. 2025, 14(6), 2120; https://doi.org/10.3390/jcm14062120 - 20 Mar 2025
Viewed by 377
Abstract
Background: Freezing of gait (FoG) is a debilitating motor symptom of Parkinson’s disease (PD), characterized by sudden episodes where patients struggle to initiate or sustain movement, often describing a sensation of their feet being “glued to the ground.” This study investigates the [...] Read more.
Background: Freezing of gait (FoG) is a debilitating motor symptom of Parkinson’s disease (PD), characterized by sudden episodes where patients struggle to initiate or sustain movement, often describing a sensation of their feet being “glued to the ground.” This study investigates the potential of machine-learning (ML) models to predict FoG severity in PD patients, focusing on the influence of dopaminergic medication by comparing gait parameters in ON and OFF medication states. Methods: Specifically, this study employed spatiotemporal gait features to develop a predictive model for FoG severity, leveraging a random forest regressor to identify the most influential gait parameters associated with this in each medication state. The results indicate that the model achieved higher predictive performance in the OFF-medication condition (R² = 0.82, MAE = 2.25, MSE = 15.23) compared to the ON-medication condition (R² = 0.52, MAE = 4.16, MSE = 42.00). Results: These findings suggest that dopaminergic treatment alters gait dynamics, potentially reducing the reliability of FoG predictions when patients are medicated. Feature importance analysis revealed distinct gait characteristics associated with FoG severity across medication states. In the OFF condition, step length parameters, particularly left step length mean, were the most dominant predictors, alongside swing time and stride width, indicating the role of spatial and temporal gait control in FoG severity without medication. In contrast, under the ON medication condition, stride width and gait speed emerged as the most influential predictors, followed by stepping frequency, reflecting how medication influences stability and movement rhythm. Conclusions: These findings highlight the need for predictive models that account for medication-induced gait variability, ensuring more reliable FoG detection. By integrating spatiotemporal gait analysis and ML-based prediction, this study contributes to the development of personalized intervention strategies for PD patients experiencing FoG episodes. Full article
(This article belongs to the Special Issue Parkinson's Disease: Diagnosis, Treatment, and Management)
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12 pages, 731 KiB  
Article
Association Between Levodopa with Inotrope Prescription and Mechanical Ventilation Dependence in People with Parkinson’s Disease upon Septic Shock
by Yun-Yung Cheng, Chien-Tai Hong, Li-Ying Chen, Yu-Hsuan Shao, Wei-Ting Chiu and Lung Chan
J. Clin. Med. 2025, 14(3), 748; https://doi.org/10.3390/jcm14030748 - 24 Jan 2025
Viewed by 623
Abstract
Background/Objectives: People with Parkinson’s disease (PwP) face high risks of bacterial infections and septic shock, often requiring inotrope treatment and mechanical ventilation. The impact of levodopa on these critical care interventions remains unclear. Methods: This retrospective cohort study analyzed data from [...] Read more.
Background/Objectives: People with Parkinson’s disease (PwP) face high risks of bacterial infections and septic shock, often requiring inotrope treatment and mechanical ventilation. The impact of levodopa on these critical care interventions remains unclear. Methods: This retrospective cohort study analyzed data from the Taipei Medical University Clinical Research Database to explore the relationship between levodopa prescription, inotrope treatment duration, and mechanical ventilation dependence in PwP who experienced septic shock. PwP aged 45 years and older who required intensive care for septic shock were categorized into levodopa and non-levodopa groups. Results: Outcomes included inotrope treatment duration, mechanical ventilation dependence, and 3-month mortality. Among 243 PwP (116 without levodopa, 127 with levodopa), no significant difference was observed in the duration of mechanical ventilation dependence. However, levodopa prescription was associated with a significantly extended inotrope treatment duration (estimate: 3.43 days, p = 0.027). Additionally, a nonsignificant trend was identified between levodopa prescription and reduced 3-month mortality (adjusted hazard ratio = 0.67, p = 0.068). Conclusions: These findings highlight the complex interplay between Parkinson’s disease management and critical care interventions during septic shock. While levodopa may prolong inotrope use, its potential to influence survival outcomes warrants further investigation. Full article
(This article belongs to the Special Issue Parkinson's Disease: Diagnosis, Treatment, and Management)
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