AI Article Synopsis

  • The article details a case of a teenage girl diagnosed with juvenile parkinsonism caused by genetic mutations, showcasing the challenges in diagnosing and treating this condition alongside other psychiatric disorders.
  • Despite years of psychiatric evaluations and treatments, clear symptoms of parkinsonism only emerged later, complicating the diagnosis.
  • It emphasizes the need for a collaborative approach between psychiatrists and neurologists for accurate diagnosis and effective treatment in cases with overlapping symptoms.

Article Abstract

The article presents a case of a teenage female patient illustrating the difficulties of diagnosis and treatment of mental pathology at the onset of juvenile parkinsonism, which developed as a result of compound heterozygous mutations and proceeds with moderate akinetic-rigid and pseudopyramidal syndromes and combined tremor. It is shown that before the appearance of distinct symptoms of parkinsonism and the genetic study that confirmed the diagnosis, the patient had been observed for several years with various psychiatric diagnoses and received psychotropic therapy. This case demonstrates the difficulties of differential diagnosis of juvenile parkinsonism in children at the initial stage due to multiple comorbid motor, affective and behavioral disorders. When neurological symptoms appear in patients, a multidisciplinary approach is required, including joint diagnostics by psychiatrists and neurologists to establish an accurate diagnosis and select the optimal therapy. The introduction of principles of interdisciplinary interaction in the management of such patients will improve the timeliness of diagnosis and pathogenetically based therapy.

Download full-text PDF

Source
http://dx.doi.org/10.17116/jnevro202412411296DOI Listing

Publication Analysis

Top Keywords

juvenile parkinsonism
12
onset juvenile
8
diagnosis
5
[psychopathological disorders
4
disorders onset
4
parkinsonism
4
parkinsonism childhood]
4
childhood] article
4
article presents
4
presents case
4

Similar Publications

Background: There had been extensive research on the role of the gut microbiota in human health and disease. Increasing evidence suggested that the gut-brain axis played a crucial role in Parkinson's disease, with changes in the gut microbiota speculated to be involved in the pathogenesis of Parkinson's disease or interfere with its treatment. However, studies utilizing deep learning methods to predict Parkinson's disease through the gut microbiota were still limited.

View Article and Find Full Text PDF

Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.

Sensors (Basel)

December 2024

School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, ON K1N 6N5, Canada.

Freezing of gait (FOG) is a walking disturbance that can lead to postural instability, falling, and decreased mobility in people with Parkinson's disease. This research used machine learning to predict and detect FOG episodes from plantar-pressure data and compared the performance of decision tree ensemble classifiers when trained on three different datasets. Dataset 1 ( = 11) was collected in a previous study.

View Article and Find Full Text PDF

Safety of Immersive Virtual Reality for the Management of Parkinson's Disease.

Sensors (Basel)

December 2024

Centro de Estudos Egas Moniz, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal.

Virtual reality (VR) has been used in research and clinical practice in the management of Parkinson's disease (PD), potentially enhancing physiotherapy. Adverse events (AEs) associated with VR applications in PD have been poorly explored. We conducted a randomized controlled trial to compare two 12-week interventions using physiotherapy and immersive VR, and analyzed the frequency and type of AEs occurring in 30 people with PD.

View Article and Find Full Text PDF

Machine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging.

Sensors (Basel)

December 2024

Faculty of Computer Science, Polish-Japanese Academy of Information Technology, 86 Koszykowa Street, 02-008 Warsaw, Poland.

Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early detection is crucial for effective intervention strategies, this study investigates whether the structural analysis of selected brain regions, including volumes and their spatial relationships obtained from regular T1-weighted MRI scans ( = 168, PPMI database), can model stages of PD using standard machine learning (ML) techniques. Thus, diverse ML models, including Logistic Regression, Random Forest, Support Vector Classifier, and Rough Sets, were trained and evaluated.

View Article and Find Full Text PDF

Mobility tasks like the Timed Up and Go test (TUG), cognitive TUG (cogTUG), and walking with turns provide insights into the impact of Parkinson's disease (PD) on motor control, balance, and cognitive function. We assess the test-retest reliability of these tasks in 262 PD participants and 50 controls by evaluating machine learning models based on wearable-sensor-derived measures and statistical metrics. This evaluation examines total duration, subtask duration, and other quantitative measures across two trials.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!