Subthalamic deep brain stimulation (STN-DBS) for refractory Parkinson's disease (PD) is more of a modality of treatment that is empirical, for which a physiological explanation is being sought. This study was done to determine the outcome and complications of patients undergoing STN-DBS for PD. This retrospective observational cohort study was conducted in an advanced neuromedicine facility in eastern India for 9 years (August 2013-August 2022), which included all patients undergoing STN-DBS. A total of 53 patients were operated on during the study period. The mean age group of the study population was 60.5 (standard deviation [SD]: 8.2) years with a male (33 [62.3%]) predominance. The most common presenting complaints included rigidity and hypokinesia (27), severe dyskinesia (21), and tremors (17). During the postoperative period, rigidity and hypokinesia (21), severe dyskinesia (16), and tremors (12) improved significantly in a subset of the patients. The majority (45 [84.9%]) of these cases received bilateral monopolar simulation, whereas three patients (5.7%) had bilateral bipolar stimulation. Unilateral bipolar stimulation was used in five (9.4%) patients. In the immediate postoperative period, they were initiated on limb, speech, and swallowing therapy as indicated. Surgery-related complications were seen in five (9.4%) cases. At 6 months of follow-up, a significant improvement in the Unified PD rating scale component (mainly motor examination and complication of PD therapy) was noted in the majority (36 [67.9%]) of patients. One patient developed neuroleptic malignant syndrome and succumbed to his illness on the fourth postoperative day. Given these findings, STN-DBS appears to be a good, safe, and effective treatment for a subset of medically refractory PD with an overall improvement in two-thirds of the study cohort and less than 10% risk of complications.
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http://dx.doi.org/10.1055/s-0043-1771318 | DOI Listing |
Comput Struct Biotechnol J
January 2025
Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, NY, USA.
Despite the wealth of single-cell multi-omics data, it remains challenging to predict the consequences of novel genetic and chemical perturbations in the human body. It requires knowledge of molecular interactions at all biological levels, encompassing disease models and humans. Current machine learning methods primarily establish statistical correlations between genotypes and phenotypes but struggle to identify physiologically significant causal factors, limiting their predictive power.
View Article and Find Full Text PDFNetwork
January 2025
Department of Electrical and Electronics Engineering, University College of Engineering Thirukkuvalai - A Constituent College of Anna University, Thirukkuvalai, Tamil Nadu, India.
Brain-controlled robotic arm systems are designed to provide a method of communication and control for individuals with limited mobility or communication abilities. These systems can be beneficial for people who have suffered from a spinal cord injury, stroke, or neurological disease that affects their motor abilities. The ability of a person to control a robotic arm to reach and grasp multiple objects using their brain signals.
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Department of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de la Sallaz 8, CH-1011, Lausanne, Switzerland.
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Clin Neuroradiol
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Department of Neurology, Klinikum rechts der Isar, School of Medicine and Health, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
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View Article and Find Full Text PDFNeuroimage
January 2025
Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea. Electronic address:
A recently introduced quantitative susceptibility mapping (QSM) technique, χ-separation, offers the capability to separate paramagnetic (χ) and diamagnetic (χ) susceptibility distribution within the brain. In-vivo high-resolution mapping of iron and myelin distribution, estimated by χ-separation, could provide a deeper understanding of brain substructures, assisting the investigation of their functions and alterations. This can be achieved using 7T MRI, which benefits from a high signal-to-noise ratio and susceptibility effects.
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