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What is the Optimal Management of Metastatic Spine Patients With Intermediate Spinal Instability Neoplastic Scores: To Operate or Not to Operate?
Global Spine J
January 2025
Combined Neurosurgical and Orthopedic Spine Program, Department of Orthopedics Surgery, University of British Columbia, Vancouver, BC, Canada.
Study Design: Systematic review.
Objective: In patients with extradural metastatic spine disease, we sought to systematically review the outcomes and complications of patients with intermediate Spinal Instability Neoplastic Score (SINS) lesions undergoing radiation therapy, percutaneous interventions, minimally invasive surgeries, or open spinal surgeries.
Methods: Following PRISMA guidelines for systematic reviews, MEDLINE, EMBASE, Web of Science, the Cochrane Database of Systematic Reviews and the Cochrane Center Register of Controlled Trials were queried for studies that reported on SINS intermediate patients who underwent: 1) radiotherapy, 2) percutaneous intervention, 3) minimally invasive, or 4) open surgery.
The effect of time to neurosurgical or neuroradiological intervention therapy on outcomes and quality of care after traumatic brain injury, a registry-based observational study.
Int J Emerg Med
December 2024
Traumatology and Critical Care Medical Center, National Hospital Organization Osaka National Hospital, Osaka, Japan.
Background: Evidence regarding the effect of time to neurosurgical and neuroradiological intervention on outcomes in traumatic brain injury (TBI) across Asia-Pacific region is limited. This study evaluates the quality of care and outcomes for TBI patients undergoing neurosurgical and neuroradiological procedures at different timings.
Methods: Adult TBI patients who received any neurosurgical or neuroradiological interventions during the year 2015-2022 in the Pan-Asian Trauma Outcome Study database were analyzed.
Association between perforator stroke after middle cerebral artery elective stenting and arterial remodeling patterns: a high-resolution MRI-based retrospective cohort study.
Quant Imaging Med Surg
December 2024
Department of Neurointervention, the First Affiliated Hospital of Zhengzhou University, Henan Provincial Neurointerventional Engineering Research Center, Zhengzhou, China.
Background: Patterns of arterial remodeling may be associated with outcomes in patients with severe middle cerebral artery (MCA) stenosis after endovascular treatment (EVT). This study aims to investigate the potential correlation between arterial remodeling patterns in patients with severe MCA stenosis, and plaque characteristics and procedure-related perforator stroke (PS).
Methods: Consecutive patients with MCA atherosclerotic disease who underwent EVT at the First Affiliated Hospital of Zhengzhou University from January 2018 to June 2023 were retrospectively enrolled in this study.
Unnecessary Scans Lead to Unnecessary Re-scans: Evaluating Clinical Management of Low and Intermediate Risk Pediatric Traumatic Brain Injuries.
J Pediatr Surg
February 2025
Department of Surgery, New Haven, CT 06510, USA; Yale University School of Medicine, New Haven, CT 06510, USA.
Background: The Pediatric Emergency Care Applied Research Network (PECARN) guidelines provide an algorithm to select patients with mild head trauma at highest risk for clinically important traumatic brain injury (ciTBI) in whom computed tomography (CT) would facilitate management. Failure to follow PECARN criteria exposes children to unnecessary radiation and contributes to increasing hospital costs, length of stay, and parental anxiety. We sought to evaluate the subsequent allocation of resources to low and intermediate risk group patients who underwent an initial Head CT - which was not indicated by PECARN guidelines but which identified cranial or intracranial injury.
View Article and Find Full Text PDFMachine Learning-based Prognostic Subgrouping of Glioblastoma: A Multi-center Study.
Neuro Oncol
December 2024
Center for Data Science and AI for Integrated Diagnostics (AI2D), and Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
Background: Glioblastoma is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification.
Methods: We developed a highly reproducible, personalized prognostication and clinical subgrouping system using machine learning (ML) on routine clinical data, MRI, and molecular measures from 2,838 demographically diverse patients across 22 institutions and 3 continents. Patients were stratified into favorable, intermediate, and poor prognostic subgroups (I, II, III) using Kaplan-Meier analysis (Cox proportional model and hazard ratios [HR]).
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