Study Design: Narrative review.
Objectives: To review the relevant literature regarding scoring systems for vertebral metastases and quantify their role in contemporary orthopedic practice.
Methods: A literature search of PubMed, Google Scholar, and Embase was performed on February 7, 2017. Eight scoring systems were selected for detailed review-7 of which were scores focused solely on patient prognosis (Tokuhashi, Tomita, Bauer, Oswestry Spinal Risk Index, Van der Linden, Rades, and Katagiri). The eighth system reviewed was the Spinal Instability Neoplastic Score, which examines for impending spinal instability in patients with vertebral metastases and represents a novel approach compared with hitherto scoring systems.
Results: The Bauer and Oswestry Spinal Risk Index have the most accurate prognostic predictive ability, with the newer Oswestry Spinal Risk Index being favored by the contemporary literature as it demands less investigation and is therefore more readily accessible. There was a growing trend in studies designed to customize scoring systems for individual cancer pathological subtypes. The Spinal Instability Neoplastic Score shows good reliability for predicting instability among surgeons and oncologists.
Conclusions: The increased understanding of cancer pathology and subsequent development of customized treatments has led to prolonged survival. For patients with vertebral metastases, this affects surgical candidacy not only on the basis of prognosis but also provides prolonged opportunity for the development of spinal instability. Scoring systems have a useful guidance role in these deciding for/against surgical intervention, but in order to remain contemporary ongoing review, development, and revalidation is mandatory.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125937 | PMC |
| http://dx.doi.org/10.1177/2192568217750125 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A study to identify individuals at risk to be affected by late-onset Pompe disease who had previously been given a non-specific or tentative diagnosis for their muscle weakness (Pompe PURSUE).
Orphanet J Rare Dis
January 2025
Department of Human Genetics, Emory University, Atlanta, GA, USA.
Background: Late-onset Pompe disease (LOPD) is an autosomal recessive lysosomal storage disorder that results in severe progressive proximal muscle weakness. Over time, reductions in muscle strength result in respiratory failure and a loss of ambulation. Delayed diagnosis of LOPD deprives patients of treatments that can enhance quality of life and potentially slow disease progression.
View Article and Find Full Text PDFHead-mounted camera as a debriefing tool for surgical simulation-based training: a randomized controlled study in Senegal.
BMC Med Educ
January 2025
Department of Surgery, Saint-Louis Regional Hospital, Gaston Berger University, Road of Ngallelle, 234, Saint-Louis, Senegal.
Introduction: Video feedback, particularly with a head-mounted camera, has previously been described as a useful debriefing tool in well-funded health systems but has never been performed in a low-resource environment. The purpose of this randomized, intervention-controlled study is to evaluate the feasibility of using video feedback with a head-mounted camera during intestinal anastomosis simulation training in a low-resource setting.
Methodology: This study recruited 14 first-year surgery residents in Senegal, who were randomized into control and camera groups.
Assessment of using transfer learning with different classifiers in hypodontia diagnosis.
BMC Oral Health
January 2025
Pediatric Dentistry Department, Faculty of Dentistry, Başkent University, 06490, Ankara, Turkey.
Background: Hypodontia is the absence of one or more teeth in the primary or permanent dentition during development, and radiographic imaging is the most common method of diagnosis. However, in recent years, artificial intelligence-based decision support systems have been employed to make highly accurate diagnoses. The aim of this study was to classify single premolar agenesis, multiple premolar agenesis, and without tooth agenesis using various artificial intelligence approaches.
View Article and Find Full Text PDFEstablishing a GRU-GCN coordination-based prediction model for miRNA-disease associations.
BMC Genom Data
January 2025
Department of Management Information Systems, National Chung Hsing University, Taichung, 402, Taiwan.
Background: miRNAs (microRNAs) are endogenous RNAs with lengths of 18 to 24 nucleotides and play critical roles in gene regulation and disease progression. Although traditional wet-lab experiments provide direct evidence for miRNA-disease associations, they are often time-consuming and complicated to analyze by current bioinformatics tools. In recent years, machine learning (ML) and deep learning (DL) techniques are powerful tools to analyze large-scale biological data.
View Article and Find Full Text PDFCan surface topography reliably determine the Rigo classification system?
Eur Spine J
January 2025
Department of Orthopaedic Surgery, Medical College of Wisconsin, Milwaukee, USA.
Purpose: No studies have explored the reliability of the Rigo classification system using surface topography (ST), which would allow optimization without radiation exposure. This study aims to measure and compare the intra- and inter-observer reliability (Kappa values) and accuracy of the Rigo system between ST and X-ray for overall types and subtypes.
Methods: X-ray and ST images of 31 adolescent idiopathic scoliosis patients were selected.
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!