Study Design: A prospective multicenter study and retrospective chart review.
Objective: To compare health-related quality of life (HRQOL) measures and sagittal deformity in operative Scheuermann kyphosis (SK), operative adolescent idiopathic scoliosis (AIS), and normal populations.
Summary Of Background Data: No study to date has evaluated patient reported HRQOL measures before surgery in operative patients with SK.
Methods: HRQOL data were prospectively collected pretreatment for operative patients with SK using the SRS-22 outcomes instrument and visual analogue scale (VAS). Comparison was made with the SRS-22 from operative AIS and normal populations. Eighty-six patients with SK enrolled in the prospective study were compared with 184 patients with AIS from a prospective database and 31 normal controls. To study the correlation between T5-T12 kyphosis magnitude and SRS-22 score, patients with AIS and SK were pooled together to create a larger continuum of kyphosis. Analysis of covariance, Pearson correlation analysis, and Bonferroni pairwise comparisons were used to determine statistical differences between group demographics, HRQOL indicators, and radiographical variables.
Results: Patients with SK had significantly lower scores in all domains of the SRS-22 than patients with AIS. Patients with SK with a thoracolumbar apex reported significantly lower mean scores in the pain domain than those with a thoracic apex. Significant negative correlations were found between all domains of the SRS-22 and T5-T12 kyphosis-the self-image domain demonstrated the highest correlation (r = 0.37). VAS score in the SK population correlated negatively to the pain, self-image, and mental health domains.
Conclusion: Increasing sagittal plane deformity as a result of SK has a significant impact on HRQOL as determined by the SRS-22 outcome instrument. In this study, patients with SK reported significantly decreased (worse) scores in all subdomains of the SRS-22 compared with patients with AIS.
Level Of Evidence: 1.
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http://dx.doi.org/10.1097/BRS.0b013e3182893c01 | DOI Listing |
Front Neurol
December 2024
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Objective: To establish and validate a model based on hyperdense middle cerebral artery sign (HMCAS) radiomics features for predicting hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) after endovascular treatment (EVT).
Methods: Patients with AIS who presented with HMCAS on non-contrast computed tomography (NCCT) at admission and underwent EVT at three comprehensive hospitals between June 2020 and January 2024 were recruited for this retrospective study. A radiomics model was constructed using the HMCAS radiomics features most strongly associated with HT.
Front Neurol
December 2024
Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Background: Low-density lipoprotein cholesterol (LDL-C) has been determined as an established risk factor for acute ischemic stroke (AIS). Despite the recommendation for in-hospital initiation of high-intensity statin therapy in AIS patients, achieving the desired target LDL-C levels remains challenging. Evolocumab, a highly effective and quickly acting agent for reducing LDL-C levels, has yet to undergo extensively exploration in the acute phase of AIS.
View Article and Find Full Text PDFFront Oncol
December 2024
Department of Respiratory and Critical Care Medicine, Center for Respiratory Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China.
Artificial intelligence (AI) has significantly impacted various fields, including oncology. This comprehensive review examines the current applications and future prospects of AI in lung cancer research and treatment. We critically analyze the latest AI technologies and their applications across multiple domains, including genomics, transcriptomics, proteomics, metabolomics, immunomics, microbiomics, radiomics, and pathomics in lung cancer research.
View Article and Find Full Text PDFHealth Sci Rep
January 2025
Department of Microbiology Dr D. Y. Patil Medical College, Hospital and Research Centre, Dr D. Y. Patil Vidyapeeth (Deemed-to-be-University) Pune Maharashtra India.
Background And Aims: Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering in a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. The goal of this review is to present a thorough analysis of AI's effects on healthcare while providing stakeholders with a road map for navigating this changing environment.
View Article and Find Full Text PDFAsian Spine J
December 2024
Department of Spine Surgery, Bombay Hospital and Medical Research Centre, Mumbai, India.
Study Design: A retrospective comparative study.
Purpose: To validate the hypothesis that a combination of multilevel Ponte osteotomy (PO) with intraoperative traction (IOT) results in a better correction than IOT alone in high-magnitude curves in adolescent idiopathic scoliosis (AIS) and does not possess an attributable risk of neurological injury.
Overview Of Literature: On a comprehensive review of the literature, the choice of technique adopted for curves between 65° and 100° remains controversial with no major consensus favoring one technique over the other.
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