World Neurosurg
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This retrospective study aimed to determine the Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOABPEQ) cutoff scores for assessing patient satisfaction postlateral lumbar interbody fusion (LLIF) in degenerative lumbar spinal stenosis (DLSS) patients. ⋯ This study underscores the value of patient-centered outcomes in evaluating LLIF surgery success for DLSS. The identified JOABPEQ cutoff values provide a quantitative tool for assessing patient satisfaction, emphasizing the necessity of comprehensive postoperative evaluations beyond traditional clinical metrics for improved patient care and life quality.
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Review Meta Analysis Comparative Study
Unilateral vs Bilateral Cages in Lumbar Interbody Fusions: A Meta-Analysis of Clinical and Radiographic Outcomes.
Bilateral cages are often used for interbody fusion. However, this procedure may not be possible in some cases making unilateral cages a reasonable alternative. The literature remains divided on the clinical and radiological distinctions when comparing unilateral to bilateral cages in lumbar interbody fusion. Thus, this meta-analysis will analyze the clinical and radiographic outcomes between these 2 groups. ⋯ Unilateral cages were shown to be superior due to their reduced OR time and estimated blood loss. As for the higher rate of pseudoarthrosis, this outcome may not be related to the cage numbers and it did not affect clinical outcomes. Nevertheless, one must consider other factors such as radiographic sagittal parameters before making a surgical decision.
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Review Meta Analysis
Application of Machine Learning for Classification of Brain Tumors: A Systematic Review and Meta-Analysis.
Classifying brain tumors accurately is crucial for treatment and prognosis. Machine learning (ML) shows great promise in improving tumor classification accuracy. This study evaluates ML algorithms for differentiating various brain tumor types. ⋯ ML demonstrated excellent performance in classifying brain tumor images, with near-maximum area under the curves, sensitivity, and specificity.