European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
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The overwhelming inflammatory response plays a critical role in the secondary injury cascade of traumatic spinal cord injury (tSCI). The systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) are two novel inflammatory biomarkers. The SII was calculated based on lymphocyte, neutrophil, and platelet counts, while the SIRI was calculated based on lymphocyte, neutrophil, and monocyte counts. Their prognostic value in patients with tSCI remains unclear. ⋯ Increased SII was independently associated with a decreased likelihood of improved AIS grade conversion.
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To investigate the clinical application value of the non-shared incentive diffusion imaging technique (ZOOM-DWI) diagnoses of cervical spondylotic myelopathy (CSM). ⋯ Cervical ZOOM-DWI can be applied to diagnose CSM, and spinal ADC value can use as reliable imaging data for diagnosing cervical myelopathy.
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Cervical sagittal alignment is essential, and there is considerable debate as to what constitutes physiological sagittal alignment. The purpose of this study was to identify constant parameters for characterizing cervical sagittal alignment under physiological conditions. ⋯ In the asymptomatic population, the C4 vertebral body maintains a constant slope angle under physiological conditions. The novel concept of C4 as a constant vertebra would provide a vital benchmark for diagnosing pathological sagittal alignment abnormalities and planning the surgical reconstruction of cervical lordosis.
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Symptoms of cauda equina syndrome (CES) secondary to degenerative lumbar spine diseases are sometimes mild and tend to be ignored by patients, resulting in delayed treatment. In addition, the long-term efficacy of surgery is unclear. ⋯ CES patients with symptoms lasting > 3 months may recover after surgery. Sexual dysfunction has a high residual rate and should not be ignored during diagnosis and treatment.
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To develop a three-stage convolutional neural network (CNN) approach to segment anatomical structures, classify the presence of lumbar spinal stenosis (LSS) for all 3 stenosis types: central, lateral recess and foraminal and assess its severity on spine MRI and to demonstrate its efficacy as an accurate and consistent diagnostic tool. ⋯ The CNN showed comparable performance to radiologist subspecialists for the detection and classification of LSS. The integration of neural network models in the detection of LSS could bring higher accuracy, efficiency, consistency, and post-hoc interpretability in diagnostic practices.