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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Review Meta Analysis
Systematic review of imaging comparisons of spinal alignment among standing positions in healthy adolescents or adolescents with idiopathic scoliosis: SOSORT 2023 award winner.
Clinicians detect scoliosis worsening over time using frequent radiographs during growth. Arms must be elevated when capturing sagittal radiographs to visualize the vertebrae, and this may affect the sagittal angles. The aim was to systematically review the published evidence of the effect of arm positions used during radiography on spinal alignment parameters in healthy participants and those with AIS. ⋯ Meta-analysis evidence showed elevated arm positions modify sagittal measurements compared to standing. Most studies did not report on all relevant parameters. It is unclear which position best represent habitual standing.
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Review Meta Analysis
Incidence of genitourinary anomalies in congenital scoliosis: systematic review and meta-analysis.
The main objective of this study was to assess the overall incidence of genitourinary anomalies in patients with congenital scoliosis by providing the highest level of evidence. The secondary objective was to look for associations and trends influencing the incidence. ⋯ The incidence of genitourinary anomalies associated with congenital scoliosis was 22.91%, and 13.92% were surgically treated. Unilateral kidney was the most common genitourinary abnormality. There were no differences between genders and deformity types. It is important to consider the association between genitourinary anomalies and intraspinal or musculoskeletal anomalies.
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Multicenter Study
Deep learning-based prediction model for postoperative complications of cervical posterior longitudinal ligament ossification.
Postoperative complication prediction helps surgeons to inform and manage patient expectations. Deep learning, a model that finds patterns in large samples of data, outperform traditional statistical methods in making predictions. This study aimed to create a deep learning-based model (DLM) to predict postoperative complications in patients with cervical ossification of the posterior longitudinal ligament (OPLL). ⋯ A new algorithm using deep learning was able to predict complications after cervical OPLL surgery. This model was well calibrated, with prediction accuracy comparable to that of regression models. The accuracy remained high even for predicting only neurological complications, for which the case number is limited compared to conventional statistical methods.
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To investigate the relationship between sagittal plane characteristics of the spinal column and conservative treatment failure in acute osteoporotic spinal fractures (OSFs). ⋯ Delayed complications requiring reconstructive surgery following OSFs are related to sagittal plane parameters of the spine such as high pelvic incidences, in addition to previously known radiographic characteristics of fractures.