脊椎骨膜炎
医学
组内相关
神经外科
神经组阅片室
外科
放射科
神经学
临床心理学
精神科
心理测量学
作者
Friederike Schömig,Li Zhao,Lena Perka,Tu-Lan Vu-Han,Torsten Diekhoff,Charles G. Fisher,Matthias Pumberger
标识
DOI:10.1007/s00586-022-07157-3
摘要
Abstract Purpose Even though spinal infections are associated with high mortality and morbidity, their therapy remains challenging due to a lack of established classification systems and widely accepted guidelines for surgical treatment. This study’s aim therefore was to propose a comprehensive classification system for spinal instability based on the Spinal Instability Neoplastic Score (SINS) aiding spine surgeons in choosing optimal treatment for spontaneous spondylodiscitis. Methods Patients who were treated for spontaneous spondylodiscitis and received computed tomography (CT) imaging were included retrospectively. The Spinal Instability Spondylodiscitis Score (SISS) was developed by expert consensus. SINS and SISS were scored in CT-images by four readers. Intraclass correlation coefficients (ICCs) and Fleiss’ Kappa were calculated to determine interrater reliabilities. Predictive validity was analyzed by cross-tabulation analysis. Results A total of 127 patients were included, 94 (74.0%) of which were treated surgically. Mean SINS was 8.3 ± 3.2, mean SISS 8.1 ± 2.4. ICCs were 0.961 (95%-CI: 0.949–0.971) for total SINS and 0.960 (95%-CI: 0.946–0.970) for total SISS. SINS yielded false positive and negative rates of 12.5% and 67.6%, SISS of 15.2% and 40.0%, respectively. Conclusion We show high reliability and validity of the newly developed SISS in detecting unstable spinal lesions in spontaneous spondylodiscitis. Therefore, we recommend its use in evaluating treatment choices based on spinal biomechanics. It is, however, important to note that stability is merely one of multiple components in making surgical treatment decisions.
科研通智能强力驱动
Strongly Powered by AbleSci AI