Background and Study Aim Spinal pyogenic infections occur frequently in today's neurosurgical routine. Conservative therapy often proves to be insufficient against an aggressive disease that affects patients who tend to be elderly and debilitated with complex comorbidity. Treatment, or lack of treatment, carries risks of persistent disability, sepsis, and death. In this study, we propose a tailored and staged algorithm for treating such spinal infections and present results of this approach. Patients and Methods We retrospectively analyzed 52 patients (33 male, 19 female; median age: 68 years) who had undergone cervical, thoracic, or lumbar surgery for spinal infections according to the proposed staged treatment algorithm. Results Most of the 52 patients were severely disabled (35% with quadri- or paraparesis, 31% with sepsis and catecholamine dependency, 17% with a single motor deficit, and 10% with meningitis). We surgically treated multilevel and multisegmental spinal infections via 23 nonstabilizing and 57 stabilizing ventral or dorsal approaches to the cervical, thoracic, or lumbar spine. The mean follow-up time was 24 months. Overall mortality was 19%. Surgery-related complications occurred in 11.5% of patients; recurrence of infection occurred in 3.8%. Motor function improved in 61.7%; bladder and sphincter dysfunction remitted completely in 50.0%. Conclusions Depending on the patient's health status and neurological condition, surgery in complex spinal infections provides a good outcome in most cases. Nevertheless, indication must be individualized; for this, the proposed algorithm seems to be an excellent tool. We find that surgery should be discussed as a treatment of first choice for today's often complex spinal infections. © 2013 Georg Thieme Verlag KG.
CITATION STYLE
Stüer, C., Stoffel, M., Hecker, J., Ringel, F., & Meyer, B. (2013). A staged treatment algorithm for spinal infections. Journal of Neurological Surgery, Part A: Central European Neurosurgery, 74(2), 87–95. https://doi.org/10.1055/s-0032-1320022
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