Abstract
Introduction The treatment of congenital spinal anomalies poses a formidable task. Although many classifications of congenital malformations of the spine and the spinal cord have been developed and a variety of surgical options offered, none of the existing classifications can be used to identify appropriate treatment guidelines and surgical practices. Design Expert consensus level. Evidence level: 5 (UK Oxford, version 2011). Objective of the study was to offer an algorithm of surgical treatment strategy for patients with congenital malformations of the spine based on identification of a leading syndrome. Material and methods The algorithm was developed through the clinical experience and consensus opinion of the authors based on the management and follow-up of 284 patients with different patterns of congenital spinal deformity treated between 2008 and 2018. Results The algorithm offered to identify an appropriate treatment strategy for congenital anomalies of the spine included a stepwise protocol for sequential assessment of the criteria selected and considered as components of the leading syndrome of multiplanar deformity allowing well-argued surgical options and succession of treatment stages. Sequential evaluation is essential for patients with multilevel congenital anomalies and several main arcs. The algorithm is presented as a checklist with a table and comments to the main syndromes and decision-making process. Conclusion The algorithm offered is a stepwise checklist providing a step-by-step process for making decisions on the approach and practice for treating congenital anomalies of the spinal column. It is designed to consider main pathological syndromes being typical of congenital pathology and reduce tactical and methodological flaws. The algorithm is of purely advisory nature. The consensus opinion of experienced surgeons has been shown to be essential for timely management facilitating appropriate treatment strategy for the rare and diverse nosological group.
Highlights
The treatment of congenital spinal anomalies poses a formidable task
Objective of the study was to offer an algorithm of surgical treatment strategy for patients with congenital malformations of the spine based on identification of a leading syndrome
The algorithm offered to identify an appropriate treatment strategy for congenital anomalies of the spine included a stepwise protocol for sequential assessment of the criteria selected and considered as components of the leading syndrome of multiplanar deformity allowing well-argued surgical options and succession of treatment stages
Summary
The treatment of congenital spinal anomalies poses a formidable task. many classifications of congenital malformations of the spine and the spinal cord have been developed and a variety of surgical options offered, none of the existing classifications can be used to identify appropriate treatment guidelines and surgical practices. Objective of the study was to offer an algorithm of surgical treatment strategy for patients with congenital malformations of the spine based on identification of a leading syndrome. Results The algorithm offered to identify an appropriate treatment strategy for congenital anomalies of the spine included a stepwise protocol for sequential assessment of the criteria selected and considered as components of the leading syndrome of multiplanar deformity allowing well-argued surgical options and succession of treatment stages. The treatment of congenital spinal anomalies poses a formidable task due to multiple criteria used to assess "vertebral status" and determine the prognosis of the pathology including complicated cases. There are many works representing retrospective analyses of local cohorts (evidence level: 3-4 UK Oxford, version 2011) without comparison of the results with uniform evaluation criteria.We could not find evidence of the treatment strategy for a congenital anomaly based on a syndromal approach. The approach is widely used when choosing treatment options for trauma and degenerative pathology of the spine
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