International Standards for Neurological Classification of Spinal Cord Injury: Case Examples Reinforcing Concepts From the 2019 Revision.

Background: The International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) is the most widely accepted system for characterizing sensorimotor impairments after spinal cord injury (SCI). There have been a number of ISNCSCI revisions, with the most recent edition published in 2019. Newer concepts, including the revised definitions of the zones of partial preservation (ZPPs) and documentation of non-SCI conditions, require training and practice for successful utilization. The International Standards Committee developed an ISNCSCI workbook of 26 practice cases, each with detailed explanations of the correct classification components. In this article, we present seven cases, which were selected from the workbook to reinforce the changes implemented in 2019.

Methods: Hypothetical ISNCSCI cases were created to illustrate important classification rules, definitions, and nuances. All cases were reviewed by members of the American Spinal Injury Association (ASIA) International Standards Committee, and if any discrepancies were identified, they were discussed until a consensus was reached. To confirm agreement, cases were also entered into online algorithms, which are compliant with the 2019 ISNCSCI revision. The seven cases in this article highlight newer classification concepts and include a discussion of key elements.

Cases: Each case reinforces the revised definitions of the ZPPs, such as the applicability of sensory ZPPs in all injuries without sensory sacral sparing and applicability of motor ZPPs in all injuries without voluntary anal contraction (VAC). Non-SCI-related impairments and their impact on the classification are reviewed in Cases 4-7.

Conclusion: The seven cases presented in this article feature key concepts from the 2019 ISNCSCI revision. These cases, as well as the full ISNCSCI workbook, can serve as valuable training tools to improve classification accuracy.