Achieving assessor accuracy on the International Standards for Neurological Classification of Spinal Cord Injury

作者:Armstrong, A. J.; Clark, J. M.; Ho, D. T.; Payne, C. J.; Nolan, S.; Goodes, L. M.; Harvey, L. A.; Marshall, R.; Galea, M. P.; Dunlop, S. A.*
来源:Spinal Cord, 2017, 55(11): 994-1001.
DOI:10.1038/sc.2017.67

摘要

Study design: A retrospective audit of assessor accuracy using the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) in three multicentre randomised controlled trials (SCIPA: Spinal Cord Injury and Physical Activity) spanning 2010-2014 with standards revised in 2011. Objectives: To investigate assessor accuracy of neurological classification after spinal cord injury. Setting: Australia and New Zealand. Methods: ISNCSCI examinations were undertaken by trained clinicians prior to randomisation. Data were recorded manually and ISNCSCI worksheets circulated to panels, consensus reached and worksheets corrected. An audit team used a 2014 computerised ISNCSCI algorithm to check manual worksheets. A second audit team assessed whether the 2014 computerised algorithm accurately reflected pre-and post-2011 ISNCSCI standards. Results: Of the 208 ISNCSCI worksheets, 24 were excluded. Of the remaining 184 worksheets, 47 (25.5%) were consistent with the 2014 computerised algorithm and 137 (74.5%) contained one or more errors. Errors were in motor (30.1%) or sensory (12.4%) levels, zone of partial preservation (24.0%), motor/sensory scoring (21.5%), ASIA Impairment Scale (AIS, 8.3%) and complete/incomplete classification (0.8%). Other difficulties included classification when anal contraction/sensation was omitted, incorrect neurological levels and violation of the ` motor follows sensory rule in non-testable myotomes' (7.4%). Panel errors comprised corrections that were incorrect or missed or incorrect changes to correct worksheets. Conclusion: Given inaccuracies in the manual ISNCSCI worksheets in this long-term clinical trial setting, continued training and a computerised algorithm are essential to ensure accurate scoring, scaling and classification of the ISNCSCI and confidence in clinical trials.

  • 出版日期2017-11

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