Degenerative Cervical Myelopathy: A 7-Letter Coding System That Supports Decision-Making for the Surgical Approach. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: To validate with a prospective study a decision-supporting coding system for the surgical approach for multilevel degenerative cervical myelopathy. METHODS: Ten cases were presented on an internet platform, including clinical and imaging data. A single-approach (G1), a choice between 2 (G2), or 3 approaches (G3) were options. Senior and junior spine surgeons analyzed 7 parameters: location and extension of the compression of the spinal cord, C-spine alignment and instability, general morbidity and bone diseases, and K-line and multilevel corpectomy. For each parameter, an anterior, posterior, or combined approach was suggested. The most frequent letter or the last letter (if C) of the resulting 7-letter code (7LC) suggested the surgical approach. Each surgeon performed 2 reads per case within 8 weeks. RESULTS: G1: Interrater reliability between junior surgeons improved from the first read (κ = 0.40) to the second (κ = 0.76, p < 0.001) but did not change between senior surgeons (κ = 0.85). The intrarater reliability was similar for junior (κ = 0.78) and senior (κ = 0.71) surgeons. G2: Junior/senior surgeons agreed completely (58%/62%), partially (24%/23%), or did not agree (18%/15%) with the 7LC choice. G3: junior/senior surgeons agreed completely (50%/50%) or partially (50%/50%) with the 7LC choice. CONCLUSION: The 7LC showed good overall reliability. Junior surgeons went through a learning curve and converged to senior surgeons in the second read. The 7LC helps less experienced surgeons to analyze, in a structured manner, the relevant clinical and imaging parameters influencing the choice of the surgical approach, rather than simply pointing out the only correct one.

publication date

  • July 9, 2019

Identity

PubMed Central ID

  • PMC7136109

Scopus Document Identifier

  • 85080827871

Digital Object Identifier (DOI)

  • 10.14245/ns.1938010.005

PubMed ID

  • 31284334

Additional Document Info

volume

  • 17

issue

  • 1