Deep flexor sarcopenia as a predictor of poor functional outcome after anterior cervical discectomy in patients with myelopathy.

Abstract

Paraspinal muscle morphometry has been recognized to be a prognostic factor across various surgical conditions, but its utility in predicting disease-specific outcomes in spine surgery remains under-explored. A prospective cohort study was performed on 45 consecutive patients undergoing anterior cervical discectomy (ACD) for single-level, symptomatic cervical degenerative disc disease causing radiculomyelopathy or myelopathy. Previously described predictors of outcome such as age, gender, smoking, comorbidities, duration of symptoms, preoperative Nurick grade, extent of cord compression, and signal intensity change in the cord were recorded. Additionally, MRI-based morphometrics of the superficial and deep paraspinal muscles were recorded. Logistic regression (LR) analysis was performed using a purposeful variable selection process to identify variables that independently predicted Nurick grade improvement (NGI). At a mean follow-up of 20.02 ± 8.63months after ACD, 37 (82.22%) patients demonstrated NGI. LR analysis yielded three predictors of NGI of which two were related to the deep flexor muscles. While a worse preoperative Nurick grade negatively predicted NGI, a deep flexor area and deep flexor/deep extensor area ratio positively predicted NGI. The regression model demonstrated a good fit and was statistically significant (χ2(3) = 22.18, p < 0.0001). The model explained 64% of the variance in NGI and correctly classified 89% of cases. This study has for the first time identified the utility of paraspinal morphometrics in predicting disease-specific functional outcome after cervical spine surgery. Our results indicate that in addition to preoperative Nurick grade, an already accepted outcome predictor, the deep flexor cross-sectional area, and the deep flexor/deep extensor ratio are strong predictors of NGI following ACD for single-level, symptomatic cervical degenerative disc disease with myelopathy. Deep muscle morphometrics could be included in future risk stratification algorithms for patients with cervical disc disease.