An Analysis of Outcome Predictors with Circumferential Minimally Invasive Surgical Correction (cMIS) of Adult Spinal Deformity (ASD)—A Multivariate Linear Regression Analysis

Presented at SMISS Annual Forum 2016
By Neel Anand MD
With Eli M. Baron MD, Babak Khandehroo MD, Sheila Kahwaty PA-C, Ryan Cohen , Jason Cohen ,

Disclosures: Neel Anand MD None Eli Baron MD , Babak Khandehroo MD None, Sheila Kahwaty PA-C None, Ryan Cohen None, Jason Cohen None,

Introduction

Predictors of outcome using Circumferential Minimally Invasive Surgical (CMIS) techniques for the correction of Adult Spinal Deformity (ASD) are not well understood. This study was conducted to assess the significant clinical and radiological prognosticators of outcomes of CMIS correction of adult spinal deformity.

Aims/Objectives

A variety of patient, clinical and radiologic factors influences ODI after CMIS correction of ASD. Baseline ODI and delta-SVA produce the best-fit multivariate regression model to predict post-op ODI.

Methods

This is a single center study from a prospective database of patients who underwent CMIS correction for ASD (Cobb angle > 20 degrees or SVA > 50 mm or PI/LL mismatch > 10). Patients without 2-year follow-up data or at least 3 or more levels operated were excluded resulting in a cohort of 81 consecutive patients.
The Pearson correlation between each outcome predictor and 2-year follow-up Oswestry disability index (ODI) was calculated. Stepwise regression analysis was used to construct a final multivariate linear regression model.

Results

In descending order of correlation strength, baseline ODI, baseline sagittal vertical alignment (SVA), BMI, baseline visual analogue score (VAS), operation before 2011, delta-SVA, postop SVA, occurrence of pseudoarthrosis, and baseline Cobb angle, demonstrated a significant linear relationship to outcome: (p < .05). All correlations were positive, with the exception of delta-SVA and baseline Cobb angle, which were inversely related to ODI. Age, sex, smoking history, and comorbid depression were not significant predictors. Using stepwise regression, baseline ODI and delta-SVA, produced the best-fit multivariate regression model (R2 = .348, R2 adj. = .312, p <.01).

Conclusions

Spinal surgeons should consider the effects of baseline quality-of-life measures, radiographic correction, BMI and pseudoarthrosis as predictors of clinical outcome. In particular, baseline ODI and delta-SVA, considered simultaneously, may prove the most useful predictive factors.