Which Sagittal Evaluation System Can Effectively Predict Mechanical Complications in the Treatment of Elderly Patients With Adult Degenerative Scoliosis? Roussouly Classification or Global Alignment and Proportion (GAP) Score

Abstract

Background: To achieve the proper sagittal alignment, previous studies have developed different assessment systems for degenerative spinal deformity which could help us in making treatment strategies. The purpose of our study is to evaluate whether Roussouly classification or GAP score is more appropriate in the prediction of mechanical complications after surgical treatment of ADS.Methods: The ADS patients who received long segmental fusion in the treatment during the period from December 2016 to December 2018 were evaluated in this study. The basic information of the patients and all radiologic measurements, which were included in GAP score and Roussouly classification, were collected for analysis. Patients were divided into two groups according to occurrence or absence of mechanical complications for comparison. The correlation between evaluation systems and mechanical complications could be analyzed in logistic regression model via stepwise backward elimination based on the Wald statistics. ROC curve was used to determine the predictability of the evaluation systems in the occurrence of mechanical complications and calculate their cut-off value. A two-tailed P value < 0.05 was statistically significant for all statistical tests.Results: A total of 80 cases were included in this study. The results of logistic regression showed: GAP score (P = 0.008) and GAP categories (P = 0.007) were positively correlated with mechanical complications; Roussouly score was negatively correlated with mechanical complications (P=0.034); GAP score was positively correlated with PJK (P = 0.021); Roussouly score was negatively correlated with implant-related complications (P = 0.018); GAP categories were correlated with implant loosening (P = 0.023). Results of ROC showed that GAP score was most effective in predicting PJK (AUC = 0.863) and PJF (AUC = 0.724); GAP categories (AUC = 0.561) was more effective than GAP score (AUC = 0.555) in predicting implant-related complications.Conclusions: Roussouly-type matching could not accurately predict the risk of mechanical complications. In contrast, GAP score was most effective in predicting PJK and PJF. The GAP score was better than Roussouly classification in predicting mechanical complications.