Lordosis distribution index for predicting mechanical complications after long-level fusion surgery: comparison of...

Both the Global Alignment and Proportion (GAP) score and Roussouly classification account for the lordosis distribution index (LDI), but the LDI of the GAP score (G-LDI) is typically set to 50%-80%, while the LDI of the Roussouly classification (R-LDI) varies depending on the degree of pelvic incidence (PI). The objective of this study was to validate the ability of the G-LDI to predict mechanical complications and compare it with the predictive probability of R-LDI in patients with long-level fusion surgery.

A total of 171 patients were divided into two groups: 93 in the nonmechanical complication group (non-MC group) and 78 in the mechanical complication group (MC group). The mean age of the participants was 66.79 ± 8.56 years (range 34-83 years), and the mean follow-up period was 45.49 ± 16.20 months (range 24-62 months). The inclusion criteria for the study were patients who underwent > 4 levels of fusion and had > 2 years of follow-up. The predictive models for mechanical complications using the G-LDI and R-LDI were analyzed using binomial logistic regression and receiver operating characteristic analyses.

There was a significant correlation between R-LDI and PI (r = -0.561, p < 0.001), while there was no correlation between G-LDI and PI (r = 0.132, p = 0.495). In reference to G-LDI, most patients in the non-MC group were classified as having alignment (72, 77.4%), while the MC group had an inhomogeneous composition (aligned: 34, 43.6%; hyperlordosis: 37, 47.4%). The agreement between the G-LDI and R-LDI was moderate (κ = 0.536, p < 0.001) to fair (κ = 0.383, p = 0.011) for patients with average or large PI, but poor (κ = -0.255, p = 0.245) for those with small PI. The areas under the curve for the G-LDI and R-LDI were 0.674 (95% CI, 0.592-0.757) and 0.745 (95% CI, 0.671-0.820), respectively.

The R-LDI, which uses a PI-based proportional parameter, enables individual quantification of LL for all PI sizes and has been shown to have a higher accuracy in classifying cases and a stronger correlation with the risk of mechanical complications compared with G-LDI.