New prognostic factors for adjacent-segment degeneration after one-stage 360 degrees fixation for spondylolytic spondylolisthesis: special reference to the usefulness of pelvic incidence angle

OBJECT: The purpose of this study was to evaluate the correlation between adjacent-segment degeneration (ASD) and pelvic parameters in the patients with spondylolytic spondylolisthesis. Sagittal balance is the most important risk and prognostic factor in the development of ASD. The pelvic incidence angle (PIA) is an important anatomical parameter in determining the sagittal curvature of the spine and in the individual variability of the sacral slope and the lordotic curve. Thus, the authors evaluated the relationship between the pelvic parameters and the ASD. Methods. Among 132 patients with spondylolytic spondylolisthesis who underwent surgery at their institution, the authors selected patients in whom a one-stage, single-level, 360 degrees fixation procedure was performed for Grade I spondylolisthesis and who underwent follow-up for more than 1 year. Parameters in 34 patients satisfied these conditions. Of the 34 patients, seven had ASD (Group 1) and 27 patients did not have ASD (Group 2). The investigators measured degree of spondylolisthesis, lordotic angle, sacral slope angle (SSA), pelvic tilt angle (PTA), PIA, and additional parameters pre-and postoperatively. The radiographic data were reviewed retrospectively. Results. The population consisted of nine men and 25 women whose mean age was 48.9 +/- 9 years (+/- standard deviation) (range 28-65 years). Seven patients developed ASD after undergoing fusion. Of all the parameters, pre- and postoperative degree of spondylolisthesis, segmental lordosis, lordotic angle, SSA, preoperative PTA, and preoperative PIA did not differ significantly between the two groups; only postoperative PTA and PIA were significantly different. Conclusions. The development of ASD is closely related to postoperative PIA and PTA, not preoperative PIA and PTA. The measurement of postoperative PIA can be used as a new indirect method to predict the ASD.