Methods: This study involved 104 asymptomatic adults (females 62 [59.6%]) aged 18–50 years. Whole-spine standing lateral radiographs were obtained, and the pelvic, lumbar, thoracic, cervicothoracic, and cervical parameters were studied. Pearson’s correlation coefficient was used to assess correlations, with a significance threshold of p<0.05. Results: The mean age of participants was 38.27±9.93 years. The pelvic incidence (PI) significantly correlated with C7 slope (r=−0.212, p=0.05). The pelvic tilt (PT) exhibited significant correlations with T1 slope−CL mismatch (r=−0.229, p=0.05) and C2 slope (r=−0.202, p=0.05). Furthermore, PI–LL mismatch showed a significant correlation with TIA (r=−0.197, p=0.05), T1 slope (r=−0.228, p=0.05), and C7 slope (r=−0.251, p=0.05). Conclusions This study reveals a significant correlation between cervical and spinopelvic parameters, emphasizing the interconnectedness of pelvic, lumbar, thoracic, and cervical spine parameters.

Methods: In total, 108 patients who underwent surgery for traumatic LLFs between January 2010 and January 2020 were reviewed to obtain their demographic details, injury level, and neurology status at the time of presentation (American Spinal Injury Association [ASIA] grade). Preoperative computed tomography scans were used to measure parameters such as anterior vertebral body height, posterior vertebral body height, loss of vertebral body height, local kyphosis, retropulsion of fracture fragment, interpedicular distance, canal compromise, sagittal transverse ratio, and presence of vertical lamina fracture. MRI was used to measure the canal encroachment ratio (CER), cross-sectional area of the thecal sac (CSAT), and presence of an epidural hematoma. Results: Of the 108 patients, 9 (8.3%) had ASIA A, 4 (3.7%) had ASIA B, 17 (15.7%) had ASIA C, 21 (19.4%) had ASIA D, and 57 (52.9%) had ASIA E neurology upon admission. The Thoracolumbar Injury Classification and Severity score (p =0.000), CER (p =0.050), and CSAT (p =0.019) were found to be independently associated with neurological deficits on the multivariate analysis. The receiver operating characteristic curves showed that only CER (area under the curve [AUC], 0.926; 95% confidence interval [CI], 0.860–0.968) and CSAT (AUC, 0.963; 95% CI, 0.908–0.990) had good discriminatory ability, with the optimal cutoff of 50% and 65.3 mm2, respectively. Conclusions Based on the results, the optimal cutoff values of CER >50% and CSAT >65.3 mm2 can predict the incidence of neurological deficits in LLFs.