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Objective Adult cervical deformity (ACD) is a debilitating spinal condition that causes significant pain, neurologic dysfunction, and functional impairment. Surgery is often performed to correct cervical alignment, but the optimal amount of correction required to improve patient-reported outcomes (PROs) are not yet well-defined. Methods A review of the literature was performed and Fisher z-transformation (Zr) was used to pool the correlation coefficients between alignment parameters and PROs. The strength of correlation was defined according to the following: poor (0

Objective Conventional techniques for atlantoaxial fixation and fusion typically pass cables or wires underneath C1 lamina to secure the bone graft between the posterior elements of C1–2, which leads to complications such as cerebrospinal fluid (CSF) leak and neurological injury. With the evolution of fixation hardware, we propose a novel C1–2 fixation technique that avoids the morbidity and complications associated with sublaminar cables and wires. Methods This technique entails wedging and anchoring a structural iliac crest graft between C1 and C2 for interlaminar arthrodesis and securing it using a 0-Prolene suture at the time of C1 lateral mass and C2 pars interarticularis screw fixation. Results We identified 32 patients who underwent surgery for atlantoaxial with our technique. A 60% improvement in pain-related disability from preoperative baseline was demonstrated by Neck Disability Index (p

Objective Lumbar fusion with implantation of interbody cage is a common procedure for treatment of lumbar degenerative disease. This study aims to compare the fusion and subsidence rates of titanium (Ti) versus polyetheretherketone (PEEK) interbody cages after posterior lumbar interbody fusion and investigate the effect of clinical and radiological outcomes following fusion on patient-reported outcomes. Methods A systematic search strategy of 4 electronic databases (MEDLINE, Embase, Web of Science, and Cochrane) was conducted using different MeSH (medical subject headings) terms until January 2020. Pooled odds ratios (ORs) with 95% confidence intervals (CI) were calculated using fixed and random-effect models based upon the heterogeneity (I2) to estimate the association between interbody cages and the measured outcomes. Results A total of 1,094 patients from 11 studies were reviewed. The final analysis included 421 patients (38.5%) who had lumbar surgery using a Ti and/or a Ti-coated interbody cage and 673 patient (61.5%) who had lumbar surgery using a PEEK cage. Overall, PEEK interbody devices were associated with a significantly lower fusion rate compared with Ti interbody devices (OR, 0.62; 95% CI, 0.41–0.93; p = 0.02). There was no difference in subsidence rates between Ti and PEEK groups (OR, 0.91; 95% CI, 0.54–1.52; p = 0.71). Also, there were no statistically significant differences in visual analogue scale (VAS)-low back pain (p = 0.14) and Japanese Orthopedic Association scale (p = 0.86) between the 2 groups. However, the PEEK group had lower odds of leg pain after surgery compared to the Ti group (OR [VAS-leg], 0.61; 95% CI, 0.28–0.94; p = 0.003). Conclusion Ti and Ti-coated PEEK cages used for posterior lumbar interbody fusion are associated with similar rates of subsidence, but a higher rate of fusion compared to PEEK interbody cages. Randomized controlled trials are needed to better assess the effect of cage materials and potential factors that could influence the outcomes of interbody lumbar fusion.

The potential of big data analytics to improve the quality of care for patients with spine tumors is significant. At this moment, the application of big data analytics to oncology and spine surgery is at a nascent stage. As such, efforts are underway to advance data-driven oncologic care, improve patient outcomes, and guide clinical decision making. This is both relevant and critical in the practice of spine oncology as clinical decision making is often made in isolation looking at select variables deemed relevant by the physician. With rapidly evolving therapeutics in surgery, radiation, interventional radiology, and oncology, there is a need to better develop decision-making algorithms utilizing the vast data available for each patient. The challenges and limitations inherent to big data analyses are presented with an eye towards future directions.