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OBJECTIVE Lordotic devices have garnered increased attention for improving the segmental lordosis (SL) achieved with transforaminal lumbar interbody fusion (TLIF). However, it is unclear the degree to which surgeons maximize the "ideal" or listed lordosis of the interbody device. METHODS Patients undergoing one- or two-level TLIF for degenerative pathologies were identified and data were extracted on demographics, baseline lumbopelvic radiographic parameters, and TLIF details. The primary outcome of interest was the degree to which postoperative SL approximated the listed cage lordosis (Δtarget). Change in SL was a secondary outcome. Linear mixed-effects modeling was used to identify significant predictors of the percentage of ideal lordosis achieved. RESULTS A total of 239 treated levels were included (median patient age 66.6 years; 56.9% female); 151 levels were part of single-level TLIF constructs. The median segmental corrections were a 2.8° increase in SL and 2.8 mm in disc height. The median difference between listed cage lordosis and postoperative SL (Δtarget) was 0.5°. However, only 56.1% of levels achieved at least the listed cage lordosis. Linear mixed-effects modeling found that independent predictors of Δtarget were lower implant lordosis (estimate −1.01° [95% CI −1.15° to −0.87°] per degree, p < 0.001), greater preoperative SL (estimate 0.38° [95% CI 0.28°–0.48°] per degree, p < 0.001), greater preoperative PI (estimate 0.06° [95% CI 0.02°–0.11°] per degree, p = 0.007), and closer approximation of the anterior apophyseal ring of the caudal vertebrae (estimate −0.27° [95% CI −0.39° to −0.15°] per mm, p < 0.001). Similarly, independent predictors of postoperative SL were larger implant lordosis (estimate 0.16° [95% CI 0.05°–0.27°] per degree, p = 0.004), lower preoperative SL (estimate −0.70° [95% CI −0.79° to −0.62°] per degree, p < 0.001), greater preoperative PI (estimate 0.08° [95% CI 0.04°–0.12°] per degree, p < 0.001), and closer approximation of the anterior apophyseal ring of the cranial vertebrae (estimate −0.15° [95% CI −0.28° to −0.03°] per mm, p = 0.014). CONCLUSIONS The present results suggest that while lordosing, only 56% TLIF operations obtain the listed interbody lordosis ("target" lordosis). Anterior placement within the disc space is the only modifiable intraoperative technical factor for maximizing lordosis for a given interbody, highlighting the importance of effective disc space exenteration.

Study Design: Retrospective cohort analysis. Objective: To determine the effect of long-segment posterior cervical decompression and fusion (PCDF) on perioperative changes in vertebral Hounsfield Units (HUs) and the impact of these changes on radiographic outcomes and fusion status. Summary of Background Data: Low preoperative CT HUs have been associated with adverse outcomes after spinal fusion, including hardware complications and reoperation. No existing studies have investigated the preoperative to postoperative change in HUs after cervical spinal fusion. Stress shielding may decrease bone quality within the fusion construct. Whereas, altered junctional loading and increased segmental mobility may precipitate bony hypertrophy in the terminal and adjacent levels. Methods: All adult patients who underwent C2-T2 PCDF for myelopathy/ myeloradiculopathy at an academic center between 2013 and 2020 were retrospectively identified. Preoperative and postoperative HUs were assessed on axial CT images in the cranial, middle, and caudal C2, C6, T2, and T3 vertebral bodies, outside of the region of instrumentation and artifact by 2 independent reviewers. Paired t test compared preoperative to postoperative changes in HUs. Preoperative and long-term postoperative cervical alignment, fusion, and revision rates were assessed. Univariate and regression analysis compared patient factors and outcomes between groups with perioperative increase versus decrease in vertebral HUs. Results: One hundred patients were included. The average preoperative to postoperative change in HUs in the C2, C6, T2, and T3 vertebral bodies were −19.80 (P=0.008), −52.63 (P<0.001), 15.15 (P=0.014), and 9.41 (P=0.346), respectively. Perioperative increase in C2 HUs was predictive of increased postoperative distal junctional angle (β=3.41, P=0.048) and increased T1–T4 kyphosis (β=6.50, P=0.003). Perioperative increase in C6 HU predicted pseudoarthrosis (fusion odds ratio: 0.19, P=0.007). Conclusions: Significant perioperative decreases in C6 HUs within a long-fused construct may demonstrate stress shielding. The significant association between greater distal kyphosis and an increase in C2 HUs may be attributed to a stress riser effect. Level of Evidence: Level III.

Background: Estimating operative time with low accuracy and precision leads to suboptimal scheduling of available operating rooms (ORs) and waste of healthcare resources. We aimed to develop a predictive machine learning (ML) model for operative time using our institutional data to improve the scheduling of neurosurgical ORs, minimize waste, and maximize resource utilization. Methods: We developed a predictive model using our institution’s multicenter registry, which included diverse neurosurgical cases across three tertiary hospitals. We applied multiple ML techniques, including linear regression, support vector regression, deep neural networks, and extreme gradient boosting regression (XGBR). The best model was combined with the first fit decreasing bin-packing algorithm to create a practical OR scheduling system based on prior data. Results: The XGBR model exhibited the best performance, with lower mean absolute errors (MAEs) (root mean squared error: 52.24, MAE: 37.25) and higher R2 (0.76) values than other models. Implementing this model in a simulated OR scheduling scenario using institutional data, we successfully scheduled 30 random procedures with minimal residual time, such that the model ran out of procedures for the week with 86 and 171 min remaining in the cranial and spinal ORs, respectively, demonstrating potential efficiency gains. The cranial procedures were scheduled over 4 days and spinal procedures over 6 days, optimizing available OR time. Conclusion: Integrating ML models into operative time prediction can significantly improve the accuracy and efficiency of surgical schedules. This approach minimizes wasted OR time and enhances resource allocation, potentially improving patient outcomes and satisfaction by reducing waiting times.

OBJECTIVE Anterior cervical discectomy and fusion (ACDF) is an established treatment for cervical degenerative disc disease; however, the procedure can cause loss of cervical spine range of motion and potentially accelerate adjacent segment degeneration. Cervical disc arthroplasty (CDA) seeks to preserve native motion of the cervical spine, which can theoretically reduce the incidence of adjacent level degeneration. The literature regarding the relative efficacy of ACDF versus CDA remains inconsistent. In this study, the authors investigate the difference in outcomes between ACDF and CDA and identify factors contributing to the heterogeneity in the literature. METHODS The Ovid, Embase, Scopus, Cochrane, and ClinicalTrials.gov databases were systematically searched from inception to September 5, 2023, for randomized controlled trials (RCTs) comparing ACDF and CDA for degenerative disc disease. Studies were extracted by two authors and verified by a third. Random-effects meta-analysis was performed. The primary outcome was the difference in clinical outcomes between the two surgical groups. The secondary outcomes were the differences in radiological outcomes, surgical characteristics, complication rates, and hospital lengths of stay. The study was registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration no. CRD42023469204) and adhered to the PRISMA guidelines. RESULTS From 584 articles uploaded to the Covidence platform for screening, 35 studies derived from 25 RCTs were included in this systematic review and meta-analysis. A total of 4530 patients were treated with ACDF (2081) and CDA (2449). Forty-six percent of the patients (2063) were male, and the mean age of the study cohort was 45 ± 3 years. In terms of the primary outcome, CDA showed higher rates of neurological and overall success. Regarding the secondary outcomes, CDA demonstrated a significantly lower rate of adjacent level disease, higher rate of heterotopic ossification, and greater range of motion at the operated level. Additionally, CDA had lower rates of reoperation but significantly longer operative times than ACDF. The inclusion of myelopathic patients and variations in follow-up between the surgical groups contributed to the observed effect heterogeneity among studies. CONCLUSIONS In this study, CDA showed comparable or potentially greater success in overall and neurological outcomes, along with a lower incidence of adjacent level degeneration and reoperation rates but longer operative times.

OBJECTIVE The evidence on ankylosing spinal disorders (ASDs), including ankylosing spondylitis (AS) and diffuse idiopathic skeletal hyperostosis (DISH), in the context of spinal fracture stems from studies with relatively small sample sizes. There are no studies addressing the patient-reported outcome measures (PROMs) and health-related quality of life (HRQOL) outcomes associated with spinal fracture in this population. The aim of this study was to investigate differences in complications, mortality, PROMs, and HRQOL in patients with and without ASD who had been treated for spinal fracture. METHODS This is a nationwide multicenter retrospective study of prospectively collected data from the Swedish Fracture Register. All patients with fractures of the cervical, thoracic, or lumbar spine treated surgically and conservatively between January 2015 and December 2021 were eligible for inclusion. Two groups of patients were formed based on the presence or absence of concomitant ASD. Primary outcomes of interest included death and PROMs. For surgically treated patients, data on complications and reoperation rates were retrieved. Propensity score matching with a ratio of 1:1 was used to balance the groups prior to intergroup comparison. Variables included in the matching process were age, sex, mechanism of injury, neurological function on admission (Frankel grade), injury type (high vs low energy), fracture type, injured spinal level, time to treatment, and type of treatment (surgical vs conservative). Kaplan-Meier analyses were used to study overall survival following injury. RESULTS A total of 14,604 patients without ASD and 1368 patients with ASD were included in this study. High-energy injuries were less frequent in patients with ASD (13% vs 24%, p < 0.001). Moreover, patients with ASD were less likely to be neurologically intact on admission (90% vs 94%, p < 0.001). There were 1707 surgically treated patients without ASD and 559 with the disorder. After matching, a higher overall risk of reoperation was found among patients with ASD (9.1% vs 3.4%, p = 0.007). Surgical site infections requiring reoperation (p = 0.012), but not construct failure or CSF leakage requiring reoperation (p ≥ 0.05), were more common among the patients with ASD. Postmatching, there were no differences in overall survival between ASD and non-ASD cases (p > 0.05). Moreover, patients with and without ASD had similar PROMs, as indicated by the EQ-5D-3L index at 1 year after injury (p = 0.59). CONCLUSIONS Self-reported recovery 1 year after spinal fracture occurred to a similar extent in patients with and without ASD. Moreover, ASD alone was not a significant risk factor for death. Finally, surgically treated patients with ASD experienced higher rates of postoperative complications and reoperations following surgery.

OBJECTIVE The landscape of healthcare policies has undergone significant reforms, with a notable shift toward a patient-centered basis. This change has prioritized the use of metrics reflecting subjective patient-reported outcome measures (PROMs). However, these metrics are often limited, especially in terms of determining clinically relevant changes over time. The concept of the minimal clinically important difference (MCID) has been introduced to address this limitation. In this study, the authors aimed to assess the predictive capability of relative change and its corresponding threshold value, the minimal clinically important relative change (MCIRC), as an alternative to the absolute difference and MCID. METHODS Prospectively collected data from 2006 to 2021 were obtained from the Swedish Spine Registry (Swespine). PROMs included the numeric rating scale (NRS) neck and arm pain scores, the EQ-5D index and EQ visual analog scale (VAS), and the Neck Disability Index (NDI). Anchor-based methods were used to determine MCID and MCIRC. Absolute differences and relative changes were compared in terms of predictive power using the area under the receiver operating characteristic curve (AUC). RESULTS A total of 5323 patients were included. The chosen MCID values were −3 for NRS neck pain, −3 for NRS arm pain, 0.08 for EQ-5D index, 13 for EQ VAS, and −30 for NDI scores. The chosen MCIRC values were −40% for NRS neck pain, −50% for arm pain, 323% for EQ-5D index, 55% for EQ VAS, and −33% for NDI scores. Relative change was superior for NRS neck and arm pain scores and NDI, while absolute difference was superior for EQ-5D and EQ VAS scores. CONCLUSIONS Relative change and its corresponding MCIRC were found to be more appropriate as a surrogate of subjective satisfaction when studying the NRS and NDI scores, whereas absolute difference and MCID was more appropriate when addressing EQ-5D index and EQ VAS scores.

OBJECTIVE Artificial intelligence (AI) is increasingly capable of academic writing, with large language models such as ChatGPT showing potential to assist or even generate scientific manuscripts. However, concerns remain regarding the quality, reliability, and interpretive capabilities of AI-generated content. The authors’ study aimed to compare the quality of a human-written versus an AI-generated scientific manuscript to evaluate the strengths and limitations of AI in the context of academic publishing. METHODS Two manuscripts were developed using identical titles, abstracts, and tables of a simulated analysis: one authored by a physician with multiple publications, and the other generated by ChatGPT-4o. Three independent and blinded reviewers—two human and one AI—assessed each manuscript across five domains: clarity and readability, coherence and flow, technical accuracy, depth, and conciseness and precision. Each category was scored on a 10-point scale, and qualitative feedback was collected to highlight specific strengths and weaknesses. Additionally, all reviewers were asked to deduce authorship of the manuscripts. RESULTS The AI-generated manuscript scored higher in clarity and readability (mean 9.0 vs 7.2), but lower in technical accuracy (mean 6.3 vs 9.3) and depth (mean 5.5 vs 7.5). However, reviewers noted that the AI version lacked depth, critical analysis, and contextual interpretation. All reviewers accurately identified the authorship of each manuscript and tended to rate the version more favorably when it aligned with their own origin (human or AI); i.e., human reviewers assigned higher scores to the human-written manuscript, while the AI reviewer scored the AI-generated manuscript higher. CONCLUSIONS Although AI models can improve some aspects of scientific writing, particularly clarity and readability, they fall short in critical reasoning and contextual understanding. This reinforces the importance of human authorship and oversight in maintaining the critical analysis and scientific accuracy essential for academic publishing. AI may be used as a complementary tool to support, rather than replace, human-led scientific writing.

OBJECTIVE Degenerative lumbar spondylolisthesis is a common cause of back and leg pain influenced by factors like instability, disc degeneration, facet arthropathy, and psychosocial phenotype. Patients’ experience of high-severity pain is complex, with significant implications for surgical planning. The goal of this study was to assess the impact of back pain catastrophizing on long-term outcomes following lumbar spondylolisthesis surgery. METHODS This study uses the Quality Outcomes Database (QOD) lumbar spondylolisthesis dataset and includes prospectively collected data from the 12 highest-enrolling clinical sites participating in the QOD lumbar module. The authors reviewed patients undergoing single-segment surgery for grade 1 degenerative lumbar spondylolisthesis. Severe baseline numeric rating scale for back pain (NRS-BP) scores (≥ 8) were classified as "catastrophizing," and mild to moderate pain scores (< 8) were classified as "non-catastrophizing." Patient-reported outcomes (PROs) were compared for catastrophizing versus non-catastrophizing patients at 60 months. Univariate and multivariate analyses were conducted to assess the impact of catastrophizing on PROs, with multivariate analysis controlling for variables initially reaching a p value < 0.10. RESULTS Of the 608 patients in this analysis, 260 (42.8%) experienced catastrophizing while 348 (57.2%) did not. Catastrophizing patients were significantly younger (59.9 ± 12.2 years vs 63.9 ± 11.7 years, p < 0.001), less often had ≥ 4 years of college education (31.2% vs 42.5%, p = 0.004), and more often used private insurance (58.8% vs 47.7%, p = 0.01). The catastrophizing cohort also had higher rates of depression (24.6% vs 17.0%, p = 0.02) and back pain predominance (45.4% vs 32.2%, p < 0.001). Surgical and perioperative characteristics did not significantly differ between cohorts. Although catastrophizing patients typically reported worse PRO scores at both baseline and 60 months, they demonstrated significantly greater improvement and minimal clinically important difference (MCID) achievement across almost all PROs at 60 months (p < 0.05). However, North American Spine Society (NASS) satisfaction scores at 60 months did not differ significantly between cohorts. Multivariate analysis found that catastrophizing significantly predicted 60-month NRS-BP change (β −1.45, 95% CI −1.81 to −1.09; p < 0.001) and MCID achievement (OR 1.98, 95% CI 1.52–2.58; p < 0.001) but not mean NRS-BP score or other metrics, including NASS satisfaction. CONCLUSIONS Despite presenting with worse baseline symptoms, patients with pain catastrophizing experienced substantial and clinically meaningful improvement following surgery for degenerative lumbar spondylolisthesis. Patient satisfaction was comparable between cohorts, reflecting a nuanced balance between greater absolute improvement and persistence of residual symptoms. These findings underscore that catastrophizing should not be viewed as a barrier to surgical success, while pointing to the need for proactive expectation setting and shared decision-making.

OBJECTIVE The present investigation aimed to 1) develop a new CT-based assessment of endplate bone density (endplate Hounsfield unit [EP-HU]) and 2) analyze if EP-HU was a better predictor than vertebral Hounsfield unit (HU) for subsidence after anterior cervical discectomy and fusion (ACDF). METHODS All adult patients who underwent one- to three-level ACDF with a titanium interbody for radiculopathy and/or myelopathy at an academic center between 2018 and 2020 were retrospectively identified. Based on preoperative sagittal CT scans (left, right, and middle cuts), 2-mm superior and inferior endplate regions were circumscribed with the free draw tool to account for endplate surface undulations. The average of the superior and inferior EP-HUs on all CT cuts was used to calculate EP-HU. Cervical vertebral HUs were determined from the average of axial CT cranial, middle, and caudal cuts circumscribing only trabecular bone. The interbody subsidence of the cranial and caudal endplates of each ACDF level was directly measured on the endplate-facing surface of both coronal and sagittal cuts of postoperative CT scans (at 1 year) to determine the maximum subsidence (subsidence defined as ≥ 2 mm). Univariate and stepwise logistic regression analyses were used to compare subsidence based on CT bone metrics. Receiver operating characteristic (ROC) curve analyses were used to determine the probability of subsidence based on EP-HUs and vertebral HUs. RESULTS A total of 35 patients were included. Subsidence occurred at 32 of 67 unique fusion levels. Subsidence was associated with older age (p = 0.008), diabetes diagnosis (p = 0.015), and decreased interbody length (p = 0.019). EP-HUs exhibited moderate correlation with cervical vertebral HUs (Pearson’s ρ = 0.63). Subsidence was significantly associated with decreased total EP-HUs (subsidence: 475 HU, no subsidence: 543 HU; p = 0.019) and decreased lumbar vertebral HUs (subsidence: 296 HU, no subsidence: 341 HU; p = 0.011). ROC curve analysis identified an optimal EP-HU cutoff of 512.30 (area under the curve [AUC] = 0.701) to predict subsidence. The AUC of the vertebral HUs with respect to subsidence was 0.662. EP-HUs < 512.30 predicted subsidence (OR 6.67, p = 0.001) independent of significant demographic and surgical factors. CONCLUSIONS CT cervical EP-HUs rather than vertebral cervical trabecular HUs may be more efficacious in predicting subsidence after ACDF.