Objective To longitudinally analyze smartphone-based real-life activity data and compare it with established clinical outcome measures in patients undergoing lumbar spine surgery for sciatica, focusing on identifying divergence in recovery trajectories.
Methods Fifty patients were assessed preoperatively and at 6 weeks (6W), 3 months (3M), and 6 months (6M). Outcomes included smartphone-derived daily Step Count, objective capacity (6-minute walking test [6WT]), and subjective disability (visual analogue scale [VAS] leg/back, Core Outcome Measures Index [COMI] back, and Oswestry Disability Index [ODI]). All metrics were standardized into z-scores relative to baseline. Piecewise linear mixed-effects (LME) models compared recovery slopes across 2 segments: phase I (early: 0–6 weeks) and phase II (late: 6 weeks–6 months).
Results The cohort (mean age, 50.7 years; 24 females) included 33 patients with lumbar disc herniation and 17 with lateral recess stenosis. All measures improved significantly during phase I (all p<0.05). However, LME modeling revealed a significant interaction between time segment and measurement type in phase II. Daily Step Count was the only metric maintaining a significant, linear upward recovery slope during the late phase (β=0.31 Z/mo). Conversely, slopes for 6WT, ODI, and COMI were significantly flatter (p<0.001 vs. Step Count), indicating a statistical plateau or “ceiling effect.” Spearman correlations between Step Count and traditional metrics weakened from strong at baseline to weak at 6 months.
Conclusion Smartphone-derived real-life activity data detect continuous functional improvement up 6 months postoperatively, whereas conventional objective and subjective measures plateau by 6 weeks. Real-world activity monitoring provides a more sensitive assessment of long-term surgical success.
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From the Editor-in-Chief: Featured Articles in the April 2026 Issue Inbo Han Neurospine.2026; 23(2): 227. CrossRef
Real-World Effectiveness Versus Efficacy in a Study Environment: How Smartphones Help Capture Meaningful Patient Recovery Trajectories – A Commentary on “Physical Performance Continues to Improve After Surgery for Sciatica, Exceeding Recovery Periods of P Victor E. Staartjes Neurospine.2026; 23(2): 239. CrossRef
Objective Lumbar fusion surgery serves as a crucial option for treating lumbar degenerative diseases. However, patient heterogeneity contributes to suboptimal surgical outcomes in a substantial proportion of cases. Therefore, an accurate classification may provide a powerful tool for personalized treatment and enable the identification of individuals at increased risk for unfavorable surgical outcomes (USO). The study aimed to develop a risk stratification model for USO using cluster analysis.
Methods Consecutive patients diagnosed with degenerative lumbar disease who underwent lumbar fusion between April 2019 and January 2023 were enrolled. The outcome of interest was the USO, defined as failure to achieve a minimal clinically important difference in the 36-Item Short Form Health Survey physical component summary score, with the presence of complications. Three machine learning algorithms were employed to identify risk factors associated with USO. Based on these risk factors, we conducted a data-driven clustering analysis to develop a risk stratification model. Furthermore, based on 6 machine learning models, we developed a classification classifier capable of accurately identifying the risk cluster of individual patients.
Results A total of 662 patients were enrolled for risk stratification model, 219 patients were classified as having an USO. Six features were identified as key prognostic predictors, including frailty, depression, PI–LL (pelvic incidence minus lumbar lordosis) match, surgical levels, functional independence measure, and the relative functional cross-sectional area. The K-prototypes clustering algorithm successfully identified 3 distinct clusters. Furthermore, we developed a classification classifier, in which LightGBM (light gradient boosting machine) demonstrated the highest predictive performance (area under the receiver operating characteristic curve, 0.951; 95% confidence interval [CI], 0.814–0.974; area under the precision-recall curve, 0.927; 95% CI, 0.769–0.969).
Conclusion Based on data-driven clustering analysis, we developed a risk stratification model for predicting USO following lumbar fusion surgery, which demonstrated high predictive accuracy. Further studies in larger and more diverse cohorts are warranted to validate the clinical applicability of clustering analysis in USO risk stratification.
Objective To develop and externally validate a dual-mechanism deep learning (DL) model that integrates vertebral segmentation and lesion detection for automated evaluation of lumbar degeneration and structured report generation on plain radiographs.
Methods In this retrospective study, 5,964 patients who underwent standing anteroposterior and lateral lumbar radiographs at a single institution and 600 patients from a public dataset (BUU-Spine) were included. Vertebral corners from T11–L5 (and S1 on lateral views) and 7 degenerative findings (scoliosis, straightened/preserved lordosis, spondylolisthesis, disc space narrowing, osteophytes, vertebral compression, and abdominal aortic calcification) were annotated by 3 spine surgeons. Two independently trained, parallel networks were developed, including a ResNet-based segmentation network and a YOLOv8-based detection network. A rule-based integration strategy reconciled both outputs and generated structured diagnostic reports. Segmentation accuracy, quantitative measurement agreement, diagnostic performance, and clinical acceptability of reports were evaluated.
Results Intra- and interobserver landmark distances within 3 mm reached 96% and >95%, respectively. On the internal test set, the percentage of correct keypoints within 3 mm was 95.7%–98.6%, with intraclass correlation coefficients of 0.84–0.89 and Pearson correlation coefficient (r) of 0.90–0.94 for key radiographic parameters. The segmentation- and detection-based models achieved precision of 92.2%–96.9% and 91.7%–95.5%, and recall of 91.6%–94.8% and 93.3%–95.2%, respectively. Under the dual-positive condition, the integrated model yielded the highest precision (93.8%–97.3%), whereas the any-positive condition achieved the highest recall (94.1%–97.6%). Of 596 automatically generated structured reports, 557 (93.4%) were deemed clinically acceptable.
Conclusion The proposed dual-mechanism DL framework enables accurate, multilesion assessment of lumbar degeneration and generation of clinically acceptable structured reports from plain radiographs, supporting workflow optimization in lumbar spine imaging.
Objective Lumbar disc herniation is among the most common and disabling spinal disorders, driven by the interplay of mechanical overload, structural failure, and cellular dysfunction. Despite advances in surgical interventions, achieving true biological repair of herniated discs remains a major clinical challenge. This review aims to critically examine the biomechanical landscape of disc herniation, focusing on how altered load transmission, tissue stiffness, and structural disruption influence cellular behavior and tissue regeneration. It further explores mechanobiological mechanisms governing repair and highlights emerging biomimetic models and technologies that integrate mechanical and biological insights to promote functional disc restoration.
Methods A comprehensive literature review was conducted using the Web of Science Core Collection, PubMed (National Library of Medicine), and ScienceDirect databases. The search was limited to peer-reviewed journal articles published in English and focused on studies related to lumbar disc herniation.
Results While decades of research have elucidated the biomechanical factors contributing to disc herniation, recent advances in mechanobiology have uncovered how mechanical cues influence cellular behavior, tissue repair, and degeneration. Evidence suggests that true disc regeneration cannot be achieved through biological replacement or mechanical stabilization alone; rather, it requires restoring functional biomechanics, specifically, the disc’s ability to sense, adapt to, and sustain physiological loading.
Conclusion Viewing disc herniation through a mechanobiological lens offers new opportunities to develop targeted therapies aimed at restoring both tissue integrity and load-bearing functionality, paving the way for more effective regenerative interventions.
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Integrating Structures and Biology: Cellular and Molecular Interactions with Functionally Graded Spinal Cage Designs Yuen Ho Cheng, Amy Libing Fu, Jessica Gaff, Gianluca Vadala, Amit Jain, Javad Tavakoli International Journal of Molecular Sciences.2026; 27(10): 4531. CrossRef
Objective Uniportal full-endoscopic transforaminal lumbar interbody fusion (FE-TLIF) carries a unique risk of nerve traction and abrasion injury during cage insertion. This study aims to evaluate the clinical efficacy of the GUARD technique and delayed ligamentum flavectomy in reducing postoperative radicular pain and neurapraxia in patients undergoing uniportal FE-TLIF.
Methods A retrospective analysis was conducted on 45 patients with an average age of 53.9±12.4 years who underwent either FE facet-sparing TLIF (FE fs-TLIF) or FE facet-resecting TLIF (FE fr-TLIF). Patients were divided into 2 groups: the sentinel group (21 patients) using traditional sentinel pin techniques, and the GUARD group (24 patients) using the GUARD technique with delayed ligamentum flavectomy. Patient-reported outcomes included the visual analogue scale (VAS) for leg and back pain, and Oswestry Disability Index. Complication rates, including incidental durotomy, postoperative neurapraxia, and hematoma, were also documented.
Results Postoperative radicular pain in the legs was significantly reduced at 6 weeks in the GUARD group compared to the sentinel group (VAS: 2.201 vs. 3.267, p=0.021). The incidence of postoperative neurapraxia was markedly lower in the GUARD group (0% vs. 19%, p=0.047). Both groups showed similar improvements in disc height, segmental lordosis, and lumbar lordosis at the 1-year follow-up, with no significant differences in endplate injury or fusion rates.
Conclusion The GUARD technique and delayed ligamentum flavectomy significantly enhance patient safety by reducing postoperative radicular pain and neurapraxia without incurring additional costs. These techniques are easy to learn and integrate into existing surgical workflows, offering a valuable improvement for surgeons performing FE-TLIF procedures.
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Cage design-centric glider approach to full-endoscopic lumbar fusion: optimizing nerve root protection in facet-sparing and facet-resecting techniques Yu-Chia Hsu, Hao-Chun Chuang, Yuan-Fu Liu, Chao-Jui Chang, Yu-Meng Hsiao, Yi-Hung Huang, Keng-Chang Liu, Chien-Min Chen, Hyeun-Sung Kim, Cheng-Li Lin Asian Spine Journal.2026; 20(2): 343. CrossRef
Clinical and Radiological Outcomes of Double-Cage Full Endoscopic Transforaminal Lumbar Interbody Fusion Compared with Posterior Lumbar Interbody Fusion : A Retrospective Cohort Study Chi Ho Kim, Pius Kim, Chang Il Ju, Jong Hun Seo Journal of Korean Neurosurgical Society.2026;[Epub] CrossRef
Jacob R. Ball, Matthew C. Gallo, Kareem Kebaish, Nicole Hang, Andy Ton, Fergui Hernandez, Marc Abdou, William J. Karakash, Jeffrey C. Wang, Raymond J. Hah, Ram K. Alluri
Neurospine 2024;21(4):1068-1077. Published online December 31, 2024
Objective The purpose of this study is to describe utilization, demographics, complications, and revisions for patients with degenerative spondylolisthesis (DS) with stenosis undergoing decompression or decompression with fusion in the United States.
Methods A national insurance database was used to identify patients who underwent either decompression and fusion or decompression alone for management of DS from 2010–2022. Utilization trends, demographics, and complications for each procedure were compared.
Results A total of 162,878 patients were identified, of which 78,043 patients underwent combined single-level lumbar decompression and fusion and 84,835 underwent single-level lumbar decompression alone. Between 2010–2021, lumbar decompression and fusion became the predominant surgical intervention for DS in 2016 and continued to account for more than half of all procedures during the remainder of the study period. Factors such as age, sex, comorbidities, geographic region, and physician specialty training were associated with procedure choice. Decompression with fusion was associated with a lower risk of revision surgery up to 5 years postoperatively and an overall lower incidence of 30-day complications.
Conclusion Decompression with fusion has become the most common treatment for lumbar DS over the past decade despite a lack of compelling evidence supporting its use compared to decompression alone. A variety of patient and surgeon-specific factors is associated with procedure choice. After accounting for cofounders, we identified treatment-specific complications that may be valuable when counseling patients.
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Interspinous process fixation versus posterior lumbar interbody fusion following decompression for single-level grade I degenerative spondylolisthesis: a retrospective propensity score-matched study Jingbo Ma, Tusheng Li, Nan Shen, Rigbat Rozi, Yu Ding Journal of Orthopaedic Surgery and Research.2026;[Epub] CrossRef
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Large-Scale Analysis of Trends and Complications in Lumbar Spondylolisthesis Surgery: A Commentary on “National Trends in Lumbar Degenerative Spondylolisthesis With Stenosis Treated With Fusion Versus Decompression” Dong-Kyu Chin Neurospine.2024; 21(4): 1078. CrossRef
Siegmund Philipp Lang, Ezra Tilahun Yoseph, Aneysis D. Gonzalez-Suarez, Robert Kim, Parastou Fatemi, Katherine Wagner, Nicolai Maldaner, Martin N. Stienen, Corinna Clio Zygourakis
Neurospine 2024;21(2):633-641. Published online June 30, 2024
Objective In the digital age, patients turn to online sources for lumbar spine fusion information, necessitating a careful study of large language models (LLMs) like chat generative pre-trained transformer (ChatGPT) for patient education.
Methods Our study aims to assess the response quality of Open AI (artificial intelligence)’s ChatGPT 3.5 and Google’s Bard to patient questions on lumbar spine fusion surgery. We identified 10 critical questions from 158 frequently asked ones via Google search, which were then presented to both chatbots. Five blinded spine surgeons rated the responses on a 4-point scale from ‘unsatisfactory’ to ‘excellent.’ The clarity and professionalism of the answers were also evaluated using a 5-point Likert scale.
Results In our evaluation of 10 questions across ChatGPT 3.5 and Bard, 97% of responses were rated as excellent or satisfactory. Specifically, ChatGPT had 62% excellent and 32% minimally clarifying responses, with only 6% needing moderate or substantial clarification. Bard’s responses were 66% excellent and 24% minimally clarifying, with 10% requiring more clarification. No significant difference was found in the overall rating distribution between the 2 models. Both struggled with 3 specific questions regarding surgical risks, success rates, and selection of surgical approaches (Q3, Q4, and Q5). Interrater reliability was low for both models (ChatGPT: k = 0.041, p = 0.622; Bard: k = -0.040, p = 0.601). While both scored well on understanding and empathy, Bard received marginally lower ratings in empathy and professionalism.
Conclusion ChatGPT3.5 and Bard effectively answered lumbar spine fusion FAQs, but further training and research are needed to solidify LLMs’ role in medical education and healthcare communication.
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Objective This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans.
Methods Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness.
Results The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements.
Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.
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Objective To evaluate the preoperative and perioperative predictors of persistent leg numbness following lumbar fusion in patients aged ≥ 75 years.
Methods This single-center retrospective study examined 304 patients aged ≥ 75 years who underwent lumbar fusion for lumbar degenerative disease (102 men, 202 women; mean age, 79.2 [75–90] years). The visual analogue scale (VAS) score for leg numbness was examined preoperatively and at 2 years postoperatively. The persistent leg numbness group included patients with a 2-year postoperative VAS score for leg numbness ≥ 5 points. The demographic data were also reviewed. A multivariate stepwise logistic regression analysis was performed for variables with univariate analysis values of p < 0.2 on univariate analysis.
Results In total, 71 patients (23.4%) experienced persistent postoperative leg numbness. Multivariate logistic regression analysis revealed that a history of lumbar decompression, longer symptom duration, and a preoperative VAS score for leg numbness ≥ 5 points were associated with greater postoperative persistent leg numbness following lumbar fusion. In contrast, other factors, such as sex, body mass index, vertebral fracture, diabetes mellitus, depression, symptom duration, dural injury, operative time, and estimated blood loss, were not.
Conclusion A history of preoperative lumbar decompression, longer symptom duration, and greater preoperative VAS scores for leg numbness were preoperative predictors of persistent postoperative leg numbness following lumbar fusion in older patients. Although lumbar fusion is expected to improve leg numbness, surgeons should consider the surgical history, duration, and preoperative numbness intensity and explain the potential postoperative persistent leg numbness in advance.
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Objective Precise knowledge regarding the mechanical stress applied to the intervertebral disc following each individual spine motion enables physicians and patients to understand how people with discogenic back pain should be guided in their exercises and which spine motions to specifically avoid. We created an intervertebral disc degeneration model and conducted a finite element (FE) analysis of loaded stresses following each spinal posture or motion.
Methods A 3-dimensional FE model of intervertebral disc degeneration at L4–5 was constructed. The intervertebral disc degeneration model was created according to the modified Dallas discogram scale. The von Mises stress and range of motion (ROM) regarding the intervertebral discs and the endplates were analyzed.
Results We observed that mechanical stresses loaded onto the intervertebral discs were similar during flexion, extension, and lateral bending, which were greater than those occurring during torsion. Based on the comparison among the grades divided by the modified Dallas discogram scale, the mechanical stress during extension was greater in grades 3–5 than it was during the others. During extension, the mechanical stress loaded onto the intervertebral disc and endplate was greatest in the posterior portion. Mechanical stresses loaded onto the intervertebral disc were greater in grades 3–5 compared to those in grades 0–2.
Conclusion Our findings suggest that it might be beneficial for patients experiencing discogenic back pain to maintain a neutral posture in their lumbar spine when engaging in daily activities and exercises, especially those suffering from significant intravertebral disc degeneration.
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Objective To analyze the usage of floor-mounted robot in minimally invasive lumbar fusion.
Methods Patients who underwent minimally invasive lumbar fusion for degenerative pathology using floor-mounted robot (ExcelsiusGPS) were included. Pedicle screw accuracy, proximal level violation rate, pedicle screw size, screw-related complications, and robot abandonment rate were analyzed.
Results Two hundred twenty-nine patients were included. Most surgeries were primary single-level fusion. Sixty-five percent of surgeries had intraoperative computed tomography (CT) workflow, 35% had preoperative CT workflow. Sixty-six percent were transforaminal lumbar interbody fusion, 16% were lateral, 8% were anterior, and 10% were a combined approach. A total of 1,050 screws were placed with robotic assistance (85% in prone position, 15% in lateral position). Postoperative CT scan was available for 80 patients (419 screws). Overall pedicle screw accuracy rate was 96.4% (prone, 96.7%; lateral, 94.2%; primary, 96.7%; revision, 95.3%). Overall poor screw placement rate was 2.8% (prone, 2.7%; lateral, 3.8%; primary, 2.7%; revision, 3.5%). Overall proximal facet and endplate violation rates were 0.4% and 0.9%. Average diameter and length of pedicle screws were 7.1 mm and 47.7 mm. Screw revision had to be done for 1 screw (0.1%). Use of the robot had to be aborted in 2 cases (0.8%).
Conclusion Usage of floor-mounted robotics for the placement of lumbar pedicle screws leads to excellent accuracy, large screw size, and negligible screw-related complications. It does so for screw placement in prone/lateral position and primary/revision surgery alike with negligible robot abandonment rates.
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Conclusion Both PAMT and PTET can achieve Eden type III-IV lumbar 1-stage tumor resection without additional spinal internal fixation due to reduced muscle, ligament, and facet joint damage. No lumbar instability and tumor recurrence occurred, and neurological function was improved.
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Neurospine 2021;18(4):725-732. Published online December 31, 2021
Objective To study the impact of demographic factors on management of traumatic injury to the lumbar spine and postoperative complication rates.
Methods Data was obtained from the National Inpatient Sample (NIS) between 2010–2014. International Classification of Diseases, 9th revision, Clinical Modification codes identified patients diagnosed with lumbar fractures or dislocations due to trauma. A series of multivariate regression models determined whether demographic variables predicted rates of complication and revision surgery.
Results A total of 38,249 patients were identified. Female patients were less likely to receive surgery and to receive a fusion when undergoing surgery, had higher complication rates, and more likely to undergo revision surgery. Medicare and Medicaid patients were less likely to receive surgical management for lumbar spine trauma and less likely to receive a fusion when operated on. Additionally, we found significant differences in surgical management and postoperative complication rates based on race, insurance type, hospital teaching status, and geography.
Conclusion Substantial differences in the surgical management of traumatic injury to the lumbar spine, including postoperative complications, among individuals of demographic factors such as age, sex, race, primary insurance, hospital teaching status, and geographic region suggest the need for further studies to understand how patient demographics influence management and complications for traumatic injury to the lumbar spine.
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