Spine最新文献

Study design: Retrospective Cohort Study.

Objective: To quantify the pathology of the spine in patients with scoliosis through one-dimensional feature analysis.

Summary of background data: Biplanar radiograph (EOS) imaging is a low-dose technology offering high-resolution spinal curvature measurement, crucial for assessing scoliosis severity and guiding treatment decisions. Machine learning (ML) algorithms, utilizing one-dimensional image features, can enable automated Cobb angle classification, improving accuracy and efficiency in scoliosis evaluation while reducing the need for manual measurements, thus supporting clinical decision-making.

Methods: This study used 816 annotated AP EOS spinal images with a spine segmentation mask and a 10-degree polynomial to represent curvature. Engineered features included the first and second derivatives, Fourier transform, and curve energy, normalized for robustness. XGBoost selected the top 32 features. The models classified scoliosis into multiple groups based on curvature degree, measured through Cobb angle. To address class imbalance, stratified sampling, undersampling, and oversampling techniques were employed, with 10-fold stratified K-fold cross-validation for generalization. An automatic grid search was used for hyperparameter optimization, with K-fold cross-validation (K=3).

Results: The top-performing model was Random Forest, achieving an ROC AUC of 91.8%. An accuracy of 86.1%, precision of 86.0%, recall of 86.0%, and an F1 score of 85.1% were also achieved. Of the three techniques employed to address class imbalance, stratified sampling produced the best out-of-sample results. SHAP values were generated for the top 20 features, including spine curve length and linear regression error, with the most predictive features ranked at the top, enhancing model explainability.

Conclusions: Feature engineering with classical ML methods offers an effective approach for classifying scoliosis severity based on Cobb angle ranges. The high interpretability of features in representing spinal pathology, along with the ease of use of classical ML techniques, makes this an attractive solution for developing automated tools to manage complex spinal measurements.

Study design: Prospective observational cohort.

Objectives: To report on the role of a single wearable sensor in the evaluation of patients with Cervical Spondylotic Myelopathy (CSM).

Summary of background data: Clinical evaluation of CSM is limited, as Hoffmann's sign, Romberg testing and Tandem Gait are largely subjective and binary, making deterioration or improvement difficult to document accurately.

Methods: Patients scheduled for surgical treatment of CSM underwent in-office and 24-hour continuous at-home data collection using a single wearable sensor. In-office testing consisted of Standing, Romberg testing, Tandem Gait and Timed Up & Go (TUG). Testing was repeated 6-months post-operatively.

Results: Statistically significant improvements were seen following surgical treatment in the Romberg test eyes-open maximum antero-posterior sway (P=0.010), eyes-open total path traveled (P=0.048); in Tandem Gait speed (P=0.021), duration (P=0.002), antero-posterior sway (P=0.046) and initial peak acceleration (P=0.001). There was no statistically significant difference in TUG testing. At-home gait pattern revealed a trend toward decreased lateral sway post-operatively (P=0.062) and fewer sleep turns (P=0.078).

Conclusion: Wearable sensor data effectively quantifies standard exam findings and identifies new metrics with the potential to assess more accurately pre-operative and post-operative function in patients with CSM. Previously unreported pre-operative to 6-month post-operative changes were seen in speed of gait and ground impact force during Tandem Gait. These metrics were more sensitive as compared to the normal antero-posterior and lateral sway assessment. 24-hour sensor data showed decreased number of turns during sleep post-operatively. This study suggests that wearable sensor data will be a viable source for quantifiable data with the potential to guide treatment for patients with CSM. This capability is based partly on better quantification of existing binary measures, but also on identification of unanticipated patterns within the data.

Study design: A retrospective real-world study.

Objective: Using machine learning models to identify risk factors for residual pain after PLIF in patients with degenerative lumbar spine disease.

Summary of background data: Residual pain after PLIF is a frequent phenomenon, and the specific risk factors for residual pain are not known.

Materials and methods: Between June 2018 and March 2023, 936 patients with lumbar degenerative disease who underwent PLIF surgery were recruited. Group A (n=501) had <7 days of VAS ≥3 pain within 1 month post-PLIF, while Group B (n=435) had ≥7 days. Imaging outcomes included PMI, MMI, MMD, lumbar lordosis (LL), and LL improvement rate. Functional outcomes were assessed by VAS. Univariate and multivariate logistic regression analyses were used to determine the potential risk of short-term postoperative pain. Risk factors were identified using machine learning models and predicted whether residual pain would occur.

Results: A total of 435 (46.5%) patients experienced residual postoperative pain. Independent risk factors included surgical segment, PMI, MMI, and depression level. The Random Forest Model model had an accuracy of 95.7%, a sensitivity of 96.4%, a specificity of 94.1%, and an F1 score of approximately 95.2% for predicting recurrent pain, indicating high reliability and generalizability.

Conclusions: Our study reveals risk factors for the development of residual pain after PLIF. Compared to the group with residual pain, the group without pain had more robust paravertebral muscles, improved psychological characteristics and a greater LL improvement rate. These factors may represent targets for pre-operative and peri-operative optimization as a means to minimize the potential for residual pain following PLIF.

Study design: Randomized controlled trial.

Objective: The aim of this study was to investigate whether instrumented posterolateral fusion is cost-effective compared to un-instrumented posterolateral fusion in elderly patients who undergo fusion surgery for one-level degenerative spondylolisthesis with spinal stenosis.

Summary of background data: For patients with persistent symptoms due to degenerative spondylolisthesis, surgical intervention may be recommended, typically decompression and fusion. Evidence on cost-effectiveness of choice of fusion method, related complications and outcome is sparse.

Methods: This cost-effectiveness analysis is based on a single-center, open label, randomized controlled trial, where patients with symptomatic degenerative spondylolisthesis were randomly assigned 1:1 to either instrumented or un-instrumented posterolateral fusion. Quality-Adjusted Life Years were obtained from EQ-5D. Use of health services were obtained from patient charts and accumulated until 2 years after index surgery.

Results: Of the 108 patients included in the study, 107 patients received the allocated intervention. There were no differences in preoperative demographics. Although the base price for the index instrumented surgery was significantly higher than the index uninstrumented surgery, average cost of surgery was only €146 higher in the instrumented group based on two-year cost data. The instrumented fusion group had a significantly lower reoperation rate (1/54 (1.9%)) than the uninstrumented fusion group 7/53 (13.2%), significantly less visits to the outpatient clinic, less Magnetic Resonance Imaging performed and fewer days of hospitalization. The base case incremental cost-effectiveness ratio was estimated at €1,536 per QALY gained over a two-year time horizon. Instrumented fusion was favored over uninstrumented fusion in sensitivity analyses including all reoperations or using hospital reimbursement rate.

Conclusion: Insturumented fusion is cost-effective compared uninstrumented fusion, with an incremental cost-effectiveness ration well below the standard range of cost-effectivenes, the difference in cost was driven by lower re-operation rates and less healthcare resource utilization over a two-year time horizon.

Study design: Retrospective review of a prospectively collected single-center adolescent idiopathic scoliosis (AIS) database.

Objective: To evaluate the incidence and predictors of growth modulation and overcorrection after vertebral body tethering (VBT) in AIS.

Background: Little data exists regarding which AIS patients will exhibit growth modulation and/or overcorrection after VBT compared to those whose curve correction will remain unchanged (no modulation).

Materials and methods: A total of 279 patients with AIS with a minimum 2-year follow-up (range 2-10 years) were included. There were 262 thoracic and 65 thoracolumbar VBT surgeries performed. Univariate and multivariate regression analyses were performed to identify the potential clinical/radiographic predictive factors for growth modulation and overcorrection.

Results: Patients with growth modulation and those with no modulation after thoracic VBT were significantly more immature (younger, premenarchal, lower Sanders score/Risser grade, open triradiate cartilage [TRC]) and physically smaller (lower height, weight, and body mass index [BMI]; P<0.02). Patients with growth modulation vs. no modulation after thoracolumbar VBT had lower preoperative Sanders score, weight, and BMI (P<0.04). Preoperative and first-erect thoracic and lumbar curve magnitudes did not affect growth modulation vs. no modulation. Patients with thoracic overcorrection were physically smaller (lower height/weight/BMI) and had lower preoperative and first-erect thoracic curves than patients with growth modulation without overcorrection (P<0.04). Patients with thoracolumbar overcorrection had open-TRC and lower first-erect lumbar curves than patients with growth modulation without overcorrection (P<0.04). Open-TRC (odds ratio: 6.8, P<0.001) and lower BMI (P<0.001) were the only significant predictive factors for thoracic growth modulation in multivariate analysis; none were identified for thoracolumbar growth modulation. Sixty-four percent of patients with overcorrection required revision surgery versus 18% of those with no modulation (P<0.001).

Conclusion: AIS patients with open-TRC and lower BMI had a statistically higher rate of thoracic growth modulation and overcorrection after VBT in multivariate analysis. Preoperative and first-erect curve magnitudes did not affect the incidence of growth modulation.

Study design: Observational epidemiological study.

Objective: To identify and comprehensively assess reasons for recalls of spinal implant devices used in patients over the past 21 years.

Summary of background data: The number of spine implant devices on the market continues to rise. Although the Food and Drug Administration (FDA) regulates the safety of these devices, there is a paucity of literature on the reasons spine implant devices are recalled.

Methods: The FDA device recall database was queried using the search term "spine" for recalls between 2003 and 2024. Data were collected regarding recall class, recall reason, FDA 510(k)/premarket approval decision date, product manufacturer, and device indication. The data was then reviewed to identify recalls for spine implant devices.

Results: A total of 386 spine implant devices were identified between January 2003 and December 2024. Among all recalls classified, 3.4% (n=13) were class I, 88.1% (n=340) were class II, and 8.5% (n=33) were class III. The most common reasons for recall were "Device/Component design" (52.8%) and "Packing/Processing Control" (24.1%). The median number of devices recalled by manufacturers included in the study was two with the highest being 41 devices.

Conclusions: Overall, 76.9% of spine implant recalls reviewed were primarily due to issues with device design and processing control. 88.1% of recalls were classified with a class II FDA designation. This is the first study to present a retrospective regulatory analysis of FDA spine implant recalls and highlights the importance of premarket analysis and postmarketing surveillance to improve device safety.

Level of evidence: 4.

Study design: Retrospective case-control study.

Objective: To evaluate clinical outcomes of cervical microendoscopic laminotomy (CMEL) and segmental partial laminectomy (SPL) in patients with cervical spondylotic myelopathy (CSM).

Summary of background data: CSM often requires posterior decompression surgery. Conventional techniques such as laminoplasty and SPL are associated with significant challenges, including axial neck pain and reduced cervical range of motion (ROM). In contrast, CMEL, a minimally invasive approach, may offer superior outcomes. However, direct comparisons with SPL remain limited.

Methods: We retrospectively analyzed 105 patients (58 with CMEL and 47 with SPL) who underwent posterior decompression surgery for CSM between 2003 and 2020. The evaluated outcomes included intraoperative parameters, postoperative clinical measures (e.g., Neck Disability Index (NDI), Japanese Orthopaedic Association (JOA) scores, including recovery rate and treatment satisfaction), radiographic assessments, and complication rates.

Results: Compared to SPL, CMEL resulted in reduced blood loss, shorter hospital stay, less postoperative neck pain, ROM preservation, and fewer complications at 1 year postoperatively.

Conclusions: CMEL is a minimally invasive alternative to SPL, providing reduced morbidity and improved outcomes. This is particularly true for aging populations that require functional preservation and quality of life improvement. By avoiding instruments such as interlaminar spacers and implants, CMEL can potentially reduce healthcare costs.

Study design: Preclinical experimental study.

Objective: To explore the use of hydrogels as bioactive scaffolds for encapsulating bone marrow mesenchymal stem cells (BMSCs) to enhance their therapeutic potential in spinal cord injury (SCI). This study further aims to evaluate the added value of a BMP7 nanoparticle delivery system in overcoming the limitations of BMSCs alone for SCI repair.

Summary of background data: SCI leads to significant neuron loss and functional impairment. While BMSC-based stem cell therapies show promise, their efficacy is limited by challenges such as the instability of bone morphogenetic protein (BMP)-7 in inducing neuronal differentiation. High concentrations of BMP7, though effective in promoting neuronal differentiation, may cause inflammation, necessitating the development of a delivery system for sustained and localized release.

Methods: BMSCs were isolated from Sprague-Dawley rats, and BMP-7's effects on neuronal differentiation were assessed via western blotting. BMP7-loaded nanoparticles (NPs) and BMSCs were co-loaded into a gelatin methacrylate (Gel-MA) hydrogel scaffold, with a cell loading density of 1 × 10⁵ cells/μl. BMP7 was encapsulated at a 0.04% (w/V) concentration, corresponding to approximately 0.4 ng BMP7 per μl of hydrogel. Optimization was performed using mechanical, cytotoxicity, and neuronal marker analyses. Scaffold properties, including water absorption, BMP7 release, and BMSC morphology, were characterized. Therapeutic efficacy was evaluated in a rat SCI model using motor function recovery, histological analysis, and molecular assessments.

Results: BMP-7 effectively promoted BMSC differentiation into neurons while suppressing glial cell development. The BMP7-NPs/Gel-MA scaffold ensured sustained BMP7 release, achieving optimal differentiation at a 0.04% (w/V) BMP7 concentration. In vivo, the scaffold combined with BMSCs enhanced neuronal proliferation and differentiation, stimulated myelin regeneration, reduced lesion volume, and significantly improved motor function recovery.

Conclusion: The BMP7-NPs/Gel-MA scaffold provides sustained delivery of BMP-7, effectively directing BMSC differentiation into neuron-like cells while avoiding glial commitment. Combined with BMSCs, it offers a promising therapeutic strategy for SCI repair.

Study design: Systematic Review.

Objective: To determine the incidence of inappropriate or uncertain implementation of the Minimally Important Clinical Difference (MCID) for the Neck Disability Index (NDI).

Summary of background data: The NDI consists of 10 items that yield a total score out of 50, but some users double the scale to report total scores out of 100. The most used MCID for the NDI is 7.5 out of 50. Implementation of the MCID can be problematic if users are not attentive to the scale of the NDI.

Methods: We performed a methodological review of studies that cited the MCID for the NDI. We defined appropriate implementation as congruent magnitude of the scales used for NDI data and the MCID. We evaluated study characteristics associated with appropriate implementation using multivariable logistic regression.

Results: Among 163 included studies, twenty (12%) reported a 0-50 scale for the NDI, 66 (40%) reported a 0-100 scale, and the remaining 77 (47%) did not report which scale was used. Fifty-seven (35%) reported an MCID of 7.5, 37 (23%) reported an MCID of 15, and the remaining 69 (42%) did not report which value of the MCID used. Appropriate implementation of the MCID occurred in 39 studies (24%), while implementation was inappropriate in 16 (10%) and uncertain due to poor reporting in 108 (66%). Studies published more recently (OR 1.20 per year, 95% CI 1.02 to 1.40, P=0.03) and studies that were RCTs (OR 4.85, 95% CI 1.25 to 18.79, P=0.02) had greater odds of being associated with appropriate implementation.

Conclusions: Inappropriate implementation of the MCID for the NDI is problematic and occurs often, and uncertain implementation due to poor reporting is also common. Evidence users should be cautious when interpreting studies that implement the NDI, and should consider whether the magnitude of the scales used for the NDI and the MCID are congruent.