Aims. This systematic review aims to identify 3D predictors derived from biplanar reconstruction, and to describe current methods for improving curve prediction in patients with mild adolescent idiopathic scoliosis. Methods. A comprehensive search was conducted by three independent investigators on MEDLINE, PubMed, Web of Science, and Cochrane Library. Search terms included “adolescent idiopathic scoliosis”,“3D”, and “progression”. The inclusion and exclusion criteria were carefully defined to include clinical studies. Risk of bias was assessed with the Quality in Prognostic Studies tool (QUIPS) and Appraisal tool for Cross-Sectional Studies (AXIS), and level of evidence for each predictor was rated with the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. In all, 915 publications were identified, with 377 articles subjected to full-text screening; overall, 31 articles were included. Results. Torsion index (TI) and apical vertebral rotation (AVR) were identified as accurate predictors of curve progression in early visits. Initial TI > 3.7° and AVR > 5.8° were predictive of curve progression. Thoracic hypokyphosis was inconsistently observed in progressive curves with weak evidence. While sagittal wedging was observed in mild curves, there is insufficient evidence for its correlation with curve progression. In curves with initial Cobb angle < 25°, Cobb angle was a poor predictor for future curve progression. Prediction accuracy was improved by incorporating serial reconstructions in stepwise layers. However, a lack of post-hoc analysis was identified in studies involving geometrical models. Conclusion. For patients with mild curves, TI and AVR were identified as predictors of curve progression, with TI > 3.7° and AVR > 5.8° found to be important thresholds. Cobb angle acts as a poor predictor in mild curves, and more investigations are required to assess thoracic kyphosis and wedging as predictors. Cumulative reconstruction of radiographs improves prediction accuracy. Comprehensive analysis between progressive and non-progressive curves is recommended to extract meaningful thresholds for clinical prognostication. Cite this article: Bone Jt Open 2024;5(3):243–251

Aims. To develop and internally validate a preoperative clinical prediction model for acute adjacent vertebral fracture (AVF) after vertebral augmentation to support preoperative decision-making, named the after vertebral augmentation (AVA) score. Methods. In this prognostic study, a multicentre, retrospective single-level vertebral augmentation cohort of 377 patients from six Japanese hospitals was used to derive an AVF prediction model. Backward stepwise selection (p < 0.05) was used to select preoperative clinical and imaging predictors for acute AVF after vertebral augmentation for up to one month, from 14 predictors. We assigned a score to each selected variable based on the regression coefficient and developed the AVA scoring system. We evaluated sensitivity and specificity for each cut-off, area under the curve (AUC), and calibration as diagnostic performance. Internal validation was conducted using bootstrapping to correct the optimism. Results. Of the 377 patients used for model derivation, 58 (15%) had an acute AVF postoperatively. The following preoperative measures on multivariable analysis were summarized in the five-point AVA score: intravertebral instability (≥ 5 mm), focal kyphosis (≥ 10°), duration of symptoms (≥ 30 days), intravertebral cleft, and previous history of vertebral fracture. Internal validation showed a mean optimism of 0.019 with a corrected AUC of 0.77. A cut-off of ≤ one point was chosen to classify a low risk of AVF, for which only four of 137 patients (3%) had AVF with 92.5% sensitivity and 45.6% specificity. A cut-off of ≥ four points was chosen to classify a high risk of AVF, for which 22 of 38 (58%) had AVF with 41.5% sensitivity and 94.5% specificity. Conclusion. In this study, the AVA score was found to be a simple preoperative method for the identification of patients at low and high risk of postoperative acute AVF. This model could be applied to individual patients and could aid in the decision-making before vertebral augmentation. Cite this article: Bone Joint J 2022;104-B(1):97–102

Introduction

Developments in the use of ultrasound during pregnancy for assessment of fetal spine abnormalities indicate a need for accurate information about the antenatal development of the vertebral column. The published work is deficient in this regard, with available data examining only the period of 8–26 weeks. The aims of this study are to establish antenatal spine growth curves with fetal radiographs, to establish growth velocity curves for each anatomical spinal, region and to calculate the multiplier factor during antenatal life.

We compared a group of 46 somatised patients with a control group of 41 non-somatised patients who had undergone elective surgery to the lumbar spine in an attempt to identify pre-operative factors which could predict the outcome. In a prospective single-centre study, the Distress and Risk Assessment method consisting of a modified somatic perception questionnaire and modified Zung depression index was used pre-operatively to identify somatised patients. The type and number of consultations were correlated with functional indicators of outcome, such as the Oswestry disability index and a visual analogue score for pain in the leg after follow-up for six and 12 months.

Similar improvements in the Oswestry disability index were found in the somatised and non-somatised groups. Somatised patients who had a good outcome on the Oswestry disability index had an increased number of orthopaedic consultations (50 of 83 patients (60%) vs 29 of 73 patients (39.7%); p = 0.16) and waited less time for their surgery (5.5 months) (sd 5.26) vs 10.1 months (sd 6.29); p = 0.026). No other identifiable factors were found. A shorter wait for surgery appeared to predict a good outcome. Early review by a spinal surgeon and a reduced waiting time to surgery appear to be of particular benefit to somatised patients.

Aim:

To compare the ability of fulcrum bend and traction radiographs to predict correction of AIS using pedicle screw only constructs and to compare the fulcrum bending correction index (FBCI) with a new measurement: the traction correction index (TCI).

To compare the ability of fulcrum bend and traction radiographs to predict correction of AIS using screw only implants and to assess the fulcrum bending correction index (FBCI) with a new measurement: the traction correction index (TCI)

Retrospective radiographic analysis of case series (Level IV)

Radiographic correction of scoliosis based on correction rate does not take into consideration the curve flexibility. It has been suggested that fulcrum bending radiographs predict curve correction in AIS [1]. This has been questioned [2] and has been suggested that traction radiographs are more predictive in a mixed group of patients with hybrid and screw only constructs.

Twenty three patients average age 15, who underwent posterior correction of scoliosis using pedicle screw only construct.

Analysis was carried out on the pre-op and immediate post-op AP radiographs and the pre-op fulcrum bend and traction radiographs. Correction rate, fulcrum flexibility, traction flexibility, FBCI and TCI was calculated.

Preoperative mean Cobb angle of 66 degrees was corrected to 25 degrees postoperatively. The mean fulcrum bending Cobb angle was 38 degrees and traction Cobb angle 28 degrees. The mean fulcrum flexibility was 45%, traction flexibility 59% and correction rate 63%. The mean FBCI was 182% and TCI was112%.

When comparing fulcrum bend and traction radiographs, we found the latter to be more predictive of curve correction in AIS using pedicle screw constructs. The TCI better takes into account the curve flexibility than the FBCI.

Aims. To determine the major risk factors for unplanned reoperations (UROs) following corrective surgery for adult spinal deformity (ASD) and their interactions, using machine learning-based prediction algorithms and game theory. Methods. Patients who underwent surgery for ASD, with a minimum of two-year follow-up, were retrospectively reviewed. In total, 210 patients were included and randomly allocated into training (70% of the sample size) and test (the remaining 30%) sets to develop the machine learning algorithm. Risk factors were included in the analysis, along with clinical characteristics and parameters acquired through diagnostic radiology. Results. Overall, 152 patients without and 58 with a history of surgical revision following surgery for ASD were observed; the mean age was 68.9 years (SD 8.7) and 66.9 years (SD 6.6), respectively. On implementing a random forest model, the classification of URO events resulted in a balanced accuracy of 86.8%. Among machine learning-extracted risk factors, URO, proximal junction failure (PJF), and postoperative distance from the posterosuperior corner of C7 and the vertical axis from the centroid of C2 (SVA) were significant upon Kaplan-Meier survival analysis. Conclusion. The major risk factors for URO following surgery for ASD, i.e. postoperative SVA and PJF, and their interactions were identified using a machine learning algorithm and game theory. Clinical benefits will depend on patient risk profiles. Cite this article: Bone Joint Res 2023;12(4):245–255

Introduction. Vertebral compression fractures are the most common type of osteoporotic fracture. Though 89% of clinical fractures occur anteriorly, it is challenging to replicate these ex vivo with the underlying intervertebral discs (IVDs) present. Furthermore, the role of disc degeneration in this mechanism is poorly understood. Understanding how disc morphology alters vertebral strain distributions may lead to the utilisation of IVD metrics in fracture prediction, or inform surgical decision-making regarding instrumentation type and placement. Aim. To determine the effect of disc degeneration on the vertebral trabecular bone strain distributions in axial compression and flexion loading. Methods. Eight cadaveric thoracolumbar segments (T11-L3) were prepared (N=4 axial compression, N=4 flexion). µCT-based digital volume correlation was used to quantify trabecular strains. A bespoke loading device fixed specimens at the resultant displacement when loaded to 50N and 800N. Flexion was achieved by adding 6° wedges. Disc degeneration was quantified with Pfirrmann grading and T2 relaxation times. Results. Anterior axial strains were 80.9±39% higher than the posterior region in flexion (p<0.01), the ratio of which was correlated with T2 relaxation time (R. 2. =0.80, p<0.05). In flexion, the central-to-peripheral axial strain ratio in the endplate region was significantly higher when the underlying IVDs were non-degenerated relative to degenerated (+38.1±12%, p<0.05). No significant differences were observed in axial compression. Conclusion. Disc degeneration is a stronger determinant of the trabecular strain distribution when flexion is applied. Load transfer through non-degenerate IVDs under flexion appears to be more centralised, suggesting that disc degeneration predisposes flexion-type compression fractures by shifting high strains anteriorly. Conflicts of interest. The authors declare none. Sources of funding. This work was funded by the Engineering & Physical Sciences Research Council (EP/V029452/1), and Back-to-Back

Aims. The aim of this study was to determine the influence of developmental spinal stenosis (DSS) on the risk of re-operation at an adjacent level. Patients and Methods. This was a retrospective study of 235 consecutive patients who had undergone decompression-only surgery for lumbar spinal stenosis and had a minimum five-year follow-up. There were 106 female patients (45.1%) and 129 male patients (54.9%), with a mean age at surgery of 66.8 years (. sd. 11.3). We excluded those with adult deformity and spondylolisthesis. Presenting symptoms, levels operated on initially and at re-operation were studied. MRI measurements included the anteroposterior diameter of the bony spinal canal, the degree of disc degeneration, and the thickness of the ligamentum flavum. DSS was defined by comparative measurements of the bony spinal canal. Risk factors for re-operation at the adjacent level were determined and included in a multivariate stepwise logistic regression for prediction modelling. Odds ratios (ORs) with 95% confidence intervals were calculated. Results. Of the 235 patients, 21.7% required re-operation at an adjacent segment. Re-operation at an adjacent segment was associated with DSS (p = 0.026), the number of levels decompressed (p = 0.008), and age at surgery (p = 0.013). Multivariate regression model (p < 0.001) controlled for other confounders showed that DSS was a significant predictor of re-operation at an adjacent segment, with an adjusted OR of 3.93. Conclusion. Patients with DSS who have undergone lumbar spinal decompression are 3.9 times more likely to undergo future surgery at an adjacent level. This is a poor prognostic indicator that can be identified prior to index decompression surgery

Aims

Scoliosis is a lateral curvature of the spine with associated rotation, often causing distress due to appearance. For some curves, there is good evidence to support the use of a spinal brace, worn for 20 to 24 hours a day to minimize the curve, making it as straight as possible during growth, preventing progression. Compliance can be poor due to appearance and comfort. A night-time brace, worn for eight to 12 hours, can achieve higher levels of curve correction while patients are supine, and could be preferable for patients, but evidence of efficacy is limited. This is the protocol for a randomized controlled trial of ‘full-time bracing’ versus ‘night-time bracing’ in adolescent idiopathic scoliosis (AIS).

Aims. Clinical decision support systems (CDSS) can support clinicians in selecting appropriate treatments for patients. The objective of this study was to examine if triaging patients with LBP to the most optimal treatment can be improved by using a data-driven approach with the help of machine learning as base of such a CDSS. Methods. A clinical database of the Groningen Spine Center containing patient-reported data from 1546 patients with LBP was used. From this dataset, a training dataset with 354 features was labeled on eight different treatments actually received by these patients. With this dataset, models were trained. A test dataset with 50 cases judged on treatments by 4 experts in LBP triage was used to test these models with data not used to train the models. Prediction accuracy and average area under curve (AUC) were used as performance measures for the models. Results. The AUC values indicated small to medium learning effects showing that machine learning on patient-reported data, to model decision-making processes on treatments for LBP, may be possible. One of the best performing models was the Bayesian Network (BN) model; e.g. predicted surgery with accuracy 0.78 (95% C.I. 0.68– 0.87) and AUC 0.70. Conclusion. Benefits to using BNs compared to other supervised machine learning techniques are that it is easy to exploit expert knowledge in BN models, meaning that advices generated by the model can be explained. The next step is to improve the BN accuracy so that it can actually be used in a CDSS. No conflicts of interest. Sources of funding: This work is partly funded by a grant from the Netherlands Organization for Health Research and Development (ZonMw), grant 10-10400-98-009

Purpose and background. There is lacking evidence about the prognostic role of anxiety as prognostic in acute low back pain patients. The objective of this study was to determine whether patients with acute low back pain (ALBP) are at risk to develop chronic low back pain (CLBP) and pain-related disability after 12 weeks due to high anxiety levels. Methods and results. An observational multi-centre study was conducted in primary physiotherapy care with measurements at baseline and at 12 weeks including known prognostic factors and psychological candidate predictors for CLBP. Two hundred and four participants completed both assessments of which 51 and 54 were classified as having less than 50% decrease in pain and pain-related disability, respectively. For pain, the final model contained higher pain intensity, longer pain duration, depression symptoms, and state anxiety with explained variance 0.30, sensitivity 0.74, specificity 0.82, Likelihood Ratio 4.1 (95% CI 2.0 to 6.1) and Area Under the Curve 0.78 (95% CI 0.70 to 0.85). For pain-related disability, trait anxiety, depression symptoms, and state anxiety contributed independently to the prediction with the model's explained variance of 0.19, sensitivity 0.78, specificity 0.78, Likelihood Ratio 3.0 (95% CI 2.0 to 4.5), and Area Under the Curve 0.73 (95% CI 0.65 to 0.81). Conclusion. State anxiety in patients with ALBP is an independent predictor of CLBP at 12 weeks after baseline in primary physiotherapy care and should be measured, in addition to known prognostic factors and depression symptoms, in order to intervene and potentially decrease duration of complaints. No conflict of interest. No funding obtained

Aims

Lumbar spinal stenosis (LSS) is a common skeletal system disease that has been partly attributed to genetic variation. However, the correlation between genetic variation and pathological changes in LSS is insufficient, and it is difficult to provide a reference for the early diagnosis and treatment of the disease.

Aims

Traumatic central cord syndrome (CCS) typically follows a hyperextension injury and results in motor impairment affecting the upper limbs more than the lower, with occasional sensory impairment and urinary retention. Current evidence on mortality and long-term outcomes is limited. The primary aim of this study was to assess the five-year mortality of CCS, and to determine any difference in mortality between management groups or age.

Aims

Repeated lumbar spine surgery has been associated with inferior clinical outcomes. This study aimed to examine and quantify the impact of this association in a national clinical register cohort.

Aims

The aim of this study was to assess the ability of morphological spinal parameters to predict the outcome of bracing in patients with adolescent idiopathic scoliosis (AIS) and to establish a novel supine correction index (SCI) for guiding bracing treatment.

Aims

Anchorage of pedicle screw rod instrumentation in the elderly spine with poor bone quality remains challenging. Our study aims to evaluate how the screw bone anchorage is affected by screw design, bone quality, loading conditions, and cementing techniques.

The revised Tokuhashi, Tomita and modified Bauer scores are commonly used to make difficult decisions in the management of patients presenting with spinal metastases. A prospective cohort study of 199 consecutive patients presenting with spinal metastases, treated with either surgery and/or radiotherapy, was used to compare the three systems. Cox regression, Nagelkerke’s R. 2. and Harrell’s concordance were used to compare the systems and find their best predictive items. The three systems were equally good in terms of overall prognostic performance. Their most predictive items were used to develop the Oswestry Spinal Risk Index (OSRI), which has a similar concordance, but a larger coefficient of determination than any of these three scores. A bootstrap procedure was used to internally validate this score and determine its prediction optimism. The OSRI is a simple summation of two elements: primary tumour pathology (PTP) and general condition (GC): OSRI = PTP + (2 – GC). This simple score can predict life expectancy accurately in patients presenting with spinal metastases. It will be helpful in making difficult clinical decisions without the delay of extensive investigations. Cite this article: Bone Joint J 2013;95-B:210–16

The identification of the extent of neural damage in patients with acute or chronic spinal cord injury is imperative for the accurate prediction of neurological recovery. The changes in signal intensity shown on routine MRI sequences are of limited value for predicting functional outcome. Diffusion tensor imaging (DTI) is a novel radiological imaging technique which has the potential to identify intact nerve fibre tracts, and has been used to image the brain for a variety of conditions. DTI imaging of the spinal cord is currently only a research tool, but preliminary studies have shown that it holds considerable promise in predicting the severity of spinal cord injury. . This paper briefly reviews our current knowledge of this technique

Aims

The aim of this study was to assess the reliability of using MRI scans to calculate the Spinal Instability Neoplastic Score (SINS) in patients with metastatic spinal cord compression (MSCC).