Search

Study Design: A retrospective cohort study of patients with surgically treated thoracolumbar fractures.Purpose: This study aimed to describe the incidence of adverse events (AEs) after surgical stabilization of thoracolumbar spine injuries and to identify predictive factors for the occurrence of AEs. Overview of Literature: Thoracolumbar spine fractures are frequently present in patients with blunt trauma and are associated with significant morbidity. AEs can occur due to the initial spinal injury or secondary to surgical treatment. There is a lack of emphasis in the literature on the AEs that can occur after operative management of thoracolumbar fractures.Methods: We performed a retrospective review of 199 patients with surgically treated thoracolumbar fractures operated between January 2007 and January 2018. The potential risk factors for the development of AEs as well as the development of common complications were evaluated by univariate analysis, and a multivariate logistic regression analysis was performed to identify independent risk factors predictive of the above.Results: The overall rate of AEs was 46.7%; 83 patients (41.7%) had nonsurgical AEs, whereas 24 (12.1%) had surgical adverse events. The most common AEs were urinary tract infections in 43 patients (21.6%), and hospital-acquired pneumonia in 21 patients (10.6%). On multivariate logistic regression, a Thoracolumbar Injury Classification and Severity (TLICS) score of 8–10 (odds ratio [OR], 6.39; 95% confidence interval [CI], 2.33–17.51), the presence of polytrauma (OR, 2.64; 95% CI, 1.17–5.99), and undergoing open surgery (OR, 2.31; 95% CI, 1.09–4.88) were significant risk factors for AEs. The absence of neurological deficit was associated with a lower rate of AEs (OR, 0.47; 95% CI, 0.31–0.70).Conclusions: This study suggests the presence of polytrauma, preoperative American Spinal Injury Association score, and TLICS score are predictive of AEs in patients with surgically treated thoracolumbar fractures. The results might also suggest a role for minimally invasive surgical methods in reducing AEs in these patients.

Background Lumbar spine MRI studies are widely used for back pain assessment. Interpretation involves grading lumbar spinal stenosis, which is repetitive and time consuming. Deep learning (DL) could provide faster and more consistent interpretation. Purpose To assess the speed and interobserver agreement of radiologists for reporting lumbar spinal stenosis with and without DL assistance. Materials and Methods In this retrospective study, a DL model designed to assist radiologists in the interpretation of spinal canal, lateral recess, and neural foraminal stenoses on lumbar spine MRI scans was used. Randomly selected lumbar spine MRI studies obtained in patients with back pain who were 18 years and older over a 3-year period, from September 2015 to September 2018, were included in an internal test data set. Studies with instrumentation and scoliosis were excluded. Eight radiologists, each with 2-13 years of experience in spine MRI interpretation, reviewed studies with and without DL model assistance with a 1-month washout period. Time to diagnosis (in seconds) and interobserver agreement (using Gwet κ) were assessed for stenosis grading for each radiologist with and without the DL model and compared with test data set labels provided by an external musculoskeletal radiologist (with 32 years of experience) as the reference standard. Results Overall, 444 images in 25 patients (mean age, 51 years ± 20 [SD]; 14 women) were evaluated in a test data set. DL-assisted radiologists had a reduced interpretation time per spine MRI study, from a mean of 124-274 seconds (SD, 25-88 seconds) to 47-71 seconds (SD, 24-29 seconds) (

IntroductionMetastatic spinal cord compression (MSCC) is a disastrous complication of advanced malignancy. A deep learning (DL) algorithm for MSCC classification on CT could expedite timely diagnosis. In this study, we externally test a DL algorithm for MSCC classification on CT and compare with radiologist assessment.MethodsRetrospective collection of CT and corresponding MRI from patients with suspected MSCC was conducted from September 2007 to September 2020. Exclusion criteria were scans with instrumentation, no intravenous contrast, motion artefacts and non-thoracic coverage. Internal CT dataset split was 84% for training/validation and 16% for testing. An external test set was also utilised. Internal training/validation sets were labelled by radiologists with spine imaging specialization (6 and 11-years post-board certification) and were used to further develop a DL algorithm for MSCC classification. The spine imaging specialist (11-years expertise) labelled the test sets (reference standard). For evaluation of DL algorithm performance, internal and external test data were independently reviewed by four radiologists: two spine specialists (Rad1 and Rad2, 7 and 5-years post-board certification, respectively) and two oncological imaging specialists (Rad3 and Rad4, 3 and 5-years post-board certification, respectively). DL model performance was also compared against the CT report issued by the radiologist in a real clinical setting. Inter-rater agreement (Gwet’s kappa) and sensitivity/specificity/AUCs were calculated.ResultsOverall, 420 CT scans were evaluated (225 patients, mean age=60 ± 11.9[SD]); 354(84%) CTs for training/validation and 66(16%) CTs for internal testing. The DL algorithm showed high inter-rater agreement for three-class MSCC grading with kappas of 0.872 (pConclusionDeep learning algorithm for metastatic spinal cord compression on CT showed superior performance to the CT report issued by experienced radiologists and could aid earlier diagnosis.

Study Design: Retrospective cohort study.Purpose: To evaluate the incidence and presentation of symptomatic failures (SFs) after metastatic spine tumor surgery (MSTS). To identify the associated risk factors. To categorize SFs based on the management in these patients.Overview of Literature: Few studies have reported on the incidence (1.9%–16%) and risk factors of SF after MSTS. It is unclear whether all SFs, occurring in MSTS-patients, result in revision surgery.Methods: We conducted a retrospective analysis on 288 patients (246 for final analysis) who underwent MSTS between 2005–2015. Data collected were demographics and peri/postoperative clinical and radiological features. Early and late radiological SF were defined as presentation before and after 3 months from index surgery, respectively. Univariate and multivariate models of competing risk regression analysis were designed to determine the risk factors for SF with death as a competing event.Results: We observed 14 SFs (5.7%) in 246 patients; 10 (4.1%) underwent revision surgery. Median survival was 13.4 months. The mean age was 58.8 years (range, 21–87 years); 48.4% were women. The median time to failure was 5 months (range, 1–60 months). Patients with SF were categorized into three groups: (1) SF when the primary implant was revised (n=5, 35.7%); (2) peri-construct progression of disease requiring extension (n=5, 35.7%); and (3) SFs that did not warrant revision (n=4, 28.5%). Four patients (28.5%) presented with early failure. SF commonly occurred at the implant-bone interface (9/14) and all patients had a spinal instability neoplastic score (SINS) >7. Thirteen patients (92.8%) who developed failure had fixation spanning junctional regions. Multivariate competing risk regression showed that preoperative Eastern Cooperative Oncology Group score was a significant risk factor for implant failure (adjusted sub-hazard ratio, 7.0; 95% confidence interval, 1.63–30.07; p7 and fixations spanning junctional regions were associated with SF. Majority of construct failures occurred at the implant-bone interface.

Objectives We hypothesize that in adequately resuscitated borderline polytrauma patients with long bone fractures (femur and tibia) or pelvic fractures; early (within 4 days) definitive stabilization (EDS) can be performed without an increase in post-operative ventilation and post-operative complications. Design Retrospective Cohort Study SETTING:: Level 1 Trauma Centre PATIENTS:: In total 103 patients were included in this study of which 18 (17.5%) were female and 85(82.5%) were male. These patients were borderline trauma patients who had the following parameters prior to definitive surgery, normal coagulation profile, lactate Intervention These patients were treated either according to Early Total Care (ETC), definitive surgery on day of admission, or Damage Control Orthopaedics (DCO) principles, temporizing external fixation followed by definitive surgery at a later date. Timing of definitive surgical fixation was recorded as EDS or late definitive surgical fixation (LDS) (>4 days). Main outcome measurements Primary outcome measured was duration of ventilation more than 3 days post definitive surgery and presence of post-operative complications. Results 35 (34.0%) patients received ETC, while 68 (66.0%) patients were treated with DCO. In total 51 (49.5%) of all patients had LDS while 52 (50.5%) patients had EDS. On Logistic Regression the following factors were found to be predictive of higher rates of post -operative ventilation ≥ 3 days, Units of Blood Transfused and time to definitive surgery>4 days. Increased age, Head AIS 3 or more and Time to definitive surgery were found to be associated with an increased risk of post-operative complications. Conclusions Borderline polytrauma patients with no severe soft tissue injuries such as chest or head injuries may be treated with EDS if adequately resuscitated with no increase in need for post-operative ventilation and complications. Level of evidence Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Background: Early diagnosis of metastatic epidural spinal cord compression (MESCC) is vital to expedite therapy and prevent paralysis. Staging CT is performed routinely in cancer patients and presents an opportunity for earlier diagnosis. Methods: This retrospective study included 123 CT scans from 101 patients who underwent spine MRI within 30 days, excluding 549 CT scans from 216 patients due to CT performed post-MRI, non-contrast CT, or a gap greater than 30 days between modalities. Reference standard MESCC gradings on CT were provided in consensus via two spine radiologists (11 and 7 years of experience) analyzing the MRI scans. CT scans were labeled using the original reports and by three radiologists (3, 13, and 14 years of experience) using dedicated CT windowing. Results: For normal/none versus low/high-grade MESCC per CT scan, all radiologists demonstrated almost perfect agreement with kappa values ranging from 0.866 (95% CI 0.787–0.945) to 0.947 (95% CI 0.899–0.995), compared to slight agreement for the reports (kappa = 0.095, 95%CI −0.098–0.287). Radiologists also showed high sensitivities ranging from 91.51 (95% CI 84.49–96.04) to 98.11 (95% CI 93.35–99.77), compared to 44.34 (95% CI 34.69–54.31) for the reports. Conclusion: Dedicated radiologist review for MESCC on CT showed high interobserver agreement and sensitivity compared to the current standard of care.

Spinal metastasis is the most common malignant disease of the spine. Recently, major advances in machine learning and artificial intelligence technology have led to their increased use in oncological imaging. The purpose of this study is to review and summarise the present evidence for artificial intelligence applications in the detection, classification and management of spinal metastasis, along with their potential integration into clinical practice. A systematic, detailed search of the main electronic medical databases was undertaken in concordance with the PRISMA guidelines. A total of 30 articles were retrieved from the database and reviewed. Key findings of current AI applications were compiled and summarised. The main clinical applications of AI techniques include image processing, diagnosis, decision support, treatment assistance and prognostic outcomes. In the realm of spinal oncology, artificial intelligence technologies have achieved relatively good performance and hold immense potential to aid clinicians, including enhancing work efficiency and reducing adverse events. Further research is required to validate the clinical performance of the AI tools and facilitate their integration into routine clinical practice.

Metastatic Spinal Cord Compression (MSCC) is a debilitating complication in oncology patients. This narrative review discusses the strengths and limitations of various imaging modalities in diagnosing MSCC, the role of imaging in stereotactic body radiotherapy (SBRT) for MSCC treatment, and recent advances in deep learning (DL) tools for MSCC diagnosis. PubMed and Google Scholar databases were searched using targeted keywords. Studies were reviewed in consensus among the co-authors for their suitability before inclusion. MRI is the gold standard of imaging to diagnose MSCC with reported sensitivity and specificity of 93% and 97% respectively. CT Myelogram appears to have comparable sensitivity and specificity to contrast-enhanced MRI. Conventional CT has a lower diagnostic accuracy than MRI in MSCC diagnosis, but is helpful in emergent situations with limited access to MRI. Metal artifact reduction techniques for MRI and CT are continually being researched for patients with spinal implants. Imaging is crucial for SBRT treatment planning and three-dimensional positional verification of the treatment isocentre prior to SBRT delivery. Structural and functional MRI may be helpful in post-treatment surveillance. DL tools may improve detection of vertebral metastasis and reduce time to MSCC diagnosis. This enables earlier institution of definitive therapy for better outcomes.

Surgery with radiation therapy (RT) is more effective in treating spinal metastases, than RT alone. However, RT when administered in close proximity to surgery may predispose to wound complications. There exist limited guidelines on the optimal timing between RT and surgery. The purpose of this systematic review is to: (1) address whether pre-operative RT (preop-RT) and/or post-operative RT (postop-RT) is associated with wound complications and (2) define the safe interval between RT and surgery or vice versa. PubMed, Embase and Scopus databases were systematically searched for articles dealing with spinal metastases, treated with surgery and RT, and discussing wound status. We obtained 2332 articles from all databases, and after applying exclusion criteria, removing duplicates and reading the full text, we identified 27 relevant articles. Fourteen additional articles were identified by hand-search, leading to a total of 41 articles. All 41 mentioned wound complications/healing. Sixteen articles discussed preop-RT, 8 postop-RT, 15 both, and 2 mentioned intraoperative-RT with additional pre/postop-RT. Twenty studies mentioned surgery-RT time interval; one concluded that wound complications were higher when RT-surgery interval was ≤ 7 days. Seven studies reported significant association between preop-RT and wound complications. Evidence is insufficient to draw definitive conclusion about optimal RT-surgery interval. However, based on published literature and expert opinions, we conclude that an interval of 2 weeks, the minimum being 7 days, is optimum between RT-surgery or vice versa; this can be reduced further by postop-stereotactic body RT. If RT-surgery window is > 12 months, wound-complications rise. Postop-RT has fewer wound complications versus preop-RT.

An accurate diagnosis of bone tumours on imaging is crucial for appropriate and successful treatment. The advent of Artificial intelligence (AI) and machine learning methods to characterize and assess bone tumours on various imaging modalities may assist in the diagnostic workflow. The purpose of this review article is to summarise the most recent evidence for AI techniques using imaging for differentiating benign from malignant lesions, the characterization of various malignant bone lesions, and their potential clinical application. A systematic search through electronic databases (PubMed, MEDLINE, Web of Science, and clinicaltrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 34 articles were retrieved from the databases and the key findings were compiled and summarised. A total of 34 articles reported the use of AI techniques to distinguish between benign vs. malignant bone lesions, of which 12 (35.3%) focused on radiographs, 12 (35.3%) on MRI, 5 (14.7%) on CT and 5 (14.7%) on PET/CT. The overall reported accuracy, sensitivity, and specificity of AI in distinguishing between benign vs. malignant bone lesions ranges from 0.44–0.99, 0.63–1.00, and 0.73–0.96, respectively, with AUCs of 0.73–0.96. In conclusion, the use of AI to discriminate bone lesions on imaging has achieved a relatively good performance in various imaging modalities, with high sensitivity, specificity, and accuracy for distinguishing between benign vs. malignant lesions in several cohort studies. However, further research is necessary to test the clinical performance of these algorithms before they can be facilitated and integrated into routine clinical practice.

Background Assessment of lumbar spinal stenosis at MRI is repetitive and time consuming. Deep learning (DL) could improve -productivity and the consistency of reporting. Purpose To develop a DL model for automated detection and classification of lumbar central canal, lateral recess, and neural -foraminal stenosis. Materials and Methods In this retrospective study, lumbar spine MRI scans obtained from September 2015 to September 2018 were included. Studies of patients with spinal instrumentation or studies with suboptimal image quality, as well as postgadolinium studies and studies of patients with scoliosis, were excluded. Axial T2-weighted and sagittal T1-weighted images were used. Studies were split into an internal training set (80%), validation set (9%), and test set (11%). Training data were labeled by four radiologists using predefined gradings (normal, mild, moderate, and severe). A two-component DL model was developed. First, a convolutional neural network (CNN) was trained to detect the region of interest (ROI), with a second CNN for classification. An internal test set was labeled by a musculoskeletal radiologist with 31 years of experience (reference standard) and two subspecialist radiologists (radiologist 1: A.M., 5 years of experience; radiologist 2: J.T.P.D.H., 9 years of experience). DL model performance on an external test set was evaluated. Detection recall (in percentage), interrater agreement (Gwet κ), sensitivity, and specificity were calculated. Results Overall, 446 MRI lumbar spine studies were analyzed (446 patients; mean age ± standard deviation, 52 years ± 19; 240 women), with 396 patients in the training (80%) and validation (9%) sets and 50 (11%) in the internal test set. For internal testing, DL model and radiologist central canal recall were greater than 99%, with reduced neural foramina recall for the DL model (84.5%) and radiologist 1 (83.9%) compared with radiologist 2 (97.1%) (

Study Design: Retrospective cohort study.Purpose: To study the incidence, onset, underlying mechanism, clinical course, and factors leading to asymptomatic construct failure (AsCF) after metastatic spinal tumor surgery (MSTS).Overview of Literature: The reported incidence rates for implant and/or construct failure after MSTS are low (1.9%–16%) and based on clinical presentations and revisions required for symptomatic failures (SFs). AsCF after MSTS has not been reported.Methods: We conducted a retrospective analysis of 288 patients (246 for final analysis) who underwent MSTS between 2005–2015. Data collected were demographics and peri/postoperative clinical and radiological features. Early and late radiological AsCF were defined as presentation before and after 3 months, respectively. We analyzed patients with AsCF for risk factors and survival duration by performing competing risk regression analyses where AsCF was the event of interest, with SF and death as competing events.Results: We observed AsCF in 41/246 patients (16.7%). The mean time to onset of AsCF after MSTS was 2 months (range, 1–9 months). Median survival of patients with AsCF was 20 and 41 months for early and late failures, respectively. Early AsCF accounted for 80.5% of cases, while late AsCF accounted for 19.5%. The commonest radiologically detectable AsCF mechanism was angular deformity (increase in kyphus) in 29 patients. Increasing age (p

Radiographic comparative study with prospectively collected data. To assess the accuracy of subaxial cervical pedicle screw (CPS) placement with freehand technique compared to lateral mass screws (LMS). The freehand cervical pedicle screw insertion technique guided by intraoperative lateral C-arm imaging has been shown to be both safe and effective. However, no study has performed a 100% audit of this technique using pre- and postoperative computed tomography (CT) to determine its true accuracy, as well as its reduction capability of CPS and LMS instrumentation. 36 consecutive patients treated surgically by a single surgeon with the exclusive practice of LMS and subsequently CPS over 2 years were included. CT and EOS slot scanner were performed pre- and post-operatively to determine the extent of pedicle screw breach and to assess sagittal alignment reduction between CPS and LMS groups. Predictors of pedicle screw breaches were also identified using multivariate analysis. CPS fixation was more effective in restoring global cervical angle and had superior reduction capability of cervical lordosis at the levels of C3/4 (5.00 ± 3.92, p = 0.008), C4/5 (6.63 ± 5.5, p = 0.010) and C5/6 (7.22 ± 6.19, p = 0.004) compared to LMS fixation. Pedicle screw breaches occurred most commonly at C4 (p = 0.003), and most commonly involved the lateral pedicle wall (p

We aim to review the incidence and risk factors for the development of intraoperative periprosthetic femur fractures while performing a bipolar hemiarthroplasty for displaced neck of femur fractures. Our secondary aim is to characterize the types of intraoperative periprosthetic fractures, the steps leading to the fractures, and the salvage treatments instituted. 271 patients treated with bipolar hemiarthroplasty after traumatic displaced femoral neck fractures were retrospectively analyzed. Demographic data, co-morbidities, vitamin D level, consumption of steroids, ASA score, surgical approach, surgeon experience, use of cemented or uncemented implants, proximal femur morphology, and types of anaesthesia were analyzed statistically. There were 28 patients (10.3%) with intraoperative periprosthetic femur fractures. We found two significant independent risk factors which were the use of uncemented prosthesis (OR 4.15; 95% CI 1.65–10.46; p = 0.003) and Dorr type C proximal femurs (Dorr A OR 3.6; 95% CI 1.47–8.82; p = 0.005). In addition, patients with Dorr type C proximal femurs who underwent uncemented bipolar hemiarthroplasty were more likely to sustain an intraoperative periprosthetic fracture (14(73.7%) out of 19 patients; p = 0.002). There were no significant differences found in other risk factors. The most common location for these fractures was at the greater trochanter at 11 (39.3%) cases. Majority of them, 15 (53.6%), had intraoperative fractures during trial implant insertion and reduction. The overall incidence of intraoperative periprosthetic femur fractures during hemiarthroplasty for displaced neck of femur fractures was 10.3%. The incidence was significantly higher for uncemented (14.7%) when compared to cemented prosthesis (5.4%) and the greater trochanter was the commonest area for periprosthetic fractures during trial implant insertion and reduction. Uncemented prosthesis and Dorr type C proximal femurs were two significant independent risk factors contributing to intraoperative periprosthetic fractures. By identifying these risk factors, surgeons can take ample precautions to prevent complications.

STUDY DESIGN Retrospective analysis. SUMMARY OF BACKGROUND DATA Recent advancements in systemic treatment of lung cancer have significantly improved the survival of patients with certain histolopathologic and molecular subtypes. Existing prognostic scores do not account for this and patients with lung cancer spinal metastases are grouped together as poor prognostic candidates, and consequently, some may be inappropriately denied palliative spine surgery. OBJECTIVE The objective of the study was to study whether the expected survival in patients with lung cancer spinal metastases is affected by histolopathologic and molecular subtypes in the context of modern systemic therapy. MATERIALS AND METHODS We retrospectively reviewed all patients with histologically confirmed lung cancer treated for spinal metastases at our institution between 2001 and 2012. Patients' demographics, histopathologic details, treatment modalities, and survival data were collected. The primary outcome was survival from time of spinal metastases diagnosis. The Cox regression analysis was used to evaluate the influence of tumor histology, molecular profile and treatment modality on survival. The Kaplan-Meier survival analysis was conducted to compare lung cancer subtypes, as well as various treatment regimens. RESULTS Out of 180 patients, 51 underwent surgery for spinal metastases. Female sex (P=0.019), absence of palsy (P=0.023), good Karnofsky performance scores (P

Distal junctional failure (DJF) with fracture at the last instrumented vertebra is a rare occurrence. In this case report, we present two patients with L5 vertebral fracture post-instrumented fusion of the lumbar spine. The first patient is a 78-year-old female who had multi-level degenerative disc disease, spinal stenosis and degenerative scoliosis involving levels T12 to L5. She underwent instrumented posterolateral fusion (PLF) from T12 to L5, and transforaminal lumbar interbody fusion (TLIF) at L2/3 and L4/5. Six months after her operation, she presented with a fracture of the L5 vertebral body necessitating revision of the L5 pedicle screws, with additional TLIF of L5/S1. The second patient is a 71-year-old female who underwent decompression and TLIF of L3/4 and L4/5 for degenerative spondylolisthesis. Six months after the surgery, she developed a fracture of the L5 vertebral body with loosening of the L5 screws. The patient declined revision surgery despite being symptomatic. DJF remains poorly understood as its rare incidence precludes sufficiently powered studies within a single institution. This report aims to contribute to the currently scarce literature on DJF.

BACKGROUND Metastatic Spine Tumour Surgery (MSTS) is often complex and extensive leading to significant blood loss. Allogeneic blood transfusion (ABT) is mainstay of blood replenishment but with immune-mediated post-operative complications. Alternative blood management techniques (salvaged blood transfusion (SBT)) allow us to overcome such complications. Despite widespread use of intra-operative cell salvage (IOCS) in oncological and non-oncological surgeries, surgeons remain reluctant to employ IOCS in MSTS. OBJECTIVE This study will analyse the safety of IOCS-LDF processed blood transfusion to patients undergoing MSTS by assessing clinical outcomes – disease progression: tumour progression and overall survival (OS). We will also evaluate whether reinfusion of IOCS-LDF processed blood can reduce the ABT rates in patients undergoing MSTS by comparing the proportion of MSTS patients requiring ABT in those patients who consent to receive SBT, and those who do not consent for SBT. METHODS We aim to recruit 90-patients (minimum)-30 SBT, 30 ABT and 30 with no blood transfusion (NBT). SBT and ABT form the two experimental arms, while NBT forms the control cohort. All available patient data will be reviewed to determine tumour burden secondary to metastasis and post-operative survival and/or disease progression, improvement in pain, neurology and ambulatory status. Collected data will be studied at 3, 6, 12 and 24 months post-operatively, or until demise, whichever occurs first. Collected outcomes of the experimental groups will be compared with that of the control group. Statistical Analysis: Outcomes will be analysed using one-way ANOVA and Fisher’s exact test. OS will be studied by Kaplan-Meier curve and log rank test. Multivariate and competing risk analysis will be used to study the association between blood transfusion type and tumour progression. All statistical analyses will be done using STATA/SE14.0 RESULTS This is the first clinical study on the use of IOCS in MSTS from various primary malignancies. It will provide major clinical evidence regarding safety and applicability of IOCS in MSTS. It will help reduce ABT usage; thus improving overall blood management of MSTS patients. However, limitation of this study is that not all patients undergoing MSTS will survive for the total follow-up period (two years), thereby theoretically leading to under-reporting of disease progression. CONCLUSIONS Results will be disseminated via peer-reviewed publications and will pave the way for future studies CLINICALTRIAL This study did not involve a healthcare intervention and hence, did not need to be registered

Study design A retrospective study of 180 patients with lung cancer spinal metastases, wherein prognostic score-predicted survival was compared with actual survival. Objective To evaluate and compare the accuracy of prognostic scoring systems in lung cancer spinal metastases. Summary of background data The modified Tokuhashi, Tomita, modified Bauer, and Oswestry scores are currently used to guide decisions regarding operative treatment of patients with spinal metastases. The best system for predicting survival in patients with lung cancer spinal metastases remains undetermined. The high incidence of spinal metastases from lung cancer and improved survival of patients treated with systemic therapy warrants evaluation of these scoring systems in this particular context. Methods Patients with lung cancer spinal metastases treated at our institution between May 2001 and August 2012 were studied. Fifty-one patients were treated surgically. The primary outcome measure was survival from the time of diagnosis. Scoring-predicted survival was compared with actual survival. Potential prognostic factors were investigated using Cox regression analyses. Predictive values of each scoring system for 3- and 6-month survival were measured via receiver operating characteristic (ROC) curves. Results Histological subtype (P = 0.015), sex (P = 0.001), Karnofsky performance scale (P = 0.001), extent of neurological palsy (P = 0.002), and visceral metastases (P = 0.037) are significant predictors of survival. Besides the Oswestry spinal risk index, no significant differences were found between different prognostic subgroups within the individual scoring systems. Although the modified Bauer score was most accurate, all four scoring systems had areas under the ROC curve 0.5 or less. Conclusion Although better prognostic scores correlated with longer survival, all four scoring systems are inaccurate in prognosticating patients with lung cancer spinal metastases. Specific lung cancer histology appears prognostic and should be considered, especially given the increased survival of patients receiving new targeted therapies appropriate to their disease. Level of evidence 3.

Chlorhexidine is a commonly used antiseptic and disinfectant in the health-care setting. Its usage has increased in recent years with intensive campaigns and infection control guidelines to combat hospital-acquired infections. As a result, patients and health-care workers (HCW) are exposed to increasing chlorhexidine usage. In recent years, adverse reactions to chlorhexidine ranging from allergic contact dermatitis, photosensitivity, fixed drug eruptions, urticaria and anaphylactic shock have been reported. Most have been isolated case reports on adverse reactions occurring in healthy individuals or HCW. We report a case of anaphylactic shock caused by applying chlorhexidine cleansing solution and masquerading as septic shock from left-leg necrotising fasciitis.

A retrospective study of all patients with histologically confirmed breast cancer spinal metastases presenting to a single institution between May 2001 and April 2012.The aim of this study was to investigate whether the 2014mT is more accurate than the 2005mT.The commonly used 2005 modified Tokuhashi score (2005mT) has become more inaccurate as oncologists move toward treating tumors according to their molecular and genomic profile, rather than their tissue-of-origin. In attempts to improve the accuracy of the 2005mT, a revised score (2014mT) was published, suggesting that hormone receptor negative and triple-negative breast cancer patients be given a modified Tokuhashi histological score of 3 rather than 5.Demographic characteristics, tumor receptor status, clinical findings in relation to the primary tumor and its metastases, and actual survival time were collated. The 2005mT was compared with the 2014mT. Univariate and multivariate Cox regression analyses were used to evaluate the influence of each parameter on survival, and receiver operating characteristic curves were used to determine predictive values of each score version.Of the 185 patients included, 32 underwent operative treatment, while 153 were managed nonoperatively for their spinal metastases. The overall cohort had a median survival time of 24 months following the diagnosis of spinal metastases, with a 6-month survival rate of 90%. Hormone, HER2 and triple-negative receptor statuses were significant predictors of poorer survival upon multivariate analysis (P = 0.004, P = 0.007, P 0.001, and P 0.001, respectively). Age, the original Tokuhashi score components, previous breast surgery for cancer, previous radiotherapy to the breast, previous radiotherapy to the spine, previous chemotherapy, and previous immunotherapy were not significant. At 6 months, the 2005mT AUROC was 0.62, while that of the 2014mT was 0.64 (P = 0.5394).Tumor histological subtype is crucial when prognosticating the survival of patients with breast cancer spinal metastases. Although the 2014mT was marginally more accurate than the 2005mT, its predictive ability remains poor.3.