North American Spine Society Journal最新文献

{"title":"Relationship between spinal alignment and functional disability after thoracolumbar spinal fractures: A systematic review","authors":"Romulo Augusto Andrade de Almeida MD ,&nbsp;Francisco Call-Orellana MD ,&nbsp;Andrei Fernandes Joaquim MD, PhD","doi":"10.1016/j.xnsj.2024.100529","DOIUrl":"10.1016/j.xnsj.2024.100529","url":null,"abstract":"<div><h3>Background</h3><p>Thoracolumbar spinal fractures (TLSF) can cause pain, neurological deficits, and functional disability. Operative treatments aim to preserve neurological function, improve functional status, and restore spinal alignment and stability. In this review, we evaluate the relationship between spinal alignment and functional impairment in patients with TLSF.</p></div><div><h3>Methods</h3><p>We performed a systematic review in accordance with the PRISMA guidelines to identify full-text articles that evaluate the correlation between spinal alignment and functional outcomes of TLSF. The artificial intelligence software Rayyan assisted the screening process. Functional outcomes referred to activity/disability, quality of life, and pain scores, as well as return to work metrics. Radiological assessments included were vertebral compression angle, Cobb and Gardner angles, sagittal vertical axis, pelvic incidence, and pelvic tilt. Statistical analyses were performed for the data provided by articles using the SPSS v24.</p></div><div><h3>Results</h3><p>Of 1,616 articles reviewed, 6 were included for final analysis. Only 1 study primarily addressed the effects of spinopelvic parameters and functional outcomes. Four studies correlated Cobb angles with functional outcome, while 3 others compared vertebral compression angles with functional outcomes. Outcomes were assessed using work status or a combination of VAS pain and spine score, ODI, SF-36, and RMDQ-24. Neither the analysis done within the articles, nor the one made with the raw data provided by them, showed a significant correlation between the radiological measurements assessed at time of injury and final functional outcomes.</p></div><div><h3>Conclusions</h3><p>A correlation between the assessed spinal radiological measurements assessed with the functional outcomes of TLSF was not found in this review. Further well-designed prospective studies are necessary to evaluate spinal alignment measurements in TLSF with functional outcomes.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100529"},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002221/pdfft?md5=00bdec5d92ddfb6dcc1afeedb2a8e1a0&pid=1-s2.0-S2666548424002221-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141850535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Twelve-month results from a randomized controlled trial comparing differential target multiplexed spinal cord stimulation and conventional spinal cord stimulation in subjects with chronic refractory axial low back pain not eligible for spine surgery","authors":"Thomas White MD ,&nbsp;Rafael Justiz MD ,&nbsp;Wilson Almonte MD ,&nbsp;Velimir Micovic MD ,&nbsp;Binit Shah MD ,&nbsp;Eric Anderson MD ,&nbsp;Leonardo Kapural MD, PhD ,&nbsp;Harold Cordner MD ,&nbsp;Amr El-Naggar MD ,&nbsp;Michael Fishman MD, MBA ,&nbsp;Yashar Eshraghi MD ,&nbsp;Philip Kim MD ,&nbsp;Alaa Abd-Elsayed MD ,&nbsp;Krishnan Chakravarthy ,&nbsp;Yoann Millet MD ,&nbsp;Mahendra Sanapati MD ,&nbsp;Nathan Harrison MD ,&nbsp;Brandon Goff DO ,&nbsp;Mayank Gupta MD ,&nbsp;Prabhdeep Grewal MD ,&nbsp;Ricardo Vallejo MD, PhD","doi":"10.1016/j.xnsj.2024.100528","DOIUrl":"10.1016/j.xnsj.2024.100528","url":null,"abstract":"<div><h3>Background</h3><p>Successful treatments for intractable chronic low back pain (CLBP) in patients who are not eligible for surgical interventions are scarce. The superior efficacy of differential target multiplexed spinal cord stimulation (DTM SCS) to conventional SCS (Conv-SCS) on the treatment of CLBP in patients with persistent spinal pain syndrome (PSPS) who have failed surgical interventions (PSPS-T2) motivated the evaluation of DTM SCS versus Conv-SCS on PSPS patients who are non-surgical candidates (PSPS-T1).</p></div><div><h3>Methods</h3><p>This is a prospective, open label, crossover, post-market randomized controlled trial in 20 centers across the United States. Eligible patients were randomized to either DTM SCS or Conv-SCS in a 1:1 ratio. Primary endpoint was CLBP responder rate (percentage of subjects with ≥50% CLBP relief) at 3-month in randomized subjects who completed trialing (modified intention-to-treat population). Patients were followed up to 12 months. Secondary endpoints included change of CLBP and leg pain, responder rates, changes in disability, quality of life, patient satisfaction and global impression of change, and safety profile. An optional crossover was available at 6-month to all patients.</p></div><div><h3>Results</h3><p>About 121 PSPS-T1 subjects with CLBP and leg pain mostly associated with degenerative disc disease and radiculopathy and who were not eligible for spine surgery were randomized. CLBP responder rate with DTM SCS (93.5%) was superior to Conv-SCS (36.4%) at the primary endpoint. Superior CLBP responder rates (88.1%–90.5%) were obtained with DTM SCS at all other timepoints. Mean CLBP reduction with DTM SCS (6.52 cm) was superior to that with Conv-SCS (3.01 cm) at the primary endpoint. Similar CLBP reductions (6.23–6.43 cm) were obtained with DTM SCS at other timepoints. DTM SCS provided significantly better leg pain reduction and responder rate, improvement of disability and quality of life, and better patient satisfaction and global impression of change. 90.9% of Conv-SCS subjects who crossed over were CLBP responders at completion of the study. Similar safety profiles were observed between the two groups.</p></div><div><h3>Conclusion</h3><p>DTM SCS for chronic CLBP in nonsurgical candidates is superior to Conv-SCS. Improvements were sustained and provided significant benefits on the management of these patients.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100528"},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266654842400221X/pdfft?md5=b02cb9ba1a77bf63ac377cbbfa76dcf2&pid=1-s2.0-S266654842400221X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141850408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction models for risk assessment of surgical site infection after spinal surgery: A systematic review","authors":"Alexa R. Lauinger BS ,&nbsp;Samuel Blake BS ,&nbsp;Alan Fullenkamp BS ,&nbsp;Gregory Polites MD ,&nbsp;Jonathan N. Grauer MD ,&nbsp;Paul M. Arnold MD","doi":"10.1016/j.xnsj.2024.100518","DOIUrl":"10.1016/j.xnsj.2024.100518","url":null,"abstract":"<div><h3>Background</h3><p>Spinal surgeries are a common procedure, but there is significant risk of adverse events following these operations. While the rate of adverse events ranges from 8% to 18%, surgical site infections (SSIs) alone occur in between 1% and 4% of spinal surgeries.</p></div><div><h3>Methods</h3><p>We completed a systematic review addressing factors that contribute to surgical site infection after spinal surgery. From the included studies, we separated the articles into groups based on whether they propose a clinical predictive tool or model. We then compared the prediction variables, model development, model validation, and model performance.</p></div><div><h3>Results</h3><p>About 47 articles were included in this study: 10 proposed a model and 5 validated a model. The models were developed from 7,720 participants in total and 210 participants with SSI. Only one of the proposed models was externally validated by an independent group. The other 4 validation papers examined the performance of the ACS NSQIP surgical risk calculator.</p></div><div><h3>Conclusions</h3><p>While some preoperative risk models have been validated, and even successfully implemented clinically, the significance of postoperative SSIs and the unique susceptibility of spine surgery patients merits the development of a spine-specific preoperative risk model. Additionally, comprehensive and stratified risk modeling for SSI would be of invaluable clinical utility and greatly improve the field of spine surgery.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100518"},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002117/pdfft?md5=cc17f09a231ddf220b4943c41a9c673e&pid=1-s2.0-S2666548424002117-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141711930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Circumferential correction of spinal deformity and instability secondary to bacterial spondylodiscitis","authors":"Azeem A. Rehman MD,&nbsp;Ziev B. Moses MD,&nbsp;Mazda K. Turel MD,&nbsp;Ravi S. Nunna MD,&nbsp;Mena G. Kerolus MD,&nbsp;Samuel J. Meza MD,&nbsp;Ricardo B.V. Fontes MD, PhD","doi":"10.1016/j.xnsj.2024.100517","DOIUrl":"10.1016/j.xnsj.2024.100517","url":null,"abstract":"<div><h3>Background</h3><p>Spinal deformity as a sequela of nontuberculous spondylodiscitis is a rarely discussed clinical entity. Sagittal plane deformity, segmental instability, and persistently active infection overlap in these patients resulting in severe restriction in activity and quality of life. The presence of multiple medical co-morbidities restricts surgical options but nonoperative care may be ineffective and result in persistent, refractory discitis for years. We describe our experience with vertebrectomy and long-segment fixation for patients with postinfectious thoracic or lumbar deformity.</p></div><div><h3>Methods</h3><p>A retrospective chart review of 23 consecutive patients who underwent vertebrectomy and long-segment fixation for thoracic or lumbar deformity secondary to nontuberculous bacterial spondylodiscitis was performed. Pre, peri- and postoperative data is compiled and analyzed with a focus on the perioperative management algorithm to safely perform an extensive reconstruction in this very sick patient population.</p></div><div><h3>Results</h3><p>Extremely low preoperative quality of life was evident with 87% (20/23) of patients bedridden primarily due to pain despite 70% (16/23) of patients being strong enough to ambulate (Frankel D or E). Most patients (87%) already had an identified infection under adequate treatment either through blood cultures, prior biopsy or decompressive surgery. A single-stage posterior-only was the primary surgical approach utilized in the majority (83%) of cases. Complications were present in 100% of patients, most commonly perioperative anemia and hypotension requiring vasopressor support and aggressive blood product replacement. One in-hospital mortality occurred secondarily to pulmonary embolism. Mean preoperative segmental angle was 18±10 degrees of kyphosis which was corrected to 1±9 degrees of lordosis (p=.001). The mean correction of the segmental angle was 19 degrees (standard deviation 23 degrees). Visual analogue scale scores improved from a preoperative value of 8.8±0.9 to a postoperative value of 2.5±1.4 (p&lt;.001), which was obtained at the last outpatient follow-up (mean 631 days after surgery). Full self-care including ambulation was achieved in 18/23 (78%) patients, and the infection was successfully treated in 22/23 (96%) patients after long-term antibiotics.</p></div><div><h3>Conclusions</h3><p>Patients with refractory spondylodiscitis on appropriate care and antibiotics are typically considered extremely poor surgical candidates despite nonoperative care often being ineffective. Postinfectious deformity may also be so severe as to preclude a limited surgical treatment strategy. This study suggests that extensive circumferential reconstruction for deformity secondary to bacterial spondylodiscitis can be effective in restoring these extremely sick patients to self-care and ambulatory status.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100517"},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002105/pdfft?md5=2dd0196f5ba6de0e54c5f906e02b019a&pid=1-s2.0-S2666548424002105-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sagittal spinal alignment measurements and evaluation: Historical perspective","authors":"Ashley Knebel BA,&nbsp;Mohammad Daher BS,&nbsp;Manjot Singh BS,&nbsp;Lauren Fisher BS,&nbsp;Alan H. Daniels MD,&nbsp;Bassel G. Diebo MD","doi":"10.1016/j.xnsj.2024.100519","DOIUrl":"10.1016/j.xnsj.2024.100519","url":null,"abstract":"<div><p>Spinal alignment analysis play an important role in evaluating patients and planning surgical corrections for adult spinal deformity. The history of these parameters is relatively short with the first parameter, the Cobb angle, introduced in 1948 as part of an effort to improve scoliosis evaluation. New developments in the field were limited for nearly 30 years before better imaging technology encouraged new theories and later data about spinal alignment and the relationship between the spine and pelvis. These efforts would ultimately contribute to the creation of foundational spinal alignment parameters, including pelvic incidence, pelvic tilt, and sacral slope. By the 1990s, spinal alignment had become a sustained area of investigation for spinal surgeons and researchers. Novel alignment parameters have since been introduced as our knowledge has evolved and has allowed for valuable research that demonstrates the clinical and surgical value of alignment measurement. This manuscript will explore the history of spinal alignment analysis over the decades.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100519"},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002129/pdfft?md5=899717a59a2349c53a4d1c1e9b7374a9&pid=1-s2.0-S2666548424002129-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141841463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lumbar pedicle subtraction osteotomy: techniques and outcomes","authors":"Anouar Bourghli MD ,&nbsp;Louis Boissiere MD ,&nbsp;Ibrahim Obeid MD","doi":"10.1016/j.xnsj.2024.100516","DOIUrl":"10.1016/j.xnsj.2024.100516","url":null,"abstract":"<div><p>Pedicle subtraction osteotomy has been thoroughly described and studied over the past 2 decades, being applied mainly in the lumbar spine, followed by the thoracic spine. Our better understanding of alignment biomechanics, and the progressive refinements of the surgical technique over time made it a very efficient procedure for the management of fixed sagittal malalignment. However, a long learning curve is mandatory to mitigate the associated risks particularly neurological deficits and achieve satisfactory clinical and radiological outcomes with an acceptable rate of complications.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100516"},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002099/pdfft?md5=cc627705b747febabd53ce85ed9bf696&pid=1-s2.0-S2666548424002099-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Osteoporotic vertebral compression fracture (OVCF) detection using artificial neural networks model based on the AO spine-DGOU osteoporotic fracture classification system","authors":"Wongthawat Liawrungrueang MD ,&nbsp;Sung Tan Cho MD ,&nbsp;Vit Kotheeranurak MD ,&nbsp;Khanathip Jitpakdee MD ,&nbsp;Pyeoungkee Kim PhD ,&nbsp;Peem Sarasombath MD","doi":"10.1016/j.xnsj.2024.100515","DOIUrl":"10.1016/j.xnsj.2024.100515","url":null,"abstract":"<div><h3>Background</h3><p>Osteoporotic Vertebral Compression Fracture (OVCF) substantially reduces a person's health-related quality of life. Computer Tomography (CT) scan is currently the standard for diagnosis of OVCF. The aim of this paper was to evaluate the OVCF detection potential of artificial neural networks (ANN).</p></div><div><h3>Methods</h3><p>Models of artificial intelligence based on deep learning hold promise for quickly and automatically identifying and visualizing OVCF. This study investigated the detection, classification, and grading of OVCF using deep artificial neural networks (ANN). Techniques: Annotation techniques were used to segregate the sagittal images of 1,050 OVCF CT pictures with symptomatic low back pain into 934 CT images for a training dataset (89%) and 116 CT images for a test dataset (11%). A radiologist tagged, cleaned, and annotated the training dataset. Disc deterioration was assessed in all lumbar discs using the AO Spine-DGOU Osteoporotic Fracture Classification System. The detection and grading of OVCF were trained using the deep learning ANN model. By putting an automatic model to the test for dataset grading, the outcomes of the ANN model training were confirmed.</p></div><div><h3>Results</h3><p>The sagittal lumbar CT training dataset included 5,010 OVCF from OF1, 1942 from OF2, 522 from OF3, 336 from OF4, and none from OF5. With overall 96.04% accuracy, the deep ANN model was able to identify and categorize lumbar OVCF.</p></div><div><h3>Conclusions</h3><p>The ANN model offers a rapid and effective way to classify lumbar OVCF by automatically and consistently evaluating routine CT scans using AO Spine-DGOU osteoporotic fracture classification system.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100515"},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002087/pdfft?md5=f7f1b7d64cc4de795abdd991aca59bd4&pid=1-s2.0-S2666548424002087-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141689227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a natural language processing algorithm for the detection of spinal metastasis based on magnetic resonance imaging reports","authors":"Evan Mostafa MD ,&nbsp;Aaron Hui BS ,&nbsp;Boudewijn Aasman BS ,&nbsp;Kamlesh Chowdary BS ,&nbsp;Kyle Mani BS ,&nbsp;Edward Mardakhaev MD ,&nbsp;Richard Zampolin MD ,&nbsp;Einat Blumfield MD ,&nbsp;Jesse Berman MD ,&nbsp;Rafael De La Garza Ramos MD ,&nbsp;Mitchell Fourman MD ,&nbsp;Reza Yassari MD ,&nbsp;Ananth Eleswarapu MD ,&nbsp;Parsa Mirhaji PhD","doi":"10.1016/j.xnsj.2024.100513","DOIUrl":"10.1016/j.xnsj.2024.100513","url":null,"abstract":"<div><h3>Background</h3><p>Metastasis to the spinal column is a common complication of malignancy, potentially causing pain and neurologic injury. An automated system to identify and refer patients with spinal metastases can help overcome barriers to timely treatment. We describe the training, optimization and validation of a natural language processing algorithm to identify the presence of vertebral metastasis and metastatic epidural cord compression (MECC) from radiology reports of spinal MRIs.</p></div><div><h3>Methods</h3><p>Reports from patients with spine MRI studies performed between January 1, 2008 and April 14, 2019 were reviewed by a team of radiologists to assess for the presence of cancer and generate a labeled dataset for model training. Using regular expression, impression sections were extracted from the reports and converted to all lower-case letters with all nonalphabetic characters removed. The reports were then tokenized and vectorized using the doc2vec algorithm. These were then used to train a neural network to predict the likelihood of spinal tumor or MECC. For each report, the model provided a number from 0 to 1 corresponding to its impression. We then obtained 111 MRI reports from outside the test set, 92 manually labeled negative and 19 with MECC to test the model's performance.</p></div><div><h3>Results</h3><p>About 37,579 radiology reports were reviewed. About 36,676 were labeled negative, and 903 with MECC. We chose a cutoff of 0.02 as a positive result to optimize for a low false negative rate. At this threshold we found a 100% sensitivity rate with a low false positive rate of 2.2%.</p></div><div><h3>Conclusions</h3><p>The NLP model described predicts the presence of spinal tumor and MECC in spine MRI reports with high accuracy. We plan to implement the algorithm into our EMR to allow for faster referral of these patients to appropriate specialists, allowing for reduced morbidity and increased survival.</p></div>","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"19 ","pages":"Article 100513"},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424002063/pdfft?md5=01450dbc60198665e1ef96ae67a4c9a2&pid=1-s2.0-S2666548424002063-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141700355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"37. Early versus late decompression for lumbar spinal nerve injury: a propensity score matched analysis","authors":"Sam Jiang BS ,&nbsp;Zayed A Almadidy MD ,&nbsp;Morteza Sadeh MD, PhD ,&nbsp;Dario Marotta DO ,&nbsp;Ankit Indravadan Mehta MD","doi":"10.1016/j.xnsj.2024.100375","DOIUrl":"10.1016/j.xnsj.2024.100375","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;BACKGROUND CONTEXT&lt;/h3&gt;&lt;p&gt;Traumatic lumbar spinal injury often necessitates surgical decompression of the thecal sac, nerve roots, or peripheral nerves. While there is some evidence in the literature to suggest a benefit to early surgery within 24 hours, there has yet to be a consensus and society recommendations for the timing of decompressive surgery for lumbar spine injuries.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;PURPOSE&lt;/h3&gt;&lt;p&gt;To evaluate the effect of early versus late decompressive surgery on inpatient outcomes at a nationwide level in the United States.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;STUDY DESIGN/SETTING&lt;/h3&gt;&lt;p&gt;Retrospective cohort database study.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;PATIENT SAMPLE&lt;/h3&gt;&lt;p&gt;Patients from the American College of Surgeons National Trauma Data Bank (NTDB) from 2017-2021.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OUTCOME MEASURES&lt;/h3&gt;&lt;p&gt;The primary outcome measures are all-cause mortality and overall hospital length of stay (LOS). Secondary outcome measures entail hospital complications such as pressure ulcers and acute kidney injury (AKI) and discharge disposition such as routine discharge to home and discharge to skilled nursing.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;p&gt;The NTDB was queried from 2017-2021 for all patients with a lumbar spinal cord or nerve injury matching the ICD-10-CM code S34. Patients younger than 18 years, who did not undergo surgical decompression, or who were missing outcome data were excluded. Patients were divided in the early surgery group if they underwent decompression within 24 hours and in the late surgery group if they underwent decompression at or after 24 hours. Propensity score matching was performed using the k-nearest neighbors algorithm based on patient age, sex, race, ethnicity, comorbidities, Glasgow Coma Scale, and insurance type. Equal post-match balance was evaluated using a standard mean difference threshold of 0.1. Early and late patients were compared using Student's t-tests and Pearson's chi-square tests.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;p&gt;A total of 1499 patients matching the inclusion and exclusion criteria were identified, of which 905 had early surgery and 591 had late surgery. Following propensity score matching, 591 matching patients in the late surgery group were identified. Post-match, the early surgery group had a lower mortality rate (0.17% vs 1.69%, p&lt;0.01) and shorter overall length of stay (2.47 vs 3.79 days, p&lt;0.01), as well as lower rates of unplanned intubation (1.02% vs 2.88%, p=0.02), AKI (0.17% vs 1.35%, p=0.02, stroke (0% vs 0.68%, p=0.045), pressure ulcer (0.68% vs 2.2%, p=0.03), unplanned intensive care unit admission (1.02% vs 4.06%, p&lt;0.01), and ventilator-associated pneumonia (0.34% vs 1.69%, p=0.02) compared to the late surgery group. Additionally, the early surgery group was more likely to be discharged to inpatient rehabilitation (53.64% vs 40.61%, p&lt;0.01) but less likely to be discharged routinely to home (26.73% vs 34.52%, p&lt;0.01) or a skilled nursing facility (4.74% vs 7.61%, p=0.04).&lt;/p&gt;&lt;/div&gt;&lt;","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"18 ","pages":"Article 100375"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424000684/pdfft?md5=931e01252afe84c2de6d52457dcf37bc&pid=1-s2.0-S2666548424000684-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141847241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"P28. Deep learning-based detection of lumbar spinal canal stenosis using convolutional neural networks","authors":"Hisataka Suzuki MD ,&nbsp;Katsuhisa Yamada MD, PhD ,&nbsp;Terufumi Kokabu MD ,&nbsp;Yoko Ishikawa MD ,&nbsp;Akito Yabu MD ,&nbsp;Takahiko Hyakumachi MD","doi":"10.1016/j.xnsj.2024.100432","DOIUrl":"10.1016/j.xnsj.2024.100432","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background Context&lt;/h3&gt;&lt;p&gt;Lumbar spinal canal stenosis (LSCS) is the most common spinal degenerative disease in elderly people and usually first seen by primary care physicians or orthopedic surgeons who are not spine surgery specialists. Magnetic resonance imaging (MRI) is useful in the diagnosis of LSCS, but the equipment is often not available or difficult to read. LCSC patients with progressive neurologic deficits have difficulty with recovery if surgical treatment is delayed. So, early diagnosis and determination of appropriate surgical indications are crucial in the treatment of LCSC. Convolutional neural networks (CNNs), a type of deep learning, offers significant advantages for image recognition and classification, and work well with radiographs, which can be easily taken at any facility.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Purpose&lt;/h3&gt;&lt;p&gt;Our purpose was to develop an algorithm to diagnose the presence or absence of LSCS requiring surgery from plain radiographs using CNNs.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Study Design/Setting&lt;/h3&gt;&lt;p&gt;This study is a cross-sectional study.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Patient Sample&lt;/h3&gt;&lt;p&gt;One hundred patients who underwent the surgery for LSCS including degenerative spondylolisthesis from January 2022 to May 2022 at a single institution were enrolled.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Outcome Measures&lt;/h3&gt;&lt;p&gt;In annotation 1, the area under the curve (AUC) computed from the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated. In annotation 2, correlation coefficients were used.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;p&gt;Four intervertebral levels from L1/2 to L4/5 were extracted as region of interest from lateral plain lumbar spine radiographs and totally 400 images were obtained. Based on the date of surgery, the 300 images derived from the first 75 cases were used for internal validation and 100 images from the second 25 cases for external validation. In annotation 1, binary classification of operative and nonoperative levels was used, and in annotation 2, the spinal canal area rate was calculated by dividing each disc level area measured on the MRI axial image by L1/2 level area. For internal validation, 300 images were divided into each 5 datasets on per-patient basis and 5-fold cross-validation was performed. Five trained models were registered in the external validation prediction performance. Grad-CAM was used to visualize area with the high features extracted by CNNs.&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;p&gt;In internal validation, the range of AUC and accuracy were 0.80 to 0.96 and 75% to 93% for the annotation 1 and correlation coefficients of 0.60 to 0.72 (All p&lt;.01) for the annotation 2. In external validation, the AUC and accuracy were 0.93 and 86% in annotation 1, and correlation coefficient was 0.69 in annotation 2 using 5 trained CNN models. Grad-CAM showed high feature density","PeriodicalId":34622,"journal":{"name":"North American Spine Society Journal","volume":"18 ","pages":"Article 100432"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666548424001252/pdfft?md5=a318965fbd961106a972e510c95fa677&pid=1-s2.0-S2666548424001252-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141847361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}