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Frederik R. Teunissen, Bianca M. Verbeek, Thomas D. Cha, and Joseph H. Schwab

OBJECTIVE

Spinal cord injury (SCI) is a major complication of spinal fractures in patients with ankylosing spondylitis (AS) and diffuse idiopathic skeletal hyperostosis (DISH). Due to the uncommon nature of these conditions, existing literature consists of relatively small case series without detailed neurological data. This study aims to investigate the incidence, predictors, and sequelae of SCI in patients with a traumatic fracture of the ankylosed spine.

METHODS

The study included all patients older than 18 years of age with AS or DISH who presented to two affiliated tertiary care centers between January 1, 1990, and January 1, 2016, and had a traumatic fracture of the spine. Factors associated with SCI after traumatic fracture were compared using Fisher’s exact tests. Logistic regression was used for the analysis of predictive factors for SCI. For the comparison of probability of survival between patients with and without SCI, Kaplan-Meier methodology was used.

RESULTS

One hundred seventy-two patients with a traumatic fracture of an ankylosed spine were included. Fifty-seven patients (34.1%) had an SCI associated with the fracture. The cervical spine was the most fractured region for patients both with (77.2%) and without (51.4%) SCI. A cervical fracture (odds ratio [OR] 2.70, p = 0.024) and a spinal epidural hematoma (SEH) after fracture (OR 2.69, p = 0.013) were predictive of SCI. Eleven patients (19.3%) with SCI had delayed SCI (range 8–230 days). Of 44 patients with SCI and sufficient follow-up, 20 (45.5%) had neurological improvement after treatment. Early and late complication rates were significantly higher (p = 0.001 and p = 0.004) and hospital stay was significantly longer (p = 0.001) in patients with SCI. The probability of survival was significantly lower in the SCI group compared with the non-SCI group (p = 0.006).

CONCLUSIONS

The incidence of SCI was high after fracture of the spine in patients with AS and DISH. Predictive factors for SCI after fracture were a fracture in the cervical spine and an SEH following fracture. One-fifth of the patients with SCI had delayed SCI. Patients with SCI had more complications, a longer hospital stay, and a lower probability of survival. Less than half of the patients with SCI showed neurological improvement.

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Predicting tumor-specific survival in patients with spinal metastatic renal cell carcinoma: which scoring system is most accurate?

Presented at the 2020 AANS/CNS Joint Section on Disorders of the Spine and Peripheral Nerves

Elie Massaad, Muhamed Hadzipasic, Christopher Alvarez-Breckenridge, Ali Kiapour, Nida Fatima, Joseph H. Schwab, Philip Saylor, Kevin Oh, Andrew J. Schoenfeld, Ganesh M. Shankar, and John H. Shin

OBJECTIVE

Although several prognostic scores for spinal metastatic disease have been developed in the past 2 decades, the applicability and validity of these models to specific cancer types are not yet clear. Most of the data used for model formation are from small population sets and have not been updated or externally validated to assess their performance. Developing predictive models is clinically relevant as prognostic assessment is crucial to optimal decision-making, particularly the decision for or against spine surgery. In this study, the authors investigated the performance of various spinal metastatic disease risk models in predicting prognosis for spine surgery to treat metastatic renal cell carcinoma (RCC).

METHODS

Data of patients who underwent surgery for RCC metastatic to the spine at 2 tertiary centers between 2010 and 2019 were retrospectively retrieved. The authors determined the prognostic value associated with the following scoring systems: the Tomita score, original and revised Tokuhashi scores, original and modified Bauer scores, Katagiri score, the Skeletal Oncology Research Group (SORG) classic algorithm and nomogram, and the New England Spinal Metastasis Score (NESMS). Regression analysis of patient variables in association with 1-year survival after surgery was assessed using Cox proportional hazard models. Calibration and time-dependent discrimination analysis were tested to quantify the accuracy of each scoring system at 3 months, 6 months, and 1 year.

RESULTS

A total of 86 metastatic RCC patients were included (median age 64 years [range 29–84 years]; 63 males [73.26%]). The 1-year survival rate was 72%. The 1-year survival group had a good performance status (Karnofsky Performance Scale [KPS] score 80%–100%) and an albumin level > 3.5 g/dL (p < 0.05). Multivariable-adjusted Cox regression analysis showed that poor performance status (KPS score < 70%), neurological deficit (Frankel grade A–D), and hypoalbuminemia (< 3.5 g/dL) were associated with a higher risk of death before 1 year (p < 0.05). The SORG nomogram, SORG classic, original Tokuhashi, and original Bauer demonstrated fair performance (0.7 < area under the curve < 0.8). The NESMS differentiates survival among the prognostic categories with the highest accuracy (area under the curve > 0.8).

CONCLUSIONS

The present study shows that the most cited and commonly used scoring systems have a fair performance predicting survival for patients undergoing spine surgery for metastatic RCC. The NESMS had the best performance at predicting 1-year survival after surgery.

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Michiel E. R. Bongers, Paul T. Ogink, Katrina F. Chu, Anuj Patel, Brett Rosenthal, John H. Shin, Sang-Gil Lee, Francis J. Hornicek, and Joseph H. Schwab

OBJECTIVE

Reconstruction of the mobile spine following total en bloc spondylectomy (TES) of one or multiple vertebral bodies in patients with malignant spinal tumors is a challenging procedure with high failure rates. A common reason for reconstructive failure is nonunion, which becomes more problematic when using local radiation therapy. Radiotherapy is an integral part of the management of primary malignant osseous tumors in the spine. Vascularized grafts may help prevent nonunion in the radiotherapy setting. The authors have utilized free vascularized fibular grafts (FVFGs) for reconstruction of the spine following TES. The purpose of this article is to describe the surgical technique for vascularized reconstruction of defects after TES. Additionally, the outcomes of consecutive cases treated with this technique are reported.

METHODS

Thirty-nine patients were treated at the authors’ tertiary care institution for malignant tumors in the mobile spine using FVFG following TES between 2010 and 2018. Postoperative union, reoperations, complications, neurological outcome, and survival were reported. The median follow-up duration was 50 months (range 14–109 months).

RESULTS

The cohort consisted of 26 males (67%), and the median age was 58 years. Chordoma was the most prevalent tumor (67%), and the lumbar spine was most affected (46%). Complete union was seen in 26 patients (76%), the overall complication rate was 54%, and implant failure was the most common complication, with 13 patients (33%) affected. In 18 patients (46%), one or more reoperations were needed, and the fixation was surgically revised 15 times (42% of reoperations) in 10 patients (26%). A reconstruction below the L1 vertebra had a higher proportion of implant failure (67%; 8 of 12 patients) compared with higher resections (21%; 5 of 24 patients) (p = 0.011). Graft length, number of resected vertebrae, and docking the FVFG on the endplate or cancellous bone was not associated with union or implant failure on univariate analysis.

CONCLUSIONS

The FVFG is an effective reconstruction technique, particularly in the cervicothoracic spine. However, high implant failure rates in the lumbar spine have been seen, which occurred even in cases in which the graft completely healed. Methods to increase the weight-bearing capacity of the graft in the lumbar spine should be considered in these reconstructions. Overall, the rates of failure and revision surgery for FVFG compare with previous reports on reconstruction after TES.

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Ronny L. Rotondo, Wendy Folkert, Norbert J. Liebsch, Yen-Lin E. Chen, Frank X. Pedlow, Joseph H. Schwab, Andrew E. Rosenberg, G. Petur Nielsen, Jackie Szymonifka, Al E. Ferreira, Francis J. Hornicek, and Thomas F. Delaney

OBJECT

Spinal chordomas can have high local recurrence rates after surgery with or without conventional dose radiation therapy (RT). Treatment outcomes and prognostic factors after high-dose proton-based RT with or without surgery were assessed.

METHODS

The authors conducted a retrospective review of 126 treated patients (127 lesions) categorized according to disease status (primary vs recurrent), resection (en bloc vs intralesional), margin status, and RT timing.

RESULTS

Seventy-one sacrococcygeal, 40 lumbar, and 16 thoracic chordomas were analyzed. Mean RT dose was 72.4 GyRBE (relative biological effectiveness). With median follow-up of 41 months, the 5-year overall survival (OS), local control (LC), locoregional control (LRC), and distant control (DC) for the entire cohort were 81%, 62%, 60%, and 77%, respectively. LC for primary chordoma was 68% versus 49% for recurrent lesions (p = 0.058). LC if treated with a component of preoperative RT was 72% versus 54% without this treatment (p = 0.113). Among primary tumors, LC and LRC were higher with preoperative RT, 85% (p = 0.019) and 79% (0.034), respectively, versus 56% and 56% if no preoperative RT was provided. Overall LC was significantly improved with en bloc versus intralesional resection (72% vs 55%, p = 0.016), as was LRC (70% vs 53%, p = 0.035). A trend was noted toward improved LC and LRC for R0/R1 margins and the absence of intralesional procedures.

CONCLUSIONS

High-dose proton-based RT in the management of spinal chordomas can be effective treatment. In patients undergoing surgery, those with primary chordomas undergoing preoperative RT, en bloc resection, and postoperative RT boost have the highest rate of local tumor control; among 28 patients with primary chordomas who underwent preoperative RT and en bloc resection, no local recurrences were seen. Intralesional and incomplete resections are associated with higher local failure rates and are to be avoided.

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Jeff Ehresman, Zach Pennington, Aditya V. Karhade, Sakibul Huq, Ravi Medikonda, Andrew Schilling, James Feghali, Andrew Hersh, A. Karim Ahmed, Ethan Cottrill, Daniel Lubelski, Erick M. Westbroek, Joseph H. Schwab, and Daniel M. Sciubba

OBJECTIVE

Incidental durotomy is a common complication of elective lumbar spine surgery seen in up to 11% of cases. Prior studies have suggested patient age and body habitus along with a history of prior surgery as being associated with an increased risk of dural tear. To date, no calculator has been developed for quantifying risk. Here, the authors’ aim was to identify independent predictors of incidental durotomy, present a novel predictive calculator, and externally validate a novel method to identify incidental durotomies using natural language processing (NLP).

METHODS

The authors retrospectively reviewed all patients who underwent elective lumbar spine procedures at a tertiary academic hospital for degenerative pathologies between July 2016 and November 2018. Data were collected regarding surgical details, patient demographic information, and patient medical comorbidities. The primary outcome was incidental durotomy, which was identified both through manual extraction and the NLP algorithm. Multivariable logistic regression was used to identify independent predictors of incidental durotomy. Bootstrapping was then employed to estimate optimism in the model, which was corrected for; this model was converted to a calculator and deployed online.

RESULTS

Of the 1279 elective lumbar surgery patients included in this study, incidental durotomy occurred in 108 (8.4%). Risk factors for incidental durotomy on multivariable logistic regression were increased surgical duration, older age, revision versus index surgery, and case starts after 4 pm. This model had an area under curve (AUC) of 0.73 in predicting incidental durotomies. The previously established NLP method was used to identify cases of incidental durotomy, of which it demonstrated excellent discrimination (AUC 0.97).

CONCLUSIONS

Using multivariable analysis, the authors found that increased surgical duration, older patient age, cases started after 4 pm, and a history of prior spine surgery are all independent positive predictors of incidental durotomy in patients undergoing elective lumbar surgery. Additionally, the authors put forth the first version of a clinical calculator for durotomy risk that could be used prospectively by spine surgeons when counseling patients about their surgical risk. Lastly, the authors presented an external validation of an NLP algorithm used to identify incidental durotomies through the review of free-text operative notes. The authors believe that these tools can aid clinicians and researchers in their efforts to prevent this costly complication in spine surgery.

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Predicting nonroutine discharge after elective spine surgery: external validation of machine learning algorithms

Presented at the 2019 AANS/CNS Joint Section on Disorders of the Spine and Peripheral Nerves

Brittany M. Stopa, Faith C. Robertson, Aditya V. Karhade, Melissa Chua, Marike L. D. Broekman, Joseph H. Schwab, Timothy R. Smith, and William B. Gormley

OBJECTIVE

Nonroutine discharge after elective spine surgery increases healthcare costs, negatively impacts patient satisfaction, and exposes patients to additional hospital-acquired complications. Therefore, prediction of nonroutine discharge in this population may improve clinical management. The authors previously developed a machine learning algorithm from national data that predicts risk of nonhome discharge for patients undergoing surgery for lumbar disc disorders. In this paper the authors externally validate their algorithm in an independent institutional population of neurosurgical spine patients.

METHODS

Medical records from elective inpatient surgery for lumbar disc herniation or degeneration in the Transitional Care Program at Brigham and Women’s Hospital (2013–2015) were retrospectively reviewed. Variables included age, sex, BMI, American Society of Anesthesiologists (ASA) class, preoperative functional status, number of fusion levels, comorbidities, preoperative laboratory values, and discharge disposition. Nonroutine discharge was defined as postoperative discharge to any setting other than home. The discrimination (c-statistic), calibration, and positive and negative predictive values (PPVs and NPVs) of the algorithm were assessed in the institutional sample.

RESULTS

Overall, 144 patients underwent elective inpatient surgery for lumbar disc disorders with a nonroutine discharge rate of 6.9% (n = 10). The median patient age was 50 years and 45.1% of patients were female. Most patients were ASA class II (66.0%), had 1 or 2 levels fused (80.6%), and had no diabetes (91.7%). The median hematocrit level was 41.2%. The neural network algorithm generalized well to the institutional data, with a c-statistic (area under the receiver operating characteristic curve) of 0.89, calibration slope of 1.09, and calibration intercept of −0.08. At a threshold of 0.25, the PPV was 0.50 and the NPV was 0.97.

CONCLUSIONS

This institutional external validation of a previously developed machine learning algorithm suggests a reliable method for identifying patients with lumbar disc disorder at risk for nonroutine discharge. Performance in the institutional cohort was comparable to performance in the derivation cohort and represents an improved predictive value over clinician intuition. This finding substantiates initial use of this algorithm in clinical practice. This tool may be used by multidisciplinary teams of case managers and spine surgeons to strategically invest additional time and resources into postoperative plans for this population.

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Aditya V. Karhade, Paul Ogink, Quirina Thio, Marike Broekman, Thomas Cha, William B. Gormley, Stuart Hershman, Wilco C. Peul, Christopher M. Bono, and Joseph H. Schwab

OBJECTIVE

If not anticipated and prearranged, hospital stay can be prolonged while the patient awaits placement in a rehabilitation unit or skilled nursing facility following elective spine surgery. Preoperative prediction of the likelihood of postoperative discharge to any setting other than home (i.e., nonroutine discharge) after elective inpatient spine surgery would be helpful in terms of decreasing hospital length of stay. The purpose of this study was to use machine learning algorithms to develop an open-access web application for preoperative prediction of nonroutine discharges in surgery for elective inpatient lumbar degenerative disc disorders.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program was queried to identify patients who underwent elective inpatient spine surgery for lumbar disc herniation or lumbar disc degeneration between 2011 and 2016. Four machine learning algorithms were developed to predict nonroutine discharge and the best algorithm was incorporated into an open-access web application.

RESULTS

The rate of nonroutine discharge for 26,364 patients who underwent elective inpatient surgery for lumbar degenerative disc disorders was 9.28%. Predictive factors selected by random forest algorithms were age, sex, body mass index, fusion, level, functional status, extent and severity of comorbid disease (American Society of Anesthesiologists classification), diabetes, and preoperative hematocrit level. On evaluation in the testing set (n = 5273), the neural network had a c-statistic of 0.823, calibration slope of 0.935, calibration intercept of 0.026, and Brier score of 0.0713. On decision curve analysis, the algorithm showed greater net benefit for changing management over all threshold probabilities than changing management on the basis of the American Society of Anesthesiologists classification alone or for all patients or for no patients. The model can be found here: https://sorg-apps.shinyapps.io/discdisposition/.

CONCLUSIONS

Machine learning algorithms show promising results on internal validation for preoperative prediction of nonroutine discharges. If found to be externally valid, widespread use of these algorithms via the open-access web application by healthcare professionals may help preoperative risk stratification of patients undergoing elective surgery for lumbar degenerative disc disorders.

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Nicolas Dea, Charles G. Fisher, Jeremy J. Reynolds, Joseph H. Schwab, Laurence D. Rhines, Ziya L. Gokaslan, Chetan Bettegowda, Arjun Sahgal, Áron Lazáry, Alessandro Luzzati, Stefano Boriani, Alessandro Gasbarrini, Ilya Laufer, Raphaële Charest-Morin, Feng Wei, William Teixeira, Niccole M. Germscheid, Francis J. Hornicek, Thomas F. DeLaney, John H. Shin, and the AOSpine Knowledge Forum Tumor

OBJECTIVE

The purpose of this study was to investigate the spectrum of current treatment protocols for managing newly diagnosed chordoma of the mobile spine and sacrum.

METHODS

A survey on the treatment of spinal chordoma was distributed electronically to members of the AOSpine Knowledge Forum Tumor, including neurosurgeons, orthopedic surgeons, and radiation oncologists from North America, South America, Europe, Asia, and Australia. Survey participants were pre-identified clinicians from centers with expertise in the treatment of spinal tumors. The suvey responses were analyzed using descriptive statistics.

RESULTS

Thirty-nine of 43 (91%) participants completed the survey. Most (80%) indicated that they favor en bloc resection without preoperative neoadjuvant radiation therapy (RT) when en bloc resection is feasible with acceptable morbidity. The main area of disagreement was with the role of postoperative RT, where 41% preferred giving RT only if positive margins were achieved and 38% preferred giving RT irrespective of margin status. When en bloc resection would result in significant morbidity, 33% preferred planned intralesional resection followed by RT, and 33% preferred giving neoadjuvant RT prior to surgery. In total, 8 treatment protocols were identified: 3 in which en bloc resection is feasible with acceptable morbidity and 5 in which en bloc resection would result in significant morbidity.

CONCLUSIONS

The results confirm that there is treatment variability across centers worldwide for managing newly diagnosed chordoma of the mobile spine and sacrum. This information will be used to design an international prospective cohort study to determine the most appropriate treatment strategy for patients with spinal chordoma.