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Joshua Bakhsheshian, Nader S. Dahdaleh, Shayan Fakurnejad, Justin K. Scheer and Zachary A. Smith

Object

The overall evidence for nonoperative management of patients with traumatic thoracolumbar burst fractures is unknown. There is no agreement on the optimal method of conservative treatment. Recent randomized controlled trials that have compared nonoperative to operative treatment of thoracolumbar burst fractures without neurological deficits yielded conflicting results. By assessing the level of evidence on conservative management through validated methodologies, clinicians can assess the availability of critically appraised literature. The purpose of this study was to examine the level of evidence for the use of conservative management in traumatic thoracolumbar burst fractures.

Methods

A comprehensive search of the English literature over the past 20 years was conducted using PubMed (MEDLINE). The inclusion criteria consisted of burst fractures resulting from a traumatic mechanism, and fractures of the thoracic or lumbar spine. The exclusion criteria consisted of osteoporotic burst fractures, pathological burst fractures, and fractures located in the cervical spine. Of the studies meeting the inclusion/exclusion criteria, any study in which nonoperative treatment was used was included in this review.

Results

One thousand ninety-eight abstracts were reviewed and 447 papers met inclusion/exclusion criteria, of which 45 were included in this review. In total, there were 2 Level-I, 7 Level-II, 9 Level-III, 25 Level-IV, and 2 Level-V studies. Of the 45 studies, 16 investigated conservative management techniques, 20 studies compared operative to nonoperative treatments, and 9 papers investigated the prognosis of conservative management.

Conclusions

There are 9 high-level studies (Levels I–II) that have investigated the conservative management of traumatic thoracolumbar burst fractures. In neurologically intact patients, there is no superior conservative management technique over another as supported by a high level of evidence. The conservative technique can be based on patient and surgeon preference, comfort, and access to resources. A high level of evidence demonstrated similar functional outcomes with conservative management when compared with open surgical operative management in patients who were neurologically intact. The presence of a neurological deficit is not an absolute contraindication for conservative treatment as supported by a high level of evidence. However, the majority of the literature excluded patients with neurological deficits. More evidence is needed to further classify the appropriate burst fractures for conservative management to decrease variables that may impact the prognosis.

Free access

Alejandro J. Lopez, Justin K. Scheer, Kayla E. Leibl, Zachary A. Smith, Brian J. Dlouhy and Nader S. Dahdaleh

The craniovertebral junction (CVJ) has unique anatomical structures that separate it from the subaxial cervical spine. In addition to housing vital neural and vascular structures, the majority of cranial flexion, extension, and axial rotation is accomplished at the CVJ. A complex combination of osseous and ligamentous supports allow for stability despite a large degree of motion. An understanding of anatomy and biomechanics is essential to effectively evaluate and address the various pathological processes that may affect this region. Therefore, the authors present an up-to-date narrative review of CVJ anatomy, normal and pathological biomechanics, and fixation techniques.

Free access

Emily K. Miller, Brian J. Neuman, Amit Jain, Alan H. Daniels, Tamir Ailon, Daniel M. Sciubba, Khaled M. Kebaish, Virginie Lafage, Justin K. Scheer, Justin S. Smith, Shay Bess, Christopher I. Shaffrey, Christopher P. Ames and the International Spine Study Group

OBJECTIVE

The goal of this study was to analyze the value of an adult spinal deformity frailty index (ASD-FI) in preoperative risk stratification. Preoperative risk assessment is imperative before procedures known to have high complication rates, such as ASD surgery. Frailty has been associated with risk of complications in trauma surgery, and preoperative frailty assessments could improve the accuracy of risk stratification by providing a comprehensive analysis of patient factors that contribute to an increased risk of complications.

METHODS

Using 40 variables, the authors calculated frailty scores with a validated method for 417 patients (enrolled between 2010 and 2014) with a minimum 2-year follow-up in an ASD database. On the basis of these scores, the authors categorized patients as not frail (NF) (< 0.3 points), frail (0.3–0.5 points), or severely frail (SF) (> 0.5 points). The correlation between frailty category and incidence of complications was analyzed.

RESULTS

The overall mean ASD-FI score was 0.33 (range 0.0–0.8). Compared with NF patients (n = 183), frail patients (n = 158) and SF patients (n = 109) had longer mean hospital stays (1.2 and 1.6 times longer, respectively; p < 0.001). The adjusted odds of experiencing a major intraoperative or postoperative complication were higher for frail patients (OR 2.8) and SF patients ( 4.1) compared with NF patients (p < 0.01). For frail and SF patients, respectively, the adjusted odds of developing proximal junctional kyphosis (OR 2.8 and 3.1) were higher than those for NF patients. The SF patients had higher odds of developing pseudarthrosis (OR 13.0), deep wound infection (OR 8.0), and wound dehiscence (OR 13.4) than NF patients (p < 0.05), and they had 2.1 times greater odds of reoperation (p < 0.05).

CONCLUSIONS

Greater patient frailty, as measured by the ASD-FI, was associated with worse outcome in many common quality and value metrics, including greater risk of major complications, proximal junctional kyphosis, pseudarthrosis, deep wound infection, wound dehiscence, reoperation, and longer hospital stay.

Free access

Taemin Oh, Justin K. Scheer, Justin S. Smith, Richard Hostin, Chessie Robinson, Jeffrey L. Gum, Frank Schwab, Robert A. Hart, Virginie Lafage, Douglas C. Burton, Shay Bess, Themistocles Protopsaltis, Eric O. Klineberg, Christopher I. Shaffrey, Christopher P. Ames and the International Spine Study Group

OBJECTIVE

Patients with adult spinal deformity (ASD) experience significant quality of life improvements after surgery. Treatment, however, is expensive and complication rates are high. Predictive analytics has the potential to use many variables to make accurate predictions in large data sets. A validated minimum clinically important difference (MCID) model has the potential to assist in patient selection, thereby improving outcomes and, potentially, cost-effectiveness.

METHODS

The present study was a retrospective analysis of a multiinstitutional database of patients with ASD. Inclusion criteria were as follows: age ≥ 18 years, radiographic evidence of ASD, 2-year follow-up, and preoperative Oswestry Disability Index (ODI) > 15. Forty-six variables were used for model training: demographic data, radiographic parameters, surgical variables, and results on the health-related quality of life questionnaire. Patients were grouped as reaching a 2-year ODI MCID (+MCID) or not (−MCID). An ensemble of 5 different bootstrapped decision trees was constructed using the C5.0 algorithm. Internal validation was performed via 70:30 data split for training/testing. Model accuracy and area under the curve (AUC) were calculated. The mean quality-adjusted life years (QALYs) and QALYs gained at 2 years were calculated and discounted at 3.5% per year. The QALYs were compared between patients in the +MCID and –MCID groups.

RESULTS

A total of 234 patients met inclusion criteria (+MCID 129, −MCID 105). Sixty-nine patients (29.5%) were included for model testing. Predicted versus actual results were 50 versus 40 for +MCID and 19 versus 29 for −MCID (i.e., 10 patients were misclassified). Model accuracy was 85.5%, with 0.96 AUC. Predicted results showed that patients in the +MCID group had significantly greater 2-year mean QALYs (p = 0.0057) and QALYs gained (p = 0.0002).

CONCLUSIONS

A successful model with 85.5% accuracy and 0.96 AUC was constructed to predict which patients would reach ODI MCID. The patients in the +MCID group had significantly higher mean 2-year QALYs and QALYs gained. This study provides proof of concept for using predictive modeling techniques to optimize patient selection in complex spine surgery.

Free access

Justin K. Scheer, Taemin Oh, Justin S. Smith, Christopher I. Shaffrey, Alan H. Daniels, Daniel M. Sciubba, D. Kojo Hamilton, Themistocles S. Protopsaltis, Peter G. Passias, Robert A. Hart, Douglas C. Burton, Shay Bess, Renaud Lafage, Virginie Lafage, Frank Schwab, Eric O. Klineberg, Christopher P. Ames and the International Spine Study Group

OBJECTIVE

Pseudarthrosis can occur following adult spinal deformity (ASD) surgery and can lead to instrumentation failure, recurrent pain, and ultimately revision surgery. In addition, it is one of the most expensive complications of ASD surgery. Risk factors contributing to pseudarthrosis in ASD have been described; however, a preoperative model predicting the development of pseudarthrosis does not exist. The goal of this study was to create a preoperative predictive model for pseudarthrosis based on demographic, radiographic, and surgical factors.

METHODS

A retrospective review of a prospectively maintained, multicenter ASD database was conducted. Study inclusion criteria consisted of adult patients (age ≥ 18 years) with spinal deformity and surgery for the ASD. From among 82 variables assessed, 21 were used for model building after applying collinearity testing, redundancy, and univariable predictor importance ≥ 0.90. Variables included demographic data along with comorbidities, modifiable surgical variables, baseline coronal and sagittal radiographic parameters, and baseline scores for health-related quality of life measures. Patients groups were determined according to their Lenke radiographic fusion type at the 2-year follow-up: bilateral or unilateral fusion (union) or pseudarthrosis (nonunion). A decision tree was constructed, and internal validation was accomplished via bootstrapped training and testing data sets. Accuracy and the area under the receiver operating characteristic curve (AUC) were calculated to evaluate the model.

RESULTS

A total of 336 patients were included in the study (nonunion: 105, union: 231). The model was 91.3% accurate with an AUC of 0.94. From 82 initial variables, the top 21 covered a wide range of areas including preoperative alignment, comorbidities, patient demographics, and surgical use of graft material.

CONCLUSIONS

A model for predicting the development of pseudarthrosis at the 2-year follow-up was successfully created. This model is the first of its kind for complex predictive analytics in the development of pseudarthrosis for patients with ASD undergoing surgical correction and can aid in clinical decision-making for potential preventative strategies.