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  • Author or Editor: Justin K. Scheer x
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Justin K. Scheer, Justin S. Smith, Frank Schwab, Virginie Lafage, Christopher I. Shaffrey, Shay Bess, Alan H. Daniels, Robert A. Hart, Themistocles S. Protopsaltis, Gregory M. Mundis Jr., Daniel M. Sciubba, Tamir Ailon, Douglas C. Burton, Eric Klineberg, Christopher P. Ames and The International Spine Study Group

OBJECTIVE

The operative management of patients with adult spinal deformity (ASD) has a high complication rate and it remains unknown whether baseline patient characteristics and surgical variables can predict early complications (intraoperative and perioperative [within 6 weeks]). The development of an accurate preoperative predictive model can aid in patient counseling, shared decision making, and improved surgical planning. The purpose of this study was to develop a model based on baseline demographic, radiographic, and surgical factors that can predict if patients will sustain an intraoperative or perioperative major complication.

METHODS

This study was a retrospective analysis of a prospective, multicenter ASD database. The inclusion criteria were age ≥ 18 years and the presence of ASD. In total, 45 variables were used in the initial training of the model including demographic data, comorbidities, modifiable surgical variables, baseline health-related quality of life, and coronal and sagittal radiographic parameters. Patients were grouped as either having at least 1 major intraoperative or perioperative complication (COMP group) or not (NOCOMP group). An ensemble of decision trees was constructed utilizing the C5.0 algorithm with 5 different bootstrapped models. Internal validation was accomplished via a 70/30 data split for training and testing each model, respectively. Overall accuracy, the area under the receiver operating characteristic (AUROC) curve, and predictor importance were calculated.

RESULTS

Five hundred fifty-seven patients were included: 409 (73.4%) in the NOCOMP group, and 148 (26.6%) in the COMP group. The overall model accuracy was 87.6% correct with an AUROC curve of 0.89 indicating a very good model fit. Twenty variables were determined to be the top predictors (importance ≥ 0.90 as determined by the model) and included (in decreasing importance): age, leg pain, Oswestry Disability Index, number of decompression levels, number of interbody fusion levels, Physical Component Summary of the SF-36, Scoliosis Research Society (SRS)–Schwab coronal curve type, Charlson Comorbidity Index, SRS activity, T-1 pelvic angle, American Society of Anesthesiologists grade, presence of osteoporosis, pelvic tilt, sagittal vertical axis, primary versus revision surgery, SRS pain, SRS total, use of bone morphogenetic protein, use of iliac crest graft, and pelvic incidence–lumbar lordosis mismatch.

CONCLUSIONS

A successful model (87% accuracy, 0.89 AUROC curve) was built predicting major intraoperative or perioperative complications following ASD surgery. This model can provide the foundation toward improved education and point-of-care decision making for patients undergoing ASD surgery.

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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.

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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.

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Samantha R. Horn, Peter G. Passias, Cheongeun Oh, Virginie Lafage, Renaud Lafage, Justin S. Smith, Breton Line, Neel Anand, Frank A. Segreto, Cole A. Bortz, Justin K. Scheer, Robert K. Eastlack, Vedat Deviren, Praveen V. Mummaneni, Alan H. Daniels, Paul Park, Pierce D. Nunley, Han Jo Kim, Eric O. Klineberg, Douglas C. Burton, Robert A. Hart, Frank J. Schwab, Shay Bess, Christopher I. Shaffrey, Christopher P. Ames and the International Spine Study Group

OBJECTIVE

Cervical deformity (CD) correction is clinically challenging. There is a high risk of developing complications with these highly complex procedures. The aim of this study was to use baseline demographic, clinical, and surgical factors to predict a poor outcome following CD surgery.

METHODS

The authors performed a retrospective review of a multicenter prospective CD database. CD was defined as at least one of the following: cervical kyphosis (C2–7 Cobb angle > 10°), cervical scoliosis (coronal Cobb angle > 10°), C2–7 sagittal vertical axis (cSVA) > 4 cm, or chin-brow vertical angle (CBVA) > 25°. Patients were categorized based on having an overall poor outcome or not. Health-related quality of life measures consisted of Neck Disability Index (NDI), EQ-5D, and modified Japanese Orthopaedic Association (mJOA) scale scores. A poor outcome was defined as having all 3 of the following categories met: 1) radiographic poor outcome: deterioration or severe radiographic malalignment 1 year postoperatively for cSVA or T1 slope–cervical lordosis mismatch (TS-CL); 2) clinical poor outcome: failing to meet the minimum clinically important difference (MCID) for NDI or having a severe mJOA Ames modifier; and 3) complications/reoperation poor outcome: major complication, death, or reoperation for a complication other than infection. Univariate logistic regression followed by multivariate regression models was performed, and internal validation was performed by calculating the area under the curve (AUC).

RESULTS

In total, 89 patients with CD were included (mean age 61.9 years, female sex 65.2%, BMI 29.2 kg/m2). By 1 year postoperatively, 18 (20.2%) patients were characterized as having an overall poor outcome. For radiographic poor outcomes, patients’ conditions either deteriorated or remained severe for TS-CL (73% of patients), cSVA (8%), horizontal gaze (34%), and global SVA (28%). For clinical poor outcomes, 80% and 60% of patients did not reach MCID for EQ-5D and NDI, respectively, and 24% of patients had severe symptoms (mJOA score 0–11). For the complications/reoperation poor outcome, 28 patients experienced a major complication, 11 underwent a reoperation, and 1 had a complication-related death. Of patients with a poor clinical outcome, 75% had a poor radiographic outcome; 35% of poor radiographic and 37% of poor clinical outcome patients had a major complication. A poor outcome was predicted by the following combination of factors: osteoporosis, baseline neurological status, use of a transition rod, number of posterior decompressions, baseline pelvic tilt, T2–12 kyphosis, TS-CL, C2–T3 SVA, C2–T1 pelvic angle (C2 slope), global SVA, and number of levels in maximum thoracic kyphosis. The final model predicting a poor outcome (AUC 86%) included the following: osteoporosis (OR 5.9, 95% CI 0.9–39), worse baseline neurological status (OR 11.4, 95% CI 1.8–70.8), baseline pelvic tilt > 20° (OR 0.92, 95% CI 0.85–0.98), > 9 levels in maximum thoracic kyphosis (OR 2.01, 95% CI 1.1–4.1), preoperative C2–T3 SVA > 5.4 cm (OR 1.01, 95% CI 0.9–1.1), and global SVA > 4 cm (OR 3.2, 95% CI 0.09–10.3).

CONCLUSIONS

Of all CD patients in this study, 20.2% had a poor overall outcome, defined by deterioration in radiographic and clinical outcomes, and a major complication. Additionally, 75% of patients with a poor clinical outcome also had a poor radiographic outcome. A poor overall outcome was most strongly predicted by severe baseline neurological deficit, global SVA > 4 cm, and including more of the thoracic maximal kyphosis in the construct.