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
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.
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.
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.
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.
David B. Bumpass, Lawrence G. Lenke, Jeffrey L. Gum, Christopher I. Shaffrey, Justin S. Smith, Christopher P. Ames, Shay Bess, Brian J. Neuman, Eric Klineberg, Gregory M. Mundis Jr., Frank Schwab, Virginie Lafage, Han Jo Kim, Douglas C. Burton, Khaled M. Kebaish, Richard Hostin, Renaud Lafage, Michael P. Kelly and for the International Spine Study Group
Adolescent spine deformity studies have shown that male patients require longer surgery and have greater estimated blood loss (EBL) and complications compared with female patients. No studies exist to support this relationship in adult spinal deformity (ASD). The purpose of this study was to investigate associations between sex and complications, deformity correction, and health-related quality of life (HRQOL) in patients with ASD. It was hypothesized that male ASD patients would have greater EBL, longer surgery, and more complications than female ASD patients.
A multicenter ASD cohort was retrospectively queried for patients who underwent primary posterior-only instrumented fusions with a minimum of 5 levels fused. The minimum follow-up was 2 years. Primary outcomes were EBL, operative time, intra-, peri-, and postoperative complications, radiographic correction, and HRQOL outcomes (Oswestry Disability Index, SF-36, and Scoliosis Research Society-22r Questionnaire). Poisson multivariate regression was used to control for age, comorbidities, and levels fused.
Ninety male and 319 female patients met the inclusion criteria. Male patients had significantly greater mean EBL (2373 ml vs 1829 ml, p = 0.01). The mean operative time, transfusion requirements, and final radiographic measurements did not differ between sexes. Similarly, changes in HRQOL showed no significant differences. Finally, there were no sex differences in the incidence of complications (total, major, or minor) at any time point after controlling for age, body mass index, comorbidities, and levels fused.
Despite higher EBL, male ASD patients did not experience more complications or require less deformity correction at the 2-year follow-up. HRQOL scores similarly showed no sex differences. These findings differ from adolescent deformity studies, and surgeons can counsel patients that sex is unlikely to influence the outcomes and complication rates of primary all-posterior ASD surgery.
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
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.
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.
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).
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.
Phoenix, Arizona • March 6–9, 2013