Browsing by Author "Osorio, Joseph A"

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    ItemOpen Access
    Development of a Preoperative Predictive Model for Reaching the Oswestry Disability Index Minimal Clinically Important Difference for Adult Spinal Deformity Patients
    (Spine Deformity, 2018-09-01) Scheer, Justin K; Osorio, Joseph A; Smith, Justin S; Schwab, Frank; Hart, Robert A; Hostin, Richard; Lafage, Virginie; Jain, Amit; Burton, Douglas C; Bess, Shay; Ailon, Tamir; Protopsaltis, Themistocles S; Klineberg, Eric O; Shaffrey, Christopher I; Ames, Christopher P; International Spine Study Group
    © 2018 Scoliosis Research Society Study Design: Retrospective review of prospective multicenter adult spinal deformity (ASD) database. Objective: To create a model based on baseline demographic, radiographic, health-related quality of life (HRQOL), and surgical factors that can predict patients meeting the Oswestry Disability Index (ODI) minimal clinically important difference (MCID) at the two-year postoperative follow-up. Summary of Background Data: Surgical correction of ASD can result in significant improvement in disability as measured by ODI, with the goal of reaching at least one MCID. However, a predictive model for reaching MCID following ASD correction does not exist. Methods: ASD patients ≥18 years and baseline ODI ≥ 30 were included. Initial training of the model comprised forty-three variables including demographic data, comorbidities, modifiable surgical variables, baseline HRQOL, and coronal/sagittal radiographic parameters. Patients were grouped by whether or not they reached at least one ODI MCID at two-year follow-up. Decision trees were constructed using the C5.0 algorithm with five different bootstrapped models. Internal validation was accomplished via a 70:30 data split for training and testing each model, respectively. Final predictions from the models were chosen by voting with random selection for tied votes. Overall accuracy, and the area under a receiver operating characteristic curve (AUC) were calculated. Results: 198 patients were included (MCID: 109, No-MCID: 89). Overall model accuracy was 86.0%, with an AUC of 0.94. The top 11 predictors of reaching MCID were gender, Scoliosis Research Society (SRS) activity subscore, back pain, sagittal vertical axis (SVA), pelvic incidence–lumbar lordosis mismatch (PI-LL), primary version revision, T1 spinopelvic inclination angle (T1SPI), American Society of Anesthesiologists (ASA) grade, T1 pelvic angle (T1PA), SRS pain, SRS total. Conclusions: A successful model was built predicting ODI MCID. Most important predictors were not modifiable surgical parameters, indicating that baseline clinical and radiographic status is a critical factor for reaching ODI MCID. Level of Evidence: Level II.
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    ItemOpen Access
    Development of Validated Computer-based Preoperative Predictive Model for Proximal Junction Failure (PJF) or Clinically Significant PJK With 86% Accuracy Based on 510 ASD Patients With 2-year Follow-up.
    (Spine, 2016-11) Scheer, Justin K; Osorio, Joseph A; Smith, Justin S; Schwab, Frank; Lafage, Virginie; Hart, Robert A; Bess, Shay; Line, Breton; Diebo, Bassel G; Protopsaltis, Themistocles S; Jain, Amit; Ailon, Tamir; Burton, Douglas C; Shaffrey, Christopher I; Klineberg, Eric; Ames, Christopher P; International Spine Study Group

    Study design

    A retrospective review of large, multicenter adult spinal deformity (ASD) database.

    Objective

    The aim of this study was to build a model based on baseline demographic, radiographic, and surgical factors that can predict clinically significant proximal junctional kyphosis (PJK) and proximal junctional failure (PJF).

    Summary of background data

    PJF and PJK are significant complications and it remains unclear what are the specific drivers behind the development of either. There exists no predictive model that could potentially aid in the clinical decision making for adult patients undergoing deformity correction.

    Methods

    Inclusion criteria: age ≥18 years, ASD, at least four levels fused. Variables included in the model were demographics, primary/revision, use of three-column osteotomy, upper-most instrumented vertebra (UIV)/lower-most instrumented vertebra (LIV) levels and UIV implant type (screw, hooks), number of levels fused, and baseline sagittal radiographs [pelvic tilt (PT), pelvic incidence and lumbar lordosis (PI-LL), thoracic kyphosis (TK), and sagittal vertical axis (SVA)]. PJK was defined as an increase from baseline of proximal junctional angle ≥20° with concomitant deterioration of at least one SRS-Schwab sagittal modifier grade from 6 weeks postop. PJF was defined as requiring revision for PJK. An ensemble of decision trees were constructed using the C5.0 algorithm with five different bootstrapped models, and internally validated via a 70 : 30 data split for training and testing. Accuracy and the area under a receiver operator characteristic curve (AUC) were calculated.

    Results

    Five hundred ten patients were included, with 357 for model training and 153 as testing targets (PJF: 37, PJK: 102). The overall model accuracy was 86.3% with an AUC of 0.89 indicating a good model fit. The seven strongest (importance ≥0.95) predictors were age, LIV, pre-operative SVA, UIV implant type, UIV, pre-operative PT, and pre-operative PI-LL.

    Conclusion

    A successful model (86% accuracy, 0.89 AUC) was built predicting either PJF or clinically significant PJK. This model can set the groundwork for preop point of care decision making, risk stratification, and need for prophylactic strategies for patients undergoing ASD surgery.

    Level of evidence

    3.
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    ItemOpen Access
    Proximal Junctional Kyphosis Prevention Strategies: A Video Technique Guide.
    (Operative neurosurgery (Hagerstown, Md.), 2017-10) Safaee, Michael M; Osorio, Joseph A; Verma, Kushagra; Bess, Shay; Shaffrey, Christopher I; Smith, Justin S; Hart, Robert; Deviren, Vedat; Ames, Christopher P
    BACKGROUND:Proximal junctional kyphosis (PJK) is a well-recognized complication in patients undergoing posterior instrumented fusion procedures for adult spinal deformity. Strategies that reduce rates of PJK have the potential to improve the safety of these operations and decrease cost by eliminating the need for revision surgery. OBJECTIVE:To present a set of surgical techniques that can decrease rates of PJK in adults undergoing surgery for spinal deformity. METHODS:We summarize the use of vertebroplasty, transverse process hooks, terminal rod contouring, and ligament augmentation as means to reduce rates of PJK. RESULTS:We present PJK prevention strategies and a video technique guide that are safe, technically feasible, and add minimal operative time to these surgical procedures. When applied to appropriate high-risk patients, these techniques have the potential to dramatically reduce rates of PJK, which improves quality of life and decreases the cost associated with this treating adult spinal deformity. CONCLUSION:PJK prevention strategies represent a critical area for improvement in surgery for adult spinal deformity. We present a summary of techniques that are safe, feasible, and add minimal time to the overall procedure. These techniques warrant investigation in a thoughtful, prospective manner, but are supported by existing data and compelling biomechanical rationale. Our hope is that these strategies can be applied, particularly in high-risk patients, to help reduce rates of PJK.