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ObjectiveExtension of the posterior upper-most instrumented vertebra (UIV) into the upper thoracic (UT) spine allows for greater deformity correction and reduced incidence of proximal junction kyphosis (PJK) in adult spinal deformity (ASD) patients. However, it may be associated with chronic postoperative scapular pain (POSP). The goal of this study was to assess the relationship between UT UIV and persistent POSP, describe the pain, and assess its impact on patient disability.MethodsASD patients who underwent multilevel posterior fusion were retrospectively identified then administered a survey regarding scapular pain and the Oswestry Disability Index (ODI), by telephone. Univariate and multivariate analysis were utilized.ResultsA total of 74 ASD patients were included in the study: 37 patients with chronic POSP and 37 without scapular pain. The mean age was 70.5 years, and 63.9% were women. There were no significant differences in clinical characteristics, including mechanical complications (PJK, pseudarthrosis, and rod fracture) or reoperation between groups. Patients with persistent POSP were more likely to have a UT than a lower thoracic UIV (p = 0.018). UT UIV was independently associated with chronic POSP on multivariate analysis (p = 0.022). ODI score was significantly higher in patients with scapular pain (p = 0.001). Chronic POSP (p = 0.001) and prior spine surgery (p = 0.037) were independently associated with ODI on multivariate analysis.ConclusionA UT UIV is independently associated with increased odds of chronic POSP, and this pain is associated with significant increases in patient disability. It is a significant clinical problem despite solid radiographic fusion and the absence of PJK.

Adult spinal deformity (ASD) is a complex and heterogeneous disease that can severely impact patients' lives. While it is clear that surgical correction can achieve significant improvement of spinopelvic parameters and quality of life measures in adults with spinal deformity, there remains a high risk of complication associated with surgical approaches to adult deformity. Over the past decade, utilization of surgical correction for ASD has increased dramatically as deformity correction techniques have become more refined and widely adopted. Along with this increase in surgical utilization, there has been a massive undertaking by spine surgeons to develop more robust models to predict postoperative outcomes in an effort to mitigate the relatively high complication rates. A large part of this revolution within spine surgery has been the gradual adoption of predictive analytics harnessing artificial intelligence through the use of machine learning algorithms. The development of predictive models to accurately prognosticate patient outcomes following ASD surgery represents a dramatic improvement over prior statistical models which are better suited for finding associations between variables than for their predictive utility. Machine learning models, which offer the ability to make more accurate and reproducible predictions, provide surgeons with a wide array of practical applications from augmenting clinical decision making to more wide-spread public health implications. The inclusion of these advanced computational techniques in spine practices will be paramount for improving the care of patients, by empowering both patients and surgeons to more specifically tailor clinical decisions to address individual health profiles and needs.

Study designRetrospective review of a multicenter prospective registry.ObjectivesOur goal was to develop a method to risk-stratify adult spinal deformity (ASD) patients on the basis of their accumulated health deficits. We developed a novel comorbidity score (CS) specific to patients with ASD based on their preoperative health state and investigated whether it was associated with major complications, length of hospital stay (LOS), and self-reported outcomes after ASD surgery.MethodsWe identified 273 operatively treated ASD patients with 2-year follow-up. We assessed associations between major complications and age, comorbidities, Charlson Comorbidity Index score, and Oswestry Disability Index score. Significant factors were used to construct the ASD-CS. Associations of ASD-CS with major complications, LOS, and patient-reported outcomes were analyzed.ResultsMajor complications increased significantly with ASD-CS (P < .01). Compared with patients with ASD-CS of 0, the odds of major complications were 2.8-fold higher (P = .068) in patients with ASD-CS of 1 through 3; 4.5-fold higher (P < .01) in patients with ASD-CS of 4 through 6; and 7.5-fold higher (P < .01) in patients with ASD-CS of 7 or 8. Patients with ASD-CS of 7 or 8 had the longest mean LOS (10.7 days) and worst mean Scoliosis Research Society-22r total score at baseline; however, they experienced the greatest mean improvement (0.98 points) over 2 years.ConclusionsThe ASD-CS is significantly associated with major complications, LOS, and patient-reported outcomes in operatively treated ASD patients.

BackgroundFor cervical deformity (CD) surgery, goals include realignment, improved patient quality of life, and improved clinical outcomes. There is limited research identifying patients most likely to achieve all three.ObjectiveThe objective is to create a model predicting good 1-year postoperative realignment, quality of life, and clinical outcomes following CD surgery using baseline demographic, clinical, and radiographic factors.MethodsRetrospective review of a multicenter CD database. CD patients were defined as having one of the following radiographic criteria: Cervical sagittal vertical axis (cSVA) >4 cm, cervical kyphosis/scoliosis >10°° or chin-brow vertical angle >25°. The outcome assessed was whether a patient achieved both a good radiographic and clinical outcome. The primary analysis was stepwise regression models which generated a dataset-specific prediction model for achieving a good radiographic and clinical outcome. Model internal validation was achieved by bootstrapping and calculating the area under the curve (AUC) of the final model with 95% confidence intervals.ResultsSeventy-three CD patients were included (61.8 years, 58.9% F). The final model predicting the achievement of a good overall outcome (radiographic and clinical) yielded an AUC of 73.5% and included the following baseline demographic, clinical, and radiographic factors: mild-moderate myelopathy (Modified Japanese Orthopedic Association >12), no pedicle subtraction osteotomy, no prior cervical spine surgery, posterior lowest instrumented vertebra (LIV) at T1 or above, thoracic kyphosis >33°°, T1 slope

Study designRetrospective cohort study.ObjectiveFactors that predict outcomes for adult cervical spine deformity (ACSD) have not been well defined. To compare ACSD patients with best versus worst outcomes.MethodsThis study was based on a prospective, multicenter observational ACSD cohort. Best versus worst outcomes were compared based on Neck Disability Index (NDI), Neck Pain Numeric Rating Scale (NP-NRS), and modified Japanese Orthopaedic Association (mJOA) scores.ResultsOf 111 patients, 80 (72%) had minimum 1-year follow-up. For NDI, compared with best outcome patients (n = 28), worst outcome patients (n = 32) were more likely to have had a major complication (P = .004) and to have undergone a posterior-only procedure (P = .039), had greater Charlson Comorbidity Index (P = .009), and had worse postoperative C7-S1 sagittal vertical axis (SVA; P = .027). For NP-NRS, compared with best outcome patients (n = 26), worst outcome patients (n = 18) were younger (P = .045), had worse baseline NP-NRS (P = .034), and were more likely to have had a minor complication (P = .030). For the mJOA, compared with best outcome patients (n = 16), worst outcome patients (n = 18) were more likely to have had a major complication (P = .007) and to have a better baseline mJOA (P = .030). Multivariate models for NDI included posterior-only surgery (P = .006), major complication (P = .002), and postoperative C7-S1 SVA (P = .012); models for NP-NRS included baseline NP-NRS (P = .009), age (P = .017), and posterior-only surgery (P = .038); and models for mJOA included major complication (P = .008).ConclusionsFactors distinguishing best and worst ACSD surgery outcomes included patient, surgical, and radiographic factors. These findings suggest areas that may warrant greater awareness to optimize patient counseling and outcomes.

Study designRetrospective cohort study.ObjectiveDetermine the indications, complications, and clinical outcomes in patients requiring fusions from the cervical spine to the pelvis. Several investigators have examined fusions from the thoracic spine to the sacrum, but no similar study has been performed for cervical-to-pelvis fusions.MethodsPatients from 2003 to 2014 with an upper instrumented vertebrae (UIV) in the cervical spine (any level) and a lower instrumented vertebrae (LIV) in the sacrum or pelvis were included in the study. Those with infectious or acute trauma-related deformities were excluded. Patient demographics, medical history, diagnosis, operative procedure, and health-related quality of life measures were analyzed. Student's t test, Kruskal-Wallis test, and χ2 test were used as appropriate; significance was set at P < .05 for all tests.ResultsFifty-five patients met inclusion criteria for the study. Average follow-up was 2.8 years. Proximal junctional kyphosis was the most common indication for cervical-to-pelvis fusions (36%). The most common UIV was C2 (29%) followed by C7 (24%). There was an average 31° correction in maximum kyphosis and a 3.3 cm improvement in sagittal vertical axis. In adults, the rate of complication was 71.4%, with a major complication rate of 39.3% and reoperation rate of 53.6%. There was significant improvement in the Scoliosis Research Society (SRS-22r) score (3.0 to 3.5; P < .01).ConclusionProximal junctional kyphosis is the most common indication for patients requiring fusion to the cervical spine. Adult patients incur a significant risk of major complications and reoperations. However, significant improvement in SRS-22r outcomes are noted in these patients.

PurposeEvaluate the presence of new-onset cervical deformity (CD) in nonoperative adult spinal deformity (ASD) patients with extended follow-up, with consideration for predictors, prevalence, and impact on patient-reported outcomes.MethodsRetrospective review of a prospective nonoperative ASD cohort. New onset CD patients at 1- (CD-1Y) and 2-year (CD-2Y) follow-up were defined as displaying baseline cervical alignment. Univariate analyses determined differences in radiographic parameters and outcome scores of CD and maintained-cervical-alignment patients. Multivariate binary logistic regression models determined new-onset CD predictors.ResultsA total of 143 patients were included (mean age 54 years, mean body mass index 25.6 kg/m2, 86% female). Cervical deformity rate was 38.5% at baseline. New-onset CD incidence at 1- and 2-year follow-up was 30.0% and 41.7%, respectively. Global sagittal profile comparison of CD-1Y/CD-2Y versus maintained cervical alignment cases revealed no differences (P > .05) at any interval. Baseline C2-C7 sagittal vertical axis (SVA) was associated with increased new-onset CD risk at 1 (odds ratio [OR] 1.14, P = .025) and 2 years (OR 1.04, P = .032); prior spine surgical history was associated with CD risk at 1-year follow-up (OR 6.75, P = .047); baseline C2 slope was associated with increased CD risk at 2-year follow-up (OR 1.12, P = .041). CD development did not significantly impact health-related quality of life (P > .05).ConclusionsCervical deformity can manifest in nonoperative ASD patients: 30.0% at 1-year follow-up, and 41.7% at 2-year follow-up. Progressive CD manifested independently of thoracolumbar profile changes. Increased baseline C2-C7 SVA, C2 slope, and prior surgical history increased new-onset CD odds at 1 and 2 years.

Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.