US regional variations in rates, outcomes, and costs of spinal arthrodesis for lumbar spinal stenosis in working adults aged 40-65 years

International Variability in Spinal Metastasis Treatment: A Survey of the AO Spine Community

STUDY DESIGN

International survey.

OBJECTIVES

To assess variability in the treatment practices for spinal metastases as a function of practice setting, surgical specialty, and fellowship training among an international group of spine surgeons.

METHODS

An anonymous internet-based survey was disseminated to the AO Spine membership. The questionnaire contained items on practice settings, fellowship training, indications used for spinal metastasis surgery, surgical strategies, multidisciplinary team use, and postoperative follow-up priorities and practice.

RESULTS

341 gave complete responses to the survey with 76.3% identifying spinal oncology as a practice focus and 95.6% treating spinal metastases. 80% use the Spinal Instability Neoplastic Score (SINS) to guide instrumentation decision-making and 60.7% recruit multidisciplinary teams for some or all cases. Priorities for postoperative follow-up are adjuvant radiotherapy (80.9%) and systemic therapy (74.8%). Most schedule first follow-up within 6 weeks of surgery (62.2%). Significant response heterogeneity was seen when stratifying by practice in an academic or university-affiliated center, practice in a cancer center, completion of a spine oncology fellowship, and self-identification as a tumor specialist. Respondents belonging to any of these categories were more likely to utilize SINS (P < .01-.02), recruit assistance from plastic surgeons (all P < .01), and incorporate radiation oncologists in postoperative care (P < .01-.03).

CONCLUSIONS

The largest variability in practice strategies is based upon practice setting, spine tumor specialization, and completion of a spine oncology fellowship. These respondents were more likely to use evidenced-based practices. However, the response variability indicates the need for consensus building, particularly for postoperative spine metastasis care pathways and multidisciplinary team use.

External validation of a predictive algorithm for in-hospital and ninety-day mortality after spinal epidural abscess

BACKGROUND CONTEXT

Mortality in patients with spinal epidural abscess (SEA) remains high. Accurate prediction of patient-specific prognosis in SEA can improve patient counseling as well as guide management decisions. There are no externally validated studies predicting short-term mortality in patients with SEA.

PURPOSE

The purpose of this study was to externally validate the Skeletal Oncology Research Group (SORG) stochastic gradient boosting algorithm for prediction of in-hospital and 90-day postdischarge mortality in SEA.

STUDY DESIGN/SETTING

Retrospective, case-control study at a tertiary care academic medical center from 2003 to 2021.

PATIENT SAMPLE

Adult patients admitted for radiologically confirmed diagnosis of SEA who did not initiate treatment at an outside institution.

OUTCOME MEASURES

In-hospital and 90-day postdischarge mortality.

METHODS

We tested the SORG stochastic gradient boosting algorithm on an independent validation cohort. We assessed its performance with discrimination, calibration, decision curve analysis, and overall performance.

RESULTS

A total of 212 patients met inclusion criteria, with a short-term mortality rate of 10.4%. The area under the receiver operating characteristic curve (AUROC) of the SORG algorithm when tested on the full validation cohort was 0.82, the calibration intercept was -0.08, the calibration slope was 0.96, and the Brier score was 0.09.

CONCLUSIONS

With a contemporaneous and geographically distinct independent cohort, we report successful external validation of a machine learning algorithm for prediction of in-hospital and 90-day postdischarge mortality in SEA.

Trends in Reimbursement and Approach Selection for Lumbar Arthrodesis

BACKGROUND

Changes in reimbursement policies have been demonstrated to correlate with clinical practice.

OBJECTIVE

To investigate trends in physician reimbursement for anterior, posterior, and combined anterior/posterior (AP) lumbar arthrodesis and relative utilization of AP.

METHODS

We queried the American College of Surgeons National Surgical Quality Improvement Project registry for anterior, posterior, and AP lumbar arthrodeses during 2010 and 2020. Work relative value units per operative hour (wRVUs/h) were calculated for each procedure. Trends in reimbursement and utilization of the AP approach were assessed with linear regression. Subgroup analyses of age and underlying pathology of AP arthrodesis were also performed.

RESULTS

During 2010 and 2020, AP arthrodesis was associated with significantly higher average wRVUs/h compared with anterior and posterior arthrodesis (AP = 17.4, anterior = 12.4, posterior = 14.5). The AP approach had a significant yearly increase in wRVUs/h (coefficient = 0.48, P = .042), contrary to anterior (coefficient = -0.01, P = .308) and posterior (coefficient = -0.13, P = .006) approaches. Utilization of AP approaches over all arthrodeses increased from 7.5% in 2010 to 15.3% in 2020 (yearly average increase 0.79%, P < .001). AP fusions increased significantly among both degenerative and deformity cases (coefficients 0.88 and 1.43, respectively). The mean age of patients undergoing AP arthrodesis increased by almost 10 years from 2010 to 2020. Rates of major 30-day complications were 2.7%, 3.1%, and 3.5% for AP, anterior, and posterior arthrodesis, respectively.

CONCLUSION

AP lumbar arthrodesis was associated with higher and increasing reimbursement (wRVUs/h) during the period 2010 to 2020. Reimbursement for anterior arthrodesis was relatively stable, while reimbursement for posterior arthrodesis decreased. The utilization of the combined AP approach relative to the other approaches increased significantly during the period of interest.

Practice Variation Research in Degenerative Lumbar Disc Surgery: A Literature Review on Design Characteristics and Outcomes

STUDY DESIGN

Literature review.

OBJECTIVE

To describe whether practice variation studies on surgery in patients with lumbar degenerative disc disease used adequate study methodology to identify unwarranted variation, and to inform quality improvement in clinical practice. Secondary aim was to describe whether variation changed over time.

METHODS

Literature databases were searched up to May 4^th, 2021. To define whether study design was appropriate to identify unwarranted variation, we extracted data on level of aggregation, study population, and case-mix correction. To define whether studies were appropriate to achieve quality improvement, data were extracted on outcomes, explanatory variables, description of scientific basis, and given recommendations. Spearman's rho was used to determine the association between the Extreme Quotient (EQ) and year of publication.

RESULTS

We identified 34 articles published between 1990 and 2020. Twenty-six articles (76%) defined the diagnosis. Prior surgery cases were excluded or adjusted for in 5 articles (15%). Twenty-three articles (68%) adjusted for case-mix. Variation in outcomes was analyzed in 7 articles (21%). Fourteen articles (41%) identified explanatory variables. Twenty-six articles (76%) described the evidence on effectiveness. Recommendations for clinical practice were given in 9 articles (26%). Extreme Quotients ranged between 1-fold and 15-fold variation and did not show a significant change over time (rho= -.33, P= .09).

CONCLUSIONS

Practice variation research on surgery in patients with degenerative disc disease showed important limitations to identify unwarranted variation and to achieve quality improvement by public reporting. Despite the availability of new evidence, we could not observe a significant decrease in variation over time.

Performance of Artificial Intelligence-Based Algorithms to Predict Prolonged Length of Stay after Lumbar Decompression Surgery

Background: Decompression of the lumbar spine is one of the most common procedures performed in spine surgery. Hospital length of stay (LOS) is a clinically relevant metric used to assess surgical success, patient outcomes, and socioeconomic impact. This study aimed to investigate a variety of machine learning and deep learning algorithms to reliably predict whether a patient undergoing decompression of lumbar spinal stenosis will experience a prolonged LOS. Methods: Patients undergoing treatment for lumbar spinal stenosis with microsurgical and full-endoscopic decompression were selected within this retrospective monocentric cohort study. Prolonged LOS was defined as an LOS greater than or equal to the 75th percentile of the cohort (normal versus prolonged stay; binary classification task). Unsupervised learning with K-means clustering was used to find clusters in the data. Hospital stay classes were predicted with logistic regression, RandomForest classifier, stochastic gradient descent (SGD) classifier, K-nearest neighbors, Decision Tree classifier, Gaussian Naive Bayes (GaussianNB), support vector machines (SVM), a custom-made convolutional neural network (CNN), multilayer perceptron artificial neural network (MLP), and radial basis function neural network (RBNN) in Python. Prediction accuracy and area under the curve (AUC) were calculated. Feature importance analysis was utilized to find the most important predictors. Further, we developed a decision tree based on the Chi-square automatic interaction detection (CHAID) algorithm to investigate cut-offs of predictors for clinical decision-making. Results: 236 patients and 14 feature variables were included. K-means clustering separated data into two clusters distinguishing the data into two patient risk characteristic groups. The algorithms reached AUCs between 67.5% and 87.3% for the classification of LOS classes. Feature importance analysis of deep learning algorithms indicated that operation time was the most important feature in predicting LOS. A decision tree based on CHAID could predict 84.7% of the cases. Conclusions: Machine learning and deep learning algorithms can predict whether patients will experience an increased LOS following lumbar decompression surgery. Therefore, medical resources can be more appropriately allocated to patients who are at risk of prolonged LOS.

Is Discretionary Care Associated with Safety Among Medicare Beneficiaries Undergoing Spine Surgery?

BACKGROUND

Spine surgery and its corresponding costs have increased in recent years and are variable across geographic regions. Discretionary care is the component of spending variation that is independent of illness severity, age, and regional pricing. It is unknown whether greater discretionary care is associated with improved safety for patients undergoing spine surgery, as we would expect from value-based health care.

METHODS

We conducted an analysis of 5 spine surgery cohorts based on Medicare claims from 2013 to 2017. Patients were grouped into quintiles based on the Dartmouth Atlas End-of-Life Inpatient Care Index (EOL), reflecting regional spending variation attributed to discretionary care. Multivariable regression examined the association between discretionary care and safety measures while controlling for age, sex, race, comorbidity, and hospital features.

RESULTS

We observed a threefold to fourfold variation in 90-day episode-of-care cost across regions, depending on the cohort. Spine-specific spending was correlated with EOL quintile, confirming that spending variation is due more to discretionary care than it is to pricing, age, or illness severity. Greater spending across EOL quintiles was not associated with improved safety, and, in fact, was associated with poorer safety in some cohorts. For example, all-cause readmission was greater in the high-spending EOL quintile relative to the low-spending EOL quintile among the "fusion, except cervical" cohort (14.2% vs. 13.1%; OR = 1.10; 95% CI = 1.05 to 1.20), the "complex fusion" cohort (28.0% vs. 25.4%; OR = 1.15; 95% CI = 1.01 to 1.30), and the "cervical fusion" cohort (15.0% vs. 13.6%; OR = 1.12; 95% CI = 1.05 to 1.20).

CONCLUSIONS

Wide variation in spending was not explained by differences in illness severity, age, or pricing, and increased discretionary care did not enhance safety. These findings point to inefficient use of health-care resources, a potential focus of reform.

LEVEL OF EVIDENCE

Economic and Decision Analysis Level IV. See Instructions for Authors for a complete description of levels of evidence.

Updated external validation of the SORG machine learning algorithms for prediction of ninety-day and one-year mortality after surgery for spinal metastasis

BACKGROUND CONTEXT

Surgical decompression and stabilization in the setting of spinal metastasis is performed to relieve pain and preserve functional status. These potential benefits must be weighed against the risks of perioperative morbidity and mortality. Accurate prediction of a patient's postoperative survival is a crucial component of patient counseling.

PURPOSE

To externally validate the SORG machine learning algorithms for prediction of 90-day and 1-year mortality after surgery for spinal metastasis.

STUDY DESIGN/SETTING

Retrospective, cohort study PATIENT SAMPLE: Patients 18 years or older at a tertiary care medical center treated surgically for spinal metastasis OUTCOME MEASURES: Mortality within 90 days of surgery, mortality within 1 year of surgery METHODS: This is a retrospective cohort study of 298 adult patients at a tertiary care medical center treated surgically for spinal metastasis between 2004 and 2020. Baseline characteristics of the validation cohort were compared to the derivation cohort for the SORG algorithms. The following metrics were used to assess the performance of the algorithms: discrimination, calibration, overall model performance, and decision curve analysis.

RESULTS

Sixty-one patients died within 90 days of surgery and 133 died within 1 year of surgery. The validation cohort differed significantly from the derivation cohort. The SORG algorithms for 90-day mortality and 1-year mortality performed excellently with respect to discrimination; the algorithm for 1-year mortality was well-calibrated. At both postoperative time points, the SORG algorithms showed greater net benefit than the default strategies of changing management for no patients or for all patients.

CONCLUSIONS

With an independent, contemporary, and geographically distinct population, we report successful external validation of SORG algorithms for preoperative risk prediction of 90-day and 1-year mortality after surgery for spinal metastasis. By providing accurate prediction of intermediate and long-term mortality risk, these externally validated algorithms may inform shared decision-making with patients in determining management of spinal metastatic disease.

From clinic to hypothesis, an innovative operation for the treatment of lumbar spinal stenosis in a minimal invasive way

Concerning the damage to back muscles and posterior ligament complex (PLC) by posterior open approach for lumbar spinal stenosis (LSS), the oblique lateral intervertebral fusion (OLIF) is pretty popular nowadays. However, oblique lateral approach has obvious drawbacks, which are limited vision and operative scope for achieving spinal canal decompression. Herein, we present a hypothesis that lumbar canal decompression can be well achieved by OLIF combined with spinal endoscope operative system. Nerval decompression and spinal reconstruction are achieved in a minimal invasive way, which may play an instructive role for the treatment of serious LSS.

Predicting Patient-Centered Outcomes from Spine Surgery Using Risk Assessment Tools: a Systematic Review

PURPOSE OF REVIEW

The purpose of this systematic review is to evaluate the current literature in patients undergoing spine surgery in the cervical, thoracic, and lumbar spine to determine the available risk assessment tools to predict the patient-centered outcomes of pain, disability, physical function, quality of life, psychological disposition, and return to work after surgery.

RECENT FINDINGS

Risk assessment tools can assist surgeons and other healthcare providers in identifying the benefit-risk ratio of surgical candidates. These tools gather demographic, medical history, and other pertinent patient-reported measures to calculate a probability utilizing regression or machine learning statistical foundations. Currently, much is still unknown about the use of these tools to predict quality of life, disability, and other factors following spine surgery. A systematic review was conducted using PRISMA guidelines that identified risk assessment tools that utilized patient-reported outcome measures as part of the calculation. From 8128 identified studies, 13 articles met inclusion criteria and were accepted into this review. The range of c-index values reported in the studies was between 0.63 and 0.84, indicating fair to excellent model performance. Post-surgical patient-reported outcomes were identified in the following categories (n = total number of predictive models): return to work (n = 3), pain (n = 9), physical functioning and disability (n = 5), quality of life (QOL) (n = 6), and psychosocial disposition (n = 2). Our review has synthesized the available evidence on risk assessment tools for predicting patient-centered outcomes in patients undergoing spine surgery and described their findings and clinical utility.

Cortical bone trajectory instrumentation provides favorable perioperative outcomes compared to pedicle screws for single-level lumbar spinal stenosis and degenerative spondylolisthesis

Objective

To compare perioperative outcomes between cortical bone trajectory (CBT) instrumentation with pedicle screws (PS) in patients undergoing laminectomy and posterolateral fusion for single-level lumbar spinal stenosis, and degenerative grade I spondylolisthesis.

Methods

A consecutive series of 91 patients from a single institution between January 2017 and July 2019 were retrospectively reviewed.

Results

Patients in CBT group had significantly shorter operative time, lower blood loss and shorter length of stay.

Conclusion

CBT instrumentation demonstrated favorable perioperative outcomes that may enhance the overall value in patients undergoing laminectomy and posterolateral fusion for single-level lumbar spinal stenosis, and degenerative grade I spondylolisthesis.

Regional Variance in Disability and Quality-of-Life Outcomes After Surgery for Grade I Degenerative Lumbar Spondylolisthesis: A Quality Outcomes Database Analysis

OBJECTIVE

Regional differences in outcomes after spine surgery are poorly understood. We assessed disability and quality-of-life outcomes by geographic region in the United States using the NeuroPoint Alliance Quality Outcomes Database.

METHODS

We queried the prospective Quality Outcomes Database patient registry to identify patients who underwent elective 1- or 2-level lumbar surgery for grade I degenerative spondylolisthesis from July 2014 through June 2016. Primary outcome measures included Oswestry Disability Index (ODI) and EuroQOL-5D (EQ-5D) reported at 24 months postoperatively. Differences in EQ-5D and ODI were compared across geographic regions of the United States (Northeast, Midwest, South, West).

RESULTS

We identified 608 patients from 12 centers who underwent surgery. Of these, 517 (85.0%) had ODI data and 492 (80.9%) had EQ-5D data at 24 months. Southern states had the largest representation (304 patients; 5 centers), followed by Northeastern (114 patients; 3 centers), Midwestern (96 patients; 2 centers), and Western (94 patients; 2 centers) states. Baseline ODI scores were significantly different among regions, with the South having the greatest baseline disability burden (Northeast: 40.9 ± 16.9, South: 51.2 ± 15.8, Midwest: 40.9 ± 17.8, West: 45.0 ± 17.1, P < 0.001). The change in ODI at 24 months postoperatively was significantly different among regions, with the South showing the greatest ODI improvement (Northeast: -21.1 ± 18.2, South: -26.5 ± 20.2, Midwest: -18.2 ± 22.9, West: -21.7 ± 19.6, P < 0.001). All regions had ≥60% achievement of the minimum clinically important difference in ODI at 24 months postoperatively. No regional differences were observed for EQ-5D.

CONCLUSION

Significant regional variation exists for disability outcomes, but not quality of life, at 24 months after spinal surgery for grade I degenerative spondylolisthesis.

SpineCloud: image analytics for predictive modeling of spine surgery outcomes

Purpose: Data-intensive modeling could provide insight on the broad variability in outcomes in spine surgery. Previous studies were limited to analysis of demographic and clinical characteristics. We report an analytic framework called "SpineCloud" that incorporates quantitative features extracted from perioperative images to predict spine surgery outcome. Approach: A retrospective study was conducted in which patient demographics, imaging, and outcome data were collected. Image features were automatically computed from perioperative CT. Postoperative 3- and 12-month functional and pain outcomes were analyzed in terms of improvement relative to the preoperative state. A boosted decision tree classifier was trained to predict outcome using demographic and image features as predictor variables. Predictions were computed based on SpineCloud and conventional demographic models, and features associated with poor outcome were identified from weighting terms evident in the boosted tree. Results: Neither approach was predictive of 3- or 12-month outcomes based on preoperative data alone in the current, preliminary study. However, SpineCloud predictions incorporating image features obtained during and immediately following surgery (i.e., intraoperative and immediate postoperative images) exhibited significant improvement in area under the receiver operating characteristic (AUC): AUC = 0.72 ( CI 95 = 0.59 to 0.83) at 3 months and AUC = 0.69 ( CI 95 = 0.55 to 0.82) at 12 months. Conclusions: Predictive modeling of lumbar spine surgery outcomes was improved by incorporation of image-based features compared to analysis based on conventional demographic data. The SpineCloud framework could improve understanding of factors underlying outcome variability and warrants further investigation and validation in a larger patient cohort.