Anatomic Parameters for Diagnosing Congenital Lumbar Stenosis Based on Computed Tomography of 1,000 Patients.

INTRODUCTION: Quantitative parameters for diagnosis of congenital lumbar stenosis (CLS) have yet to be universally accepted. This study establishes parameters for CLS using CT, assessing the influences of patient sex, race, ethnicity, and anthropometric characteristics. METHODS: Interpedicular distance (IPD), pedicle length, canal diameter, and canal area were measured using 1,000 patients between 18 and 35 years of age who were without spinal pathology. RESULTS: Irrespective of disk level, threshold values for CLS were 16.1 mm for IPD, 3.9 mm for pedicle length, 11.5 mm for canal diameter, and 142.5 mm2 for canal area. Notable differences based on patient sex were observed, with men demonstrating larger CLS threshold values with respect to IPD and canal area across all vertebral levels from L1 to L5. Based on patient anthropometric factors, no strong or moderate associations were observed between any spinal measurement and patient height, weight, or body mass index across all levels from L1 to L5. However, notable differences were observed based on patient race and ethnicity from L1 to L5. Asian patients demonstrated the largest pedicle lengths, followed by White, Hispanic, and Black patients in descending order. White patients demonstrated the largest IPD, canal AP diameter, and canal area, followed by Asian, Hispanic, and Black patients in descending order. Black patients demonstrated the smallest values across all anatomic measurements relative to Asian, White, and Hispanic patients. CONCLUSION: This study reports 25,000 measurements of lumbar central canal dimensions to establish quantitative thresholds for the diagnosis of CLS. Although not influenced by patient height, weight, or body mass index as one might intuit, canal dimensions were influenced by patient sex, race, and ethnicity. These findings may help explain differences in predisposition or prevalence of lumbar nerve root compression among patients of different races, which can be important when considering rates of surgery and access to care.

Social determinants of health and disparities in spine surgery: a 10-year analysis of 8,565 cases using ensemble machine learning and multilayer perceptron.

BACKGROUND CONTEXT: The influence of SDOH on spine surgery is poorly understood. Historically, researchers commonly focused on the isolated influences of race, insurance status, or income on healthcare outcomes. However, analysis of SDOH is becoming increasingly more nuanced as viewing social factors in aggregate rather than individually may offer more precise estimates of the impact of SDOH on healthcare delivery. PURPOSE: The aim of this study was to evaluate the effects of patient social history on length of stay (LOS) and readmission within 90 days following spine surgery using ensemble machine learning and multilayer perceptron. STUDY DESIGN: Retrospective chart review. PATIENT SAMPLE: 8,565 elective and emergency spine surgery cases performed from 2013 to 2023 using our institution's database of longitudinally collected electronic medical record information. OUTCOMES MEASURES: Patient LOS, discharge disposition, and rate of 90-day readmission. METHODS: Ensemble machine learning and multilayer perceptron were employed to predict LOS and readmission within 90 days following spine surgery. All other subsequent statistical analysis was performed using SPSS version 28. To further assess correlations among variables, Pearson's correlation tests and multivariate linear regression models were constructed. Independent sample t-tests, paired sample t-tests, one-way analysis of variance (ANOVA) with post-hoc Bonferroni and Tukey corrections, and Pearson's chi-squared test were applied where appropriate for analysis of continuous and categorical variables. RESULTS: Black patients demonstrated a greater LOS compared to white patients, but race and ethnicity were not significantly associated with 90-day readmission rates. Insured patients had a shorter LOS and lower readmission rates compared to non-insured patients, as did privately insured patients compared to publicly insured patients. Patients discharged home had lower LOS and lower readmission rates, compared to patients discharged to other facilities. Marriage decreased both LOS and readmission rates, underweight patients showcased increased LOS and readmission rates, and religion was shown to impact LOS and readmission rates. When utilizing patient social history, lab values, and medical history, machine learning determined the top 5 most-important variables for prediction of LOS -along with their respective feature importances-to be insurance status (0.166), religion (0.100), ICU status (0.093), antibiotic use (0.061), and case status: elective or urgent (0.055). The top 5 most-important variables for prediction of 90-day readmission-along with their respective feature importances-were insurance status (0.177), religion (0.123), discharge location (0.096), emergency case status (0.064), and history of diabetes (0.041). CONCLUSIONS: This study highlights that SDOH is influential in determining patient length of stay, discharge disposition, and likelihood of readmission following spine surgery. Machine learning was utilized to accurately predict LOS and 90-day readmission with patient medical history, lab values, and social history, as well as social history alone.

Risk of adjacent level fracture after percutaneous vertebroplasty and kyphoplasty vs natural history for the management of osteoporotic vertebral compression fractures: a network meta-analysis of randomized controlled trials.

OBJECTIVES: Percutaneous vertebroplasty and kyphoplasty are common interventions for osteoporotic vertebral compression fractures. However, there is concern about an increased risk of adjacent-level fractures after treatment. This study aimed to compare the risk of adjacent-level fractures after vertebroplasty and kyphoplasty with the natural history after osteoporotic vertebral compression fractures. MATERIALS AND METHODS: A network meta-analysis of randomized controlled trials (RCTs) was conducted to evaluate the risk of adjacent-level fractures after vertebroplasty and kyphoplasty compared to the natural history after osteoporotic vertebral compression fractures. Frequentist network meta-analysis was conducted using the "netmeta" package, and heterogeneity was assessed using Q statistics. The pooled risk ratio (RR) and 95% confidence intervals (CI) were calculated using random effects. RESULTS: Twenty-three RCTs with a total of 2838 patients were included in the analysis. The network meta-analysis showed comparable risks of adjacent-level fractures between vertebroplasty, kyphoplasty, and natural history after osteoporotic vertebral compression fractures with a mean follow-up of 21.2 (range: 3-49.4 months). The pooled RR for adjacent-level fractures after kyphoplasty compared to natural history was 1.35 (95% CI, 0.78-2.34, p = 0.23) and for vertebroplasty compared to natural history was 1.16 (95% CI, 0.62-2.14) p = 0.51. The risk of bias assessment showed a low to moderate risk of bias among included RCTs. CONCLUSION: There was no difference in the risk of adjacent-level fractures after vertebroplasty and kyphoplasty compared to natural history after osteoporotic vertebral compression fractures. The inclusion of a large patient number and network meta-analysis of RCTs serve evidence-based clinical practice. CLINICAL RELEVANCE STATEMENT: The risk of adjacent-level fracture following percutaneous vertebroplasty or kyphoplasty is similar to that observed in the natural history after osteoporotic vertebral compression fractures. KEY POINTS: RCTs have examined the risk of adjacent-level fracture after intervention for osteoporotic vertebral compression fractures. There was no difference between vertebroplasty and kyphoplasty patients compared to the natural disease history for adjacent compression fractures. This is strong evidence that interventional treatments for these fractures do not increase the risk of adjacent fractures.

Morphometric analysis of cervical neuroforaminal dimensions from C2-T1 using computed tomography of 1,000 patients.

BACKGROUND: Race and sex differences are not consistently reported in the literature. Fundamentally, anatomical differences of cervical neuroforaminal dimensions (CNFD) amongst these groups would be important to know. PURPOSE: To establish normative radiographic morphometric measurements of CNFD and uncover the influence of patient sex, race, and ethnicity while also considering anthropometric characteristics. STUDY DESIGN: Retrospective radiographic morphometric study. PATIENT SAMPLE: A total of 1,000 patients between 18 and 35 years of age who were free of spinal pathology. OUTCOME MEASURES: Foraminal height, axial width, and area of cervical neural foramen. METHODS: Cervical CTs were reviewed to measure CNFD, defined as follows: foraminal height, axial width, and area. Statistical analyses were performed to assess associations between CNFD, and patient height, weight, sex, race, and ethnicity. RESULTS: CNFD measurements followed a bimodal distribution pattern moving caudally from C2-T1. Irrespective of disc level, cervical CNFD were as follows: left and right widths of 6.6±1.5 and 6.6±1.5 mm, heights of 9.4±2.4 and 9.4±3.2 mm, and areas of 60.0±19.5 and 60.6±20.7 mm2. Left and right foraminal width were highest at C2-C3 and lowest at C3-C4. Left and right foraminal height were highest at C7-T1 and C6-C7, respectively and lowest at C3-C4. Left and right foraminal areas were highest at C2-C3 and lowest at C3-C4. Significant differences were observed for all CNFD measurements across disc levels. CNFD did not vary based on laterality. Significant CNFD differences were observed with respect to patient sex, race, and ethnicity. Male height and area were larger compared to females. In contrast, female foraminal width was larger compared to males. The Asian cohort demonstrated the largest foraminal widths. White and Hispanic patients demonstrated the largest foraminal heights and areas. Black patients demonstrated the smallest foraminal widths, heights, and areas. Patient height and weight were only weakly correlated with CNFD measurements across all levels from C2-T1. CONCLUSIONS: This study describes 36,000 normative measurements of 12,000 foramina from C2-T1. CNFD measurements vary based on disc level, but not laterality. Contrasting left- versus right-sided neuroforamina of the same level may aid in determining the presence of unilateral stenosis. Patient sex, race, and ethnicity are associated with CNFD, while patient anthropometric factors are weakly correlated with CNFD.

Assessing the variation and drivers of cost in 1-level lumbar fusion: a time-driven activity-based costing analysis.

BACKGROUND CONTEXT: As value-based health care arrangements gain traction in spine care, understanding the true cost of care becomes critical. Historically, inaccurate cost proxies have been used, including negotiated reimbursement rates or list prices. However, time-driven activity-based costing (TDABC) allows for a more accurate cost assessment, including a better understanding of the primary drivers of cost in 1-level lumbar fusion. PURPOSE: To determine the variation of total hospital cost, differences in characteristics between high-cost and nonhigh-cost patients, and to identify the primary drivers of total hospital cost in a sample of patients undergoing 1-level lumbar fusion. STUDY DESIGN/SETTING: Retrospective, multicenter (one academic medical center, one community-based hospital), observational study. PATIENT SAMPLE: A total of 383 patients undergoing elective 1-level lumbar fusion for degenerative spine conditions between November 2, 2021 and December 2, 2022. OUTCOME MEASURES: Total hospital cost of care (normalized); preoperative, intraoperative, and postoperative cost of care (normalized); ratio of most to least expensive 1-level lumbar fusion. METHODS: Patients undergoing a 1-level lumbar fusion between November 2, 2021 and December 2, 2022 were identified at two hospitals (one quaternary referral academic medical center and one community-based hospital) within our health system. TDABC was used to calculate total hospital cost, which was also broken up into: pre-, intra-, and postoperative timeframes. Operating surgeon and patient characteristics were also collected and compared between high- and nonhigh-cost patients. The correlation of surgical time and cost was determined. Multivariable linear regression was used to determine factors associated with total hospital cost. RESULTS: The most expensive 1-level lumbar fusion was 6.8x more expensive than the least expensive 1-level lumbar fusion, with the intraoperative period accounting for 88% of total cost. On average. the implant cost accounted for 30% of the total, but across the patient sample, the implant cost accounted for a range of 6% to 44% of the total cost. High-cost patients were younger (55 years [SD: 13 years] vs 63 years [SD: 13 years], p=.0002), more likely to have commercial health insurance (24 out of 38 (63%) vs 181 out of 345 (52%), p=.003). There was a poor correlation between time of surgery (ie, incision to close) and total overall cost (ρ: .26, p<.0001). Increase age (RC: -0.003 [95% CI: -0.006 to -0.000007], p=.049) was associated with decreased cost. Surgery by certain surgeons was associated with decreased total cost when accounting for other factors (p<.05). CONCLUSIONS: A large variation exists in the total hospital cost for patients undergoing 1-level lumbar fusion, which is primarily driven by surgeon-level decisions and preferences (eg, implant and technology use). Also, being a "fast" surgeon intraoperatively does not mean your total cost is meaningfully lower. As efforts continue to optimize patient value through ensuring appropriate clinical outcomes while also reducing cost, spine surgeons must use this knowledge to lead, or at least be active participants in, any discussions that could impact patient care.

Using advanced imaging to measure bone density, compression fracture risk, and risk for construct failure after spine surgery.

Low bone mineral density (BMD) can predispose to vertebral body compression fractures and postoperative instrumentation failure. DEXA is considered the gold standard for measurement of BMD, however it is not obtained for all spine surgery patients preoperatively. There is a growing body of evidence suggesting that more routinely acquired spine imaging studies such as computed tomography (CT) and magnetic resonance imaging (MRI) can be opportunistically used to measure BMD. Here we review available studies that assess the validity of opportunistic screening with CT-derived Hounsfield Units (HU) and MRI-derived vertebral vone quality (VBQ) to measure BMD of the spine as well the utility of these measures in predicting postoperative outcomes. Additionally, we provide screening thresholds based on HU and VBQ for prediction of osteopenia/ osteoporosis and postoperative outcomes such as cage subsidence, screw loosening, proximal junctional kyphosis, and implant failure.

Prediction of In-Hospital Mortality Following Vertebral Fracture Fixation in Patients With Ankylosing Spondylitis or Diffuse Idiopathic Skeletal Hyperostosis: Machine Learning Analysis.

BACKGROUND: Ankylosing spondylitis (AS) and diffuse idiopathic skeletal hyperostosis (DISH) are distinct pathological entities that similarly increase the risk of vertebral fractures. Such fractures can be clinically devastating and frequently portend significant neurological injury, thus making their prevention a critical focus. Of particular significance, spinal fractures in patients with AS or DISH carry a considerable risk of mortality, with reports on 1-year injury-related deaths ranging from 24% to 33%. As such, the purpose of this study was to conduct machine learning (ML) analysis to predict postoperative mortality in patients with AS or DISH using the Nationwide Inpatient Sample Healthcare Cost and Utilization Project (HCUP-NIS) database. METHODS: HCUP-NIS was queried to identify adult patients carrying a diagnosis of AS or DISH who were admitted for spinal fractures and underwent subsequent fusion or corpectomy between 2016 and 2018. Predictions of in-hospital mortality in this cohort were then generated by three independent ML algorithms. RESULTS: An in-hospital mortality rate of 5.40% was observed in our selected population, including a rate of 6.35% in patients with AS, 2.81% in patients with DISH, and 8.33% in patients with both diagnoses. Increasing age, hypertension with end-organ complications, spinal cord injury, and cervical spinal fractures each carried considerable predictive importance across the algorithms utilized in our analysis. Predictions were generated with an average area under the curve of 0.758. CONCLUSIONS: This study's application of ML algorithms to predict in-hospital mortality among patients with AS or DISH identified a number of clinical risk factors relevant to this outcome. CLINICAL RELEVANCE: These findings may serve to provide physicians with an awareness of risk factors for in-hospital mortality and, subsequently, guide management and shared decision-making among patients with AS or DISH.

An international consensus based on the Delphi method to define failure of medical treatment in pyogenic spinal infections.

BACKGROUND CONTEXT: Pyogenic spinal infections (PSIs) are severe conditions with high morbidity and mortality. If medical treatment fails, patients may require surgery, but there is no consensus regarding the definition of medical treatment failure. PURPOSE: To determine criteria for defining failure of medical treatment in PSI through an international consensus of experts. STUDY DESIGN: A two-round basic Delphi method study. SAMPLE: One hundred and fifty experts from 22 countries (authors or co-authors of clinical guidelines or indexed publications on the topic) were invited to participate; 33 answered both rounds defining the criteria. OUTCOME MEASURES: A scale of 1 to 9 (1: no relevance; 9: highly relevant) applied to each criterion. METHODS: We created an online survey with 10 criteria reported in the literature to define the failure of medical treatment in PSIs. We sent this survey via email to the experts. Agreement among the participants on relevant criteria (score ≥7) was determined. One month later, the second round of evaluations was sent. An extra criterion suggested by six responders in the first round was incorporated. The final version was reached with the criteria considered relevant and with high agreement. RESULTS: The consensus definition is: (1) There is an uncontrolled sepsis despite broad spectrum antibiotic treatment, and (2) There is an infection relapse, following a six-week period of antibiotics with clinical and laboratory improvement. CONCLUSIONS: Our definition of failure following nonsurgical treatment of PSI can offer a standardized approach to guide clinical decision-making. Furthermore, it has the potential to enhance scientific reporting within this field.

Accounting for age in prediction of discharge destination following elective lumbar fusion: a supervised machine learning approach.

BACKGROUND CONTEXT: The number of elective spinal fusion procedures performed each year continues to grow, making risk factors for post-operative complications following this procedure increasingly clinically relevant. Nonhome discharge (NHD) is of particular interest due to its associations with increased costs of care and rates of complications. Notably, increased age has been found to influence rates of NHD. PURPOSE: To identify aged-adjusted risk factors for nonhome discharge following elective lumbar fusion through the utilization of Machine Learning-generated predictions within stratified age groupings. STUDY DESIGN: Retrospective Database Study. PATIENT SAMPLE: The American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database years 2008 to 2018. OUTCOME MEASURES: Postoperative discharge destination. METHODS: ACS-NSQIP was queried to identify adult patients undergoing elective lumbar spinal fusion from 2008 to 2018. Patients were then stratified into the following age ranges: 30 to 44 years, 45 to 64 years, and ≥65 years. These groups were then analyzed by eight ML algorithms, each tasked with predicting post-operative discharge destination. RESULTS: Prediction of NHD was performed with average AUCs of 0.591, 0.681, and 0.693 for those aged 30 to 44, 45 to 64, and ≥65 years respectively. In patients aged 30 to 44, operative time (p<.001), African American/Black race (p=.003), female sex (p=.002), ASA class three designation (p=.002), and preoperative hematocrit (p=.002) were predictive of NHD. In ages 45 to 64, predictive variables included operative time, age, preoperative hematocrit, ASA class two or class three designation, insulin-dependent diabetes, female sex, BMI, and African American/Black race all with p<.001. In patients ≥65 years, operative time, adult spinal deformity, BMI, insulin-dependent diabetes, female sex, ASA class four designation, inpatient status, age, African American/Black race, and preoperative hematocrit were predictive of NHD with p<.001. Several variables were distinguished as predictive for only one age group including ASA Class two designation in ages 45 to 64 and adult spinal deformity, ASA class four designation, and inpatient status for patients ≥65 years. CONCLUSIONS: Application of ML algorithms to the ACS-NSQIP dataset identified a number of highly predictive and age-adjusted variables for NHD. As age is a risk factor for NHD following spinal fusion, our findings may be useful in both guiding perioperative decision-making and recognizing unique predictors of NHD among specific age groups.

Thoracolumbar Injury Classification Systems: The Importance of Concepts and Language in the Move Toward Standardization.

STUDY DESIGN: Narrative review. OBJECTIVE: To describe the evolution of acute traumatic thoracolumbar (TL) injury classification systems; to promote standardization of concepts and vocabulary with respect to TL injuries. SUMMARY OF BACKGROUND DATA: Over the past century, numerous TL classification systems have been proposed and implemented, each influenced by the thought, imaging modalities, and surgical techniques available at the time. While much progress has been made in our understanding and management of these injuries, concepts, and terms are often intermixed, leading to potential confusion and miscommunication. METHODS: We present a narrative review of the current state of the literature regarding classification systems for TL trauma. RESULTS: The evolution of TL classification systems has broadly been characterized by a transition away from descriptive categorizations of fracture patterns to schema incorporating morphology, stability, and neurological function. In addition to these features, more recent systems have demonstrated the importance of predictive/prognostic capability, reliability, validity, and generalizability. The Arbeitsgemeinschaft fur Osteosynthesenfragen Spine Thoracolumbar Injury Classification System/Thoracolumbar Arbeitsgemeinschaft fur Osteosynthesenfragen Spine Injury Score represents the most modern and recently updated system, retiring past concepts and terminology in favor of clear, internationally agreed upon descriptors. CONCLUSIONS: Advancements in our understanding of blunt TL trauma injuries have led to changes in management. Such advances are reflected in modern, dedicated classification systems. Over time, various key factors have been acknowledged and incorporated. In an effort to promote standardization of thought and language, past ideas and terminology should be retired.

External validation of a predictive algorithm for in-hospital and 90-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.

When the Physician Becomes the Patient: Considerations for Work, Life, and Leadership.

Most orthopaedic surgeons are unprepared for serious medical illnesses. In such cases, the unique work-related and personal considerations for orthopaedic surgeons affect their career, their practice partners, and their patients. Planning together as an orthopaedic business organization for such issues can provide a framework to better navigate these difficult situations. Understanding the considerations and stressors from the individual's perspective can help provide the appropriate level of support while maintaining privacy. Throughout these considerations, open communication regarding expectations and concerns and expressions of empathy are the cornerstones of dealing with physician illness. Being a physician-patient adds complexity to an already difficult and stressful profession. Further dialogue regarding the physician-patient experience can help increase awareness of this issue and allow organizations to create a structure to best manage this almost inevitable occurrence.

Does Nasal Screening for Methicillin-Resistant Staphylococcus aureus (MRSA) Prevent Deep Surgical Site Infections for Elective Cervical Spinal Fusion?

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: The objective of this study was to determine the relationship between nasal methicillin-resistant Staphylococcus aureus (MRSA) testing and surgical site infection (SSI) rates in the setting of primary posterior cervical instrumented spine surgery. SUMMARY OF BACKGROUND DATA: Preoperative MRSA screening and decolonization has demonstrated success for some orthopedic subspecialties in prevention of SSIs. Spine surgery, however, has seen varied results, potentially secondary to the anatomic and surgical heterogeneity of the patients included in prior studies. Given that prior research has demonstrated greater propensity for gram positive SSIs in the cervical spine, we sought to investigate if MRSA screening would be more impactful in the cervical spine. MATERIALS AND METHODS: Adult patients undergoing primary instrumented posterior cervical procedures from January 2015 to December 2019 were reviewed for MRSA testing <90 days before surgery, preoperative mupirocin, perioperative antibiotics, and SSI defined as operative incision and drainage (I&D) <90 days after surgery. Logistic regression modeling used SSI as the primary outcome, MRSA screening as primary predictor, and clinical and demographic factors as covariates. RESULTS: This study included 668 patients, of whom MRSA testing was performed in 212 patients (31.7%) and 6 (2.8%) were colonized with MRSA. Twelve patients (1.8%) underwent an I&D. On adjusted analysis, preoperative MRSA testing was not associated with postoperative I&D risk. Perioperative vancomycin similarly had no association with postoperative I&D risk. Notably, 6 patients (50%) grew methicillin sensitive Staphylococcus aureus from intraoperative cultures, with no cases of MRSA. CONCLUSIONS: There was no association between preoperative nasal MRSA screening and SSIs in primary posterior cervical instrumented procedures, nor was there any association between vancomycin or infection rate. Furthermore, there was a preponderance of gram positive infections but none caused by MRSA. Given these findings, the considerable cost and effort associated with MRSA testing in the setting of primary posterior cervical instrumentation may not be justified. Further research should investigate if higher-risk scenarios demonstrate greater utility of preoperative testing.

Magnetic Resonance Imaging Is Inadequate to Assess Cervical Sagittal Alignment Parameters.

STUDY DESIGN: Retrospective radiographic study. OBJECTIVE: To evaluate cervical sagittal alignment measurement reliability and correlation between upright radiographs and magnetic resonance imaging (MRI). SUMMARY OF BACKGROUND DATA: Cervical sagittal alignment (CSA) helps determine the surgical technique employed to treat cervical spondylotic myelopathy. Traditionally, upright lateral radiographs are used to measure CSA, but obtaining adequate imaging can be challenging. Utilizing MRI to evaluate sagittal parameters has been explored; however, the impact of positional change on these parameters has not been determined. METHODS: One hundred seventeen adult patients were identified who underwent laminoplasty or laminectomy and fusion for cervical spondylotic myelopathy from 2017 to 2019. Two clinicians independently measured the C2-C7 sagittal angle, C2-C7 sagittal vertical axis (SVA), and the T1 tilt. Interobserver and intraobserver reliability were assessed by intraclass correlation coefficient. RESULTS: Intraobserver and interobserver reliabilities were highly correlated, with correlations greater than 0.85 across all permutations; intraclass correlation coefficients were highest with MRI measurements. The C2-C7 sagittal angle was highly correlated between x-ray and MRI at 0.76 with no significant difference ( P =0.46). There was a weaker correlation with regard to C2-C7 SVA (0.48) and T1 tilt (0.62) with significant differences observed in the mean values between the 2 modalities ( P <0.01). CONCLUSIONS: The C2-C7 sagittal angle is highly correlated and not significantly different between upright x-ray and supine MRIs. However, cervical SVA and T1 tilt change with patient position. Since MRI does not accurately reflect the CSA in the upright position, upright lateral radiographs should be obtained to assess global sagittal alignment when planning a posterior-based cervical procedure.

Sociodemographic Factors Are Associated with Patient-Reported Outcome Measure Completion in Orthopaedic Surgery: An Analysis of Completion Rates and Determinants Among New Patients.

Patient-reported outcome measures (PROMs) and, specifically, the Patient-Reported Outcomes Measurement Information System (PROMIS), are increasingly utilized for clinical research, clinical care, and health-care policy. However, completion of these outcome measures can be inconsistent and challenging. We hypothesized that sociodemographic variables are associated with the completion of PROM questionnaires. The purposes of the present study were to calculate the completion rate of assigned PROM forms and to identify sociodemographic and other variables associated with completion to help guide improved collection efforts. Methods: All new orthopaedic patients at a single academic medical center were identified from 2016 to 2020. On the basis of subspecialty and presenting condition, patients were assigned certain PROMIS forms and legacy PROMs. Demographic and clinical information was abstracted from the electronic medical record. Bivariate analyses were performed to compare characteristics among those who completed assigned PROMs and those who did not. A multivariable logistic regression model was created to determine which variables were associated with successful completion of assigned PROMs. Results: Of the 219,891 new patients, 88,052 (40%) completed all assigned PROMs. Patients who did not activate their internet-based patient portal had a 62% increased likelihood of not completing assigned PROMs (odds ratio [OR], 1.62; 95% confidence interval [CI], 1.58 to 1.66; p < 0.001). Non-English-speaking patients had a 90% (OR, 1.90; 95% CI, 1.82 to 2.00; p < 0.001) increased likelihood of not completing assigned PROMs at presentation. Older patients (≥65 years of age) and patients of Black race had a 23% (OR, 1.23; 95% CI, 1.19 to 1.27; p < 0.001) and 24% (OR, 1.24; 95% CI, 1.19 to 1.30; p < 0.001) increased likelihood of not completing assigned PROMs, respectively. Conclusions: The rate of completion of PROMs varies according to sociodemographic variables. This variability could bias clinical outcomes research in orthopaedic surgery. The present study highlights the need to uniformly increase completion rates so that outcomes research incorporates truly representative cohorts of patients treated. Furthermore, the use of these PROMs to guide health-care policy decisions necessitates a representative patient distribution to avoid bias in the health-care system. Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Development and external validation of predictive algorithms for six-week mortality in spinal metastasis using 4,304 patients from five institutions.

BACKGROUND CONTEXT: Historically, spine surgeons used expected postoperative survival of 3-months to help select candidates for operative intervention in spinal metastasis. However, this cutoff has been challenged by the development of minimally invasive techniques, novel biologics, and advanced radiotherapy. Recent studies have suggested that a life expectancy of 6 weeks may be enough to achieve significant improvements in postoperative health-related quality of life. PURPOSE: The purpose of this study was to develop a model capable of predicting 6-week mortality in patients with spinal metastases treated with radiation or surgery. STUDY DESIGN/SETTING: A retrospective review was conducted at five large tertiary centers in the United States and Taiwan. PATIENT SAMPLE: The development cohort consisted of 3,001 patients undergoing radiotherapy and/or surgery for spinal metastases from one institution. The validation institutional cohort consisted of 1,303 patients from four independent, external institutions. OUTCOME MEASURES: The primary outcome was 6-week mortality. METHODS: Five models were considered to predict 6-week mortality, and the model with the best performance across discrimination, calibration, decision-curve analysis, and overall performance was integrated into an open access web-based application. RESULTS: The most important variables for prediction of 6-week mortality were albumin, primary tumor histology, absolute lymphocyte, three or more spine metastasis, and ECOG score. The elastic-net penalized logistic model was chosen as the best performing model with AUC 0.84 on evaluation in the independent testing set. On external validation in the 1,303 patients from the four independent institutions, the model retained good discriminative ability with an area under the curve of 0.81. The model is available here: https://sorg-apps.shinyapps.io/spinemetssurvival/. CONCLUSIONS: While this study does not advocate for the use of a 6-week life expectancy as criteria for considering operative management, the algorithm developed and externally validated in this study may be helpful for preoperative planning, multidisciplinary management, and shared decision-making in spinal metastasis patients with shorter life expectancy.

What Is the Clinical Benefit of Common Orthopaedic Procedures as Assessed by the PROMIS Versus Other Validated Outcomes Tools?

BACKGROUND: Patient-reported outcome measures (PROMs), including the Patient-reported Outcomes Measurement Information System (PROMIS), are increasingly used to measure healthcare value. The minimum clinically important difference (MCID) is a metric that helps clinicians determine whether a statistically detectable improvement in a PROM after surgical care is likely to be large enough to be important to a patient or to justify an intervention that carries risk and cost. There are two major categories of MCID calculation methods, anchor-based and distribution-based. This variability, coupled with heterogeneous surgical cohorts used for existing MCID values, limits their application to clinical care. QUESTIONS/PURPOSES: In our study, we sought (1) to determine MCID thresholds and attainment percentages for PROMIS after common orthopaedic procedures using distribution-based methods, (2) to use anchor-based MCID values from published studies as a comparison, and (3) to compare MCID attainment percentages using PROMIS scores to other validated outcomes tools such as the Hip Disability and Osteoarthritis Outcome Score (HOOS) and Knee Disability and Osteoarthritis Outcome Score (KOOS). METHODS: This was a retrospective study at two academic medical centers and three community hospitals. The inclusion criteria for this study were patients who were age 18 years or older and who underwent elective THA for osteoarthritis, TKA for osteoarthritis, one-level posterior lumbar fusion for lumbar spinal stenosis or spondylolisthesis, anatomic total shoulder arthroplasty or reverse total shoulder arthroplasty for glenohumeral arthritis or rotator cuff arthropathy, arthroscopic anterior cruciate ligament reconstruction, arthroscopic partial meniscectomy, or arthroscopic rotator cuff repair. This yielded 14,003 patients. Patients undergoing revision operations or surgery for nondegenerative pathologies and patients without preoperative PROMs assessments were excluded, leaving 9925 patients who completed preoperative PROMIS assessments and 9478 who completed other preoperative validated outcomes tools (HOOS, KOOS, numerical rating scale for leg pain, numerical rating scale for back pain, and QuickDASH). Approximately 66% (6529 of 9925) of patients had postoperative PROMIS scores (Physical Function, Mental Health, Pain Intensity, Pain Interference, and Upper Extremity) and were included for analysis. PROMIS scores are population normalized with a mean score of 50 ± 10, with most scores falling between 30 to 70. Approximately 74% (7007 of 9478) of patients had postoperative historical assessment scores and were included for analysis. The proportion who reached the MCID was calculated for each procedure cohort at 6 months of follow-up using distribution-based MCID methods, which included a fraction of the SD (1/2 or 1/3 SD) and minimum detectable change (MDC) using statistical significance (such as the MDC 90 from p < 0.1). Previously published anchor-based MCID thresholds from similar procedure cohorts and analogous PROMs were used to calculate the proportion reaching MCID. RESULTS: Within a given distribution-based method, MCID thresholds for PROMIS assessments were similar across multiple procedures. The MCID threshold ranged between 3.4 and 4.5 points across all procedures using the 1/2 SD method. Except for meniscectomy (3.5 points), the anchor-based PROMIS MCID thresholds (range 4.5 to 8.1 points) were higher than the SD distribution-based MCID values (2.3 to 4.5 points). The difference in MCID thresholds based on the calculation method led to a similar trend in MCID attainment. Using THA as an example, MCID attainment using PROMIS was achieved by 76% of patients using an anchor-based threshold of 7.9 points. However, 82% of THA patients attained MCID using the MDC 95 method (6.1 points), and 88% reached MCID using the 1/2 SD method (3.9 points). Using the HOOS metric (scaled from 0 to 100), 86% of THA patients reached the anchor-based MCID threshold (17.5 points). However, 91% of THA patients attained the MCID using the MDC 90 method (12.5 points), and 93% reached MCID using the 1/2 SD method (8.4 points). In general, the proportion of patients reaching MCID was lower for PROMIS than for other validated outcomes tools; for example, with the 1/2 SD method, 72% of patients who underwent arthroscopic partial meniscectomy reached the MCID on PROMIS Physical Function compared with 86% on KOOS. CONCLUSION: MCID calculations can provide clinical correlation for PROM scores interpretation. The PROMIS form is increasingly used because of its generalizability across diagnoses. However, we found lower proportions of MCID attainment using PROMIS scores compared with historical PROMs. By using historical proportions of attainment on common orthopaedic procedures and a spectrum of MCID calculation techniques, the PROMIS MCID benchmarks are realizable for common orthopaedic procedures. For clinical practices that routinely collect PROMIS scores in the clinical setting, these results can be used by individual surgeons to evaluate personal practice trends and by healthcare systems to quantify whether clinical care initiatives result in meaningful differences. Furthermore, these MCID thresholds can be used by researchers conducting retrospective outcomes research with PROMIS. LEVEL OF EVIDENCE: Level III, therapeutic study.

Practice Variation Within a Single Institution in Management of Degenerative Spondylolisthesis.

STUDY DESIGN: This was a retrospective cohort study. OBJECTIVE: The objective of this study was to assess variation in care for degenerative spondylolisthesis (DS) among surgeons at the same institution, to establish diagnostic and therapeutic variables contributing to this variation, and to determine whether variation in care changed over time. SUMMARY OF BACKGROUND DATA: Like other degenerative spinal disorders, DS is prone to practice variation due to the wide array of treatment options. Focusing on a single institution can identify more individualized drivers of practice variation by omitting geographic variability of demographics and socioeconomic factors. MATERIALS AND METHODS: We collected number of office visits, imaging procedures, injections, electromyography (EMG), and surgical procedures within 1 year after diagnosis. Multivariable logistic regression was used to determine predictors of surgery. The coefficient of variation (CV) was calculated to compare the variation in practice over time. RESULTS: Patients had a mean 2.5 (±0.6) visits, 1.8 (±0.7) imaging procedures, and 0.16 (±0.09) injections in the first year after diagnosis. Thirty-six percent (1937/5091) of patients had physical therapy in the 3 months after diagnosis. CV was highest for EMG (95%) and lowest for office visits (22%). An additional spinal diagnosis [odds ratio (OR)=3.99, P <0.001], visiting a neurosurgery clinic (OR=1.81, P =0.016), and diagnosis post-2007 (OR=1.21, P =0.010) were independently associated with increased surgery rates. The CVs for all variables decreased after 2007, with the largest decrease seen for EMG (132% vs. 56%). CONCLUSIONS: While there is variation in the management of patients diagnosed with DS between surgeons of a single institution, this variation seems to have gone down in recent years. All practice variables showed diminished variation. The largest variation and subsequent decrease of variation was seen in the use of EMG. Despite the smaller amount of variation, the rate of surgery has gone up since 2007.