Opportunistic CT for Prediction of Adverse Postoperative Events in Patients with Spinal Metastases

The purpose of this study was to assess the value of body composition measures obtained from opportunistic abdominal computed tomography (CT) in order to predict hospital length of stay (LOS), 30-day postoperative complications, and reoperations in patients undergoing surgery for spinal metastases. 196 patients underwent CT of the abdomen within three months of surgery for spinal metastases. Automated body composition segmentation and quantifications of the cross-sectional areas (CSA) of abdominal visceral and subcutaneous adipose tissue and abdominal skeletal muscle was performed. From this, 31% (61) of patients had postoperative complications within 30 days, and 16% (31) of patients underwent reoperation. Lower muscle CSA was associated with increased postoperative complications within 30 days (OR [95% CI] = 0.99 [0.98-0.99], p = 0.03). Through multivariate analysis, it was found that lower muscle CSA was also associated with an increased postoperative complication rate after controlling for the albumin, ASIA score, previous systemic therapy, and thoracic metastases (OR [95% CI] = 0.99 [0.98-0.99], p = 0.047). LOS and reoperations were not associated with any body composition measures. Low muscle mass may serve as a biomarker for the prediction of complications in patients with spinal metastases. The routine assessment of muscle mass on opportunistic CTs may help to predict outcomes in these patients.

Are Commonly Used Geographically Based Social Determinant of Health Indices in Orthopaedic Surgery Research Correlated With Each Other and With PROMIS Global-10 Physical and Mental Health Scores?

BACKGROUND

Geographically based social determinants of health (SDoH) measures are useful in research and policy aimed at addressing health disparities. In the United States, the Area Deprivation Index (ADI), Neighborhood Stress Score (NSS), and Social Vulnerability Index (SVI) are frequently used, but often without a clear reason as to why one is chosen over another. There is limited evidence about how strongly correlated these geographically based SDoH measures are with one another. Further, there is a paucity of research examining their relationship with patient-reported outcome measures (PROMs) in orthopaedic patients. Such insights are important in order to determine whether comparisons of policies and care programs using different geographically based SDoH indices to address health disparities in orthopaedic surgery are appropriate.

QUESTIONS/PURPOSES

Among new patients seeking care at an orthopaedic surgery clinic, (1) what is the correlation of the NSS, ADI, and SVI with one another? (2) What is the correlation of Patient-Reported Outcomes Measurement Information System (PROMIS) Global-10 physical and mental health scores and the NSS, ADI, and SVI? (3) Which geographically based SDoH index or indices are associated with presenting PROMIS Global-10 physical and mental health scores when accounting for common patient-level sociodemographic factors?

METHODS

New adult orthopaedic patient encounters at clinic sites affiliated with a tertiary referral academic medical center between 2016 and 2021 were identified, and the ADI, NSS, and SVI were determined. Patients also completed the PROMIS Global-10 questionnaire as part of routine care. Overall, a total of 75,335 new patient visits were noted. Of these, 62% (46,966 of 75,335) of new patient visits were excluded because of missing PROMIS Global-10 physical and mental health scores. An additional 2.2% of patients (1685 of 75,335) were excluded because they were missing at least one SDoH index at the time of their visit (for example, if a patient only had a Post Office box listed, the SDoH index could not be determined). This left 35% of the eligible new patient visits (26,684 of 75,335) in our final sample. Though only 35% of possible new patient visits were included, the diversity of these individuals across numerous characteristics and the wide range of sociodemographic status-as measured by the SDoH indices-among included patients supports the generalizability of our sample. The mean age of patients in our sample was 55 ± 18 years and a slight majority were women (54% [14,366 of 26,684]). Among the sample, 16% (4381of 26,684) of patients were of non-White race. The mean PROMIS Global-10 physical and mental health scores were 43.4 ± 9.4 and 49.7 ± 10.1, respectively. Spearman correlation coefficients were calculated among the three SDoH indices and between each SDoH index and PROMIS Global-10 physical and mental health scores. In addition, regression analysis was used to assess the association of each SDoH index with presenting functional and mental health, accounting for key patient characteristics. The strength of the association between each SDoH index and PROMIS Global-10 physical and mental health scores was determined using partial r-squared values. Significance was set at p < 0.05.

RESULTS

There was a poor correlation between the ADI and the NSS (ρ = 0.34; p < 0.001). There were good correlations between the ADI and SVI (ρ = 0.43; p < 0.001) and between the NSS and SVI (ρ = 0.59; p < 0.001). There was a poor correlation between the PROMIS Global-10 physical health and NSS (ρ = -0.14; p < 0.001), ADI (ρ = -0.24; p < 0.001), and SVI (ρ = -0.17; p < 0.001). There was a poor correlation between PROMIS Global-10 mental health and NSS (ρ = -0.13; p < 0.001), ADI (ρ = -0.22; p < 0.001), and SVI (ρ = -0.17; p < 0.001). When accounting for key sociodemographic factors, the ADI demonstrated the largest association with presenting physical health (regression coefficient: -0.13 [95% CI -0.14 to -0.12]; p < 0.001) and mental health (regression coefficient: -0.13 [95% CI -0.14 to -0.12]; p < 0.001), as confirmed by the partial r-squared values for each SDoH index (physical health: ADI 0.04 versus SVI 0.02 versus NSS 0.01; mental health: ADI 0.04 versus SVI 0.02 versus NSS 0.01). This finding means that as social deprivation increases, physical and mental health scores decrease, representing poorer health. For further context, an increase in ADI score by approximately 36 and 39 suggests a clinically meaningful (determined using distribution-based minimum clinically important difference estimates of one-half SD of each PROMIS score) worsening of physical and mental health, respectively.

CONCLUSION

Orthopaedic surgeons, policy makers, and other stakeholders looking to address SDoH factors to help alleviate disparities in musculoskeletal care should try to avoid interchanging the ADI, SVI, and NSS. Because the ADI has the largest association between any of the geographically based SDoH indices and presenting physical and mental health, it may allow for easier clinical and policy application.

CLINICAL RELEVANCE

We suggest using the ADI as the geographically based SDoH index in orthopaedic surgery in the United States. Further, we caution against comparing findings in one study that use one geographically based SDoH index to another study's findings that incorporates another geographically based SDoH index. Although the general findings may be the same, the strength of association and clinical relevance could differ and have policy ramifications that are not otherwise appreciated; however, the degree to which this may be true is an area for future inquiry.

Survival in Patients With Spinal Metastatic Disease Treated Nonoperatively With Radiotherapy: Are the SORG-ML Algorithms Relevant?

SUMMARY OF BACKGROUND DATA

The SORG-ML algorithms for survival in spinal metastatic disease were developed in patients who underwent surgery and were externally validated for patients managed operatively.

OBJECTIVE

To externally validate the SORG-ML algorithms for survival in spinal metastatic disease in patients managed nonoperatively with radiation.

STUDY DESIGN

Retrospective cohort.

METHODS

The performance of the SORG-ML algorithms was assessed by discrimination [receiver operating curves and area under the receiver operating curve (AUC)], calibration (calibration plots), decision curve analysis, and overall performance (Brier score). The primary outcomes were 90-day and 1-year mortality.

RESULTS

Overall, 2074 adult patients underwent radiation for spinal metastatic disease and 29% (n=521) and 59% (n=917) had 90-day and 1-year mortality, respectively. On complete case analysis (n=415), the AUC was 0.76 (95% CI: 0.71-0.80) and 0.78 (95% CI: 0.73-0.83) for 90-day and 1-year mortality with fair calibration and positive net benefit confirmed by the decision curve analysis. With multiple imputation (n=2074), the AUC was 0.85 (95% CI: 0.83-0.87) and 0.87 (95% CI: 0.85-0.89) for 90-day and 1-year mortality with fair calibration and positive net benefit confirmed by the decision curve analysis.

CONCLUSION

The SORG-ML algorithms for survival in spinal metastatic disease generalize well to patients managed nonoperatively with radiation.

Limited health literacy results in lower health-related quality of life in spine patients

BACKGROUND CONTEXT

Spinal conditions impact health-related quality of life (HRQoL). Patient education and counseling improve HRQoL, yet the effects may be limited for patients with inadequate health literacy (HL). Despite the established relationship between HRQoL and HL in other fields, research in the orthopedic spine population is lacking.

PURPOSE

To investigate if limited HL results in lower HRQoL and to evaluate factors are associated with HRQoL in patients seen at an outpatient orthopedic spine center.

STUDY DESIGN/SETTING

Prospective single-center cross-sectional study.

PATIENT SAMPLE

Patients 18 years of age or older seen at a tertiary urban academic hospital- based multi-surgeon outpatient spine center.

OUTCOME MEASURES

EQ-5D-5L health-related quality of life (HRQoL) questionnaire, and the Newest Vital Sign (NVS) HL assessment tool.

METHODS

Between October 2022 and February 2023, consecutive English-speaking patients over the age of 18 and new to the outpatient spine clinic were approached for participation in this cross-sectional survey study. Patients completed a sociodemographic survey, EQ-5D-5L HRQoL questionnaire, and Newest Vital Sign (NVS) HL assessment tool. The EQ-5D-5L yields two continuous outcomes: an index score ranging from below 0 to 1 and a visual analog scale (EQ-VAS) score ranging from 0 to 100. The NVS scores were divided into limited (0-3) and adequate (4-6) HL. Multivariate linear regression with purposeful selection of variables was performed to identify independent factors associated with HRQoL.

RESULTS

Out of 397 eligible patients, 348 (88%) agreed to participate and were included in statistical analysis. Limited HL was independently associated with lower EQ-5D-5L index scores (B=1.07 [95% CI 1.00-1.15], p=.049. Other factors associated with lower EQ-5D-5L index scores were being obese (BMI≥30), having housing concerns, and being an active smoker. Factors associated with lower EQ-VAS scores were being underweight (BMI<18.5), obese, having housing concerns, and higher updated Charlson comorbidity index (uCCI) scores. Being married was associated with higher EQ-VAS scores.

CONCLUSIONS

Limited HL is associated with lower EQ-5D-5L index scores in spine patients, indicating lower HRQoL. To effectively apply HL-related interventions in this population, a better understanding of the complex interactions between patient characteristics, social determinants of health, and HRQoL outcomes is required. Further research should focus on interventions to improve HRQoL in patients with limited HL and how to accurately identify these patients.

LEVEL OF EVIDENCE

Level II prognostic.

Fracture rate after conventional external beam radiation therapy to the spine in multiple myeloma patients

BACKGROUND CONTEXT

Conventional external beam radiation therapy (cEBRT) is used in multiple myeloma (MM) to treat severe pain, spinal cord compression, and disease-related bone disease. However, radiation may be associated with an increased risk of vertebral compression fractures (VCFs), which could substantially impair survival and quality of life. Additionally, the use of the Spinal Instability Neoplastic Score (SINS) in MM is debated in MM.

PURPOSE

To determine the incidence of VCFs after cEBRT in patients with MM and to assess the applicability of the SINS score in the prediction of VCFs in MM.

STUDY DESIGN

Retrospective multicenter cohort study.

PATIENT SAMPLE

MM patients with spinal myeloma lesions who underwent cEBRT between January 2010 and December 2021.

OUTCOME MEASURES

Frequency of new or progressed VCFs and subdistribution hazard ratios for potentially associated factors.

METHODS

Patient and treatment characteristics were manually collected from the patients' electronic medical records. Computed tomography (CT) scans from before and up to 3 years after the start of radiation were used to score radiographic variables at baseline and at follow-up. Multivariable Fine and Gray competing risk analyses were performed to evaluate the diagnostic value of the SINS score to predict the postradiation VCF rate.

RESULTS

A total of 127 patients with 427 eligible radiated vertebrae were included in this study. The mean age at radiation was 64 years, and 66.1% of them were male. At the start of radiation, 57 patients (44.9%) had at least one VCF. There were 89 preexisting VCFs (18.4% of 483 vertebrae). Overall, 39 of 127 patients (30.7%) reported new fractures (number of vertebrae (n)=12) or showed progression of existing fractures (n=36). This number represented 11.2% of all radiated vertebrae. Five of the 39 (12.8%) patients with new or worsened VCFs received an unplanned secondary treatment (augmentation [n=2] or open surgery [n=3]) within 3 years. Both the total SINS score (SHR 1.77; 95% confidence interval (CI) 1.54-2.03; p<.001) and categorical SINS score (SHR 10.83; 95% CI 4.20-27.94; p<.001) showed an independent association with higher rates of new or progressed VCFs in adjusted analyses. The use of bisphosphonates was independently associated with a lower rate of new or progressed VCFs (SHR 0.47 [95% CI 0.24-0.92; p=.027]).

CONCLUSIONS

This study demonstrated that new or progressed VCFs occurred in 30.7% of patients within 3 years, in a total of 11.2% of vertebrae. The SINS score was found to be independently associated with the development or progression of VCFs and could thus be applied in MM for fracture prediction and possibly prevention.

Analysis of complications and revisions after spine surgery in 270 multiple myeloma patients with spinal involvement

BACKGROUND CONTEXT

Patients with multiple myeloma (MM) are at increased risk of infections and suffer from poor bone quality due to their disseminated malignant bone disease. Therefore, postoperative complications may occur following surgical treatment of MM lesions.

PURPOSE

In this study, we aimed to determine the incidence of postoperative complications and retreatments after spinal surgery in MM patients. Additionally, we sought to identify risk factors associated with complications and retreatments.

STUDY DESIGN

Retrospective cohort study.

PATIENT SAMPLE

In total, 270 patients with MM who received surgical treatment for spinal involvement between 2008 and 2021 were included.

OUTCOME MEASURES

The incidence of perioperative complications within 6 weeks and reoperations within 2.5 years and individual odds ratios for factors associated with these complications and reoperations.

METHODS

Data were collected through manual chart review. Hosmer and Lemeshow's purposeful regression method was used to identify risk factors for complications and reoperations.

RESULTS

The median age of our cohort was 65 years (SD = 10.8), and 58% were male (n = 57). Intraoperative complications were present in 24 patients (8.9%). The overall 6-week complication rate after surgery was 35% (n = 95). The following variables were independently associated with 6-week complications: higher Genant grading of a present vertebral fracture (OR 1.41; 95% CI 1.04-1.95; p = .031), receiving intramuscular or intravenous steroids within a week prior to surgery (OR 3.97; 95% CI 1.79-9.06; p = .001), decompression surgery without fusion (OR 6.53; 95% CI 1.30-36.86; p = .026), higher creatinine levels (OR 2.18; 95% CI 1.19-5.60; p = .014), and lower calcium levels (OR 0.58; 95% CI 0.37-0.88; p = .013). A secondary surgery was indicated for 53 patients (20%), of which 13 (4.8%) took place within two weeks after the initial surgery. We additionally discovered factors associated with retreatments, which are elucidated within the manuscript.

CONCLUSION

The goal of surgical treatment for MM bone disease is to enhance patient quality of life and reduce symptom burden. However, postoperative complication rates remain relatively high after spine surgery in patients with MM, likely attributable to both inherent characteristics of the disease and patient comorbidities. The risk for complications and secondary surgeries should be explored and a multidisciplinary approach is crucial.

Does the SORG Machine-learning Algorithm for Extremity Metastases Generalize to a Contemporary Cohort of Patients? Temporal Validation From 2016 to 2020

BACKGROUND

The ability to predict survival accurately in patients with osseous metastatic disease of the extremities is vital for patient counseling and guiding surgical intervention. We, the Skeletal Oncology Research Group (SORG), previously developed a machine-learning algorithm (MLA) based on data from 1999 to 2016 to predict 90-day and 1-year survival of surgically treated patients with extremity bone metastasis. As treatment regimens for oncology patients continue to evolve, this SORG MLA-driven probability calculator requires temporal reassessment of its accuracy.

QUESTION/PURPOSE

Does the SORG-MLA accurately predict 90-day and 1-year survival in patients who receive surgical treatment for a metastatic long-bone lesion in a more recent cohort of patients treated between 2016 and 2020?

METHODS

Between 2017 and 2021, we identified 674 patients 18 years and older through the ICD codes for secondary malignant neoplasm of bone and bone marrow and CPT codes for completed pathologic fractures or prophylactic treatment of an impending fracture. We excluded 40% (268 of 674) of patients, including 18% (118) who did not receive surgery; 11% (72) who had metastases in places other than the long bones of the extremities; 3% (23) who received treatment other than intramedullary nailing, endoprosthetic reconstruction, or dynamic hip screw; 3% (23) who underwent revision surgery, 3% (17) in whom there was no tumor, and 2% (15) who were lost to follow-up within 1 year. Temporal validation was performed using data on 406 patients treated surgically for bony metastatic disease of the extremities from 2016 to 2020 at the same two institutions where the MLA was developed. Variables used to predict survival in the SORG algorithm included perioperative laboratory values, tumor characteristics, and general demographics. To assess the models' discrimination, we computed the c-statistic, commonly referred to as the area under the receiver operating characteristic (AUC) curve for binary classification. This value ranged from 0.5 (representing chance-level performance) to 1.0 (indicating excellent discrimination) Generally, an AUC of 0.75 is considered high enough for use in clinical practice. To evaluate the agreement between predicted and observed outcomes, a calibration plot was used, and the calibration slope and intercept were calculated. Perfect calibration would result in a slope of 1 and intercept of 0. For overall performance, the Brier score and null-model Brier score were determined. The Brier score can range from 0 (representing perfect prediction) to 1 (indicating the poorest prediction). Proper interpretation of the Brier score necessitates a comparison with the null-model Brier score, which represents the score for an algorithm that predicts a probability equal to the population prevalence of the outcome for each patient. Finally, a decision curve analysis was conducted to compare the potential net benefit of the algorithm with other decision-support methods, such as treating all or none of the patients. Overall, 90-day and 1-year mortality were lower in the temporal validation cohort than in the development cohort (90 day: 23% versus 28%; p < 0.001, and 1 year: 51% versus 59%; p<0.001).

RESULTS

Overall survival of the patients in the validation cohort improved from 28% mortality at the 90-day timepoint in the cohort on which the model was trained to 23%, and 59% mortality at the 1-year timepoint to 51%. The AUC was 0.78 (95% CI 0.72 to 0.82) for 90-day survival and 0.75 (95% CI 0.70 to 0.79) for 1-year survival, indicating the model could distinguish the two outcomes reasonably. For the 90-day model, the calibration slope was 0.71 (95% CI 0.53 to 0.89), and the intercept was -0.66 (95% CI -0.94 to -0.39), suggesting the predicted risks were overly extreme, and that in general, the risk of the observed outcome was overestimated. For the 1-year model, the calibration slope was 0.73 (95% CI 0.56 to 0.91) and the intercept was -0.67 (95% CI -0.90 to -0.43). With respect to overall performance, the model's Brier scores for the 90-day and 1-year models were 0.16 and 0.22. These scores were higher than the Brier scores of internal validation of the development study (0.13 and 0.14) models, indicating the models' performance has declined over time.

CONCLUSION

The SORG MLA to predict survival after surgical treatment of extremity metastatic disease showed decreased performance on temporal validation. Moreover, in patients undergoing innovative immunotherapy, the possibility of mortality risk was overestimated in varying severity. Clinicians should be aware of this overestimation and discount the prediction of the SORG MLA according to their own experience with this patient population. Generally, these results show that temporal reassessment of these MLA-driven probability calculators is of paramount importance because the predictive performance may decline over time as treatment regimens evolve. The SORG-MLA is available as a freely accessible internet application at https://sorg-apps.shinyapps.io/extremitymetssurvival/ .Level of Evidence Level III, prognostic study.

Inpatient opioid use varies by construct length among laminoplasty versus laminectomy and fusion patients

Background

Laminoplasty (LP) and laminectomy and fusion (LF) are utilized to achieve decompression in patients with symptomatic degenerative cervical myelopathy (DCM). Comparative analyses aimed at determining outcomes and clarifying indications between these procedures represent an area of active research. Accordingly, we sought to compare inpatient opioid use between LP and LF patients and to determine if opioid use correlated with length of stay.

Methods

Sociodemographic information, surgical and hospitalization data, and medication administration records were abstracted for patients >18 years of age who underwent LP or LF for DCM in the Mass General Brigham (MGB) health system between 2017 and 2019. Specifically, morphine milligram equivalents (MME) of oral and parenteral pain medication given after arrival in the recovery area until discharge from the hospital were collected. Categorical variables were analyzed using chi-squared analysis or Fisher exact test when appropriate. Continuous variables were compared using Independent samples t tests and Mann-Whitney U tests.

Results

One hundred eight patients underwent LF, while 138 patients underwent LP. Total inpatient opioid use was significantly higher in the LF group (312 vs. 260 MME, p=.03); this difference was primarily driven by higher postoperative day 0 pain medication requirements. Furthermore, more LF patients required high dose (>80 MME/day) regimens. While length of stay was significantly different between groups, with LF patients staying approximately 1 additional day, postoperative day 0 MME was not a significant predictor of this difference. When operative levels including C2, T1, and T2 were excluded, the differences in total opioid use and average length of stay lost significance.

Conclusions

Inpatient opioid use and length of stay were significantly greater in LF patients compared to LP patients; however, when constructs including C2, T1, T2 were excluded from analysis, these differences lost significance. Such findings highlight the impact of operative extent between these procedures. Future studies incorporating patient reported outcomes and evaluating long-term pain needs will provide a more complete understanding of postoperative outcomes between these 2 procedures.

Pilot Study: Short Term Impact of Radiation Therapy on Bone Mineral Density and Bone Metabolism

Despite the risk of complications, high dose radiation therapy is increasingly utilized in the management of selected bone malignancies. In this study, we investigate the impact of moderate to high dose radiation (over 50 Gy) on bone metabolism and structure. Between 2015 and 2018, patients with a primary malignant bone tumor of the sacrum that were either treated with high dose definitive radiation only or a combination of moderate to high dose radiation and surgery were prospectively enrolled at a single institution. Quantitative CTs were performed before and after radiation to determine changes in volumetric bone mineral density (BMD) of the irradiated and non-irradiated spine. Bone histomorphometry was performed on biopsies of the irradiated sacrum and the non-irradiated iliac crest of surgical patients using a quadruple tetracycline labeling protocol. In total, 9 patients were enrolled. Two patients received radiation only (median dose 78.3 Gy) and 7 patients received a combination of preoperative radiation (median dose 50.4 Gy), followed by surgery. Volumetric BMD of the non-irradiated lumbar spine did not change significantly after radiation, while the BMD of the irradiated sacrum did (pre-radiation median: 108.0 mg/cm3 (IQR 91.8-167.1); post-radiation median: 75.3 mg/cm3 (IQR 57.1-110.2); p = 0.010). The cancellous bone of the non-irradiated iliac crest had a stable bone formation rate, while the irradiated sacrum showed a significant decrease in bone formation rate [pre-radiation median: 0.005 mm3/mm2/year (IQR 0.003-0.009), post-radiation median: 0.001 mm3/mm2/year (IQR 0.001-0.001); p = 0.043]. Similar effects were seen in the cancellous and endocortical envelopes. This pilot study shows a decrease of volumetric BMD and bone formation rate after high-dose radiation therapy. Further studies with larger cohorts and other endpoints are needed to get more insight into the effect of radiation on bone. Level of evidence: IV.

AOA Critical Issues Symposium: Shaping the Impact of Artificial Intelligence within Orthopaedic Surgery

ABSTRACT

Artificial intelligence (AI) is a broad term that is widely used but inconsistently understood. It refers to the ability of any machine to exhibit human-like intelligence by making decisions, solving problems, or learning from experience. With its ability to rapidly process large amounts of information, AI has already transformed many industries such as entertainment, transportation, and communications through consumer-facing products and business-to-business applications. Given its potential, AI is also anticipated to impact the practice of medicine and the delivery of health care. Interest in AI-based techniques has grown rapidly within the orthopaedic community, resulting in an increasing number of publications on this topic. Topics of interest have ranged from the use of AI for imaging interpretation to AI-based techniques for predicting postoperative outcomes.The highly technical and data-driven nature of orthopaedic surgery creates the potential for AI, and its subdisciplines machine learning (ML) and deep learning (DL), to fundamentally transform our understanding of musculoskeletal care. However, AI-based techniques are not well known to most orthopaedic surgeons, nor are they taught with the same level of insight and critical thinking as traditional statistical methodology. With a clear understanding of the science behind AI-based techniques, orthopaedic surgeons will be able to identify the potential pitfalls of the application of AI to musculoskeletal health. Additionally, with increased understanding of AI, surgeons and their patients may have more trust in the results of AI-based analytics, thereby expanding the potential use of AI in clinical care and amplifying the impact it could have in improving quality and value. The purpose of this American Orthopaedic Association (AOA) symposium was to facilitate understanding and development of AI and AI-based techniques within orthopaedic surgery by defining common terminology related to AI, demonstrating the existing clinical utility of AI, and presenting future applications of AI in surgical care.

Development of a machine learning algorithm to identify surgical candidates for hip and knee arthroplasty without in-person evaluation

INTRODUCTION

Arthroplasty care delivery is facing a growing supply-demand mismatch. To meet future demand for joint arthroplasty, systems will need to identify potential surgical candidates prior to evaluation by orthopaedic surgeons.

MATERIALS AND METHODS

Retrospective review was conducted at two academic medical centers and three community hospitals from March 1 to July 31, 2020 to identify new patient telemedicine encounters (without prior in-person evaluation) for consideration of hip or knee arthroplasty. The primary outcome was surgical indication for joint replacement. Five machine learning algorithms were developed to predict likelihood of surgical indication and assessed by discrimination, calibration, overall performance, and decision curve analysis.

RESULTS

Overall, 158 patients underwent new patient telemedicine evaluation for consideration of THA, TKA, or UKA and 65.2% (n = 103) were indicated for operative intervention prior to in-person evaluation. The median age was 65 (interquartile range 59-70) and 60.8% were women. Variables found to be associated with operative intervention were radiographic degree of arthritis, prior trial of intra-articular injection, trial of physical therapy, opioid use, and tobacco use. In the independent testing set (n = 46) not used for algorithm development, the stochastic gradient boosting algorithm achieved the best performance with AUC 0.83, calibration intercept 0.13, calibration slope 1.03, Brier score 0.15 relative to a null model Brier score of 0.23, and higher net benefit than the default alternatives on decision curve analysis.

CONCLUSION

We developed a machine learning algorithm to identify potential surgical candidates for joint arthroplasty in the setting of osteoarthritis without an in-person evaluation or physical examination. If externally validated, this algorithm could be deployed by various stakeholders, including patients, providers, and health systems, to direct appropriate next steps in patients with osteoarthritis and improve efficiency in identifying surgical candidates.

LEVEL OF EVIDENCE

III.

A Machine Learning Algorithm for Predicting 6-Week Survival in Spinal Metastasis: An External Validation Study Using 2,768 Taiwanese Patients

INTRODUCTION

There are predictive algorithms for predicting 3-month and 1-year survival in patients with spinal metastasis. However, advance in surgical technique, immunotherapy, and advanced radiation therapy has enabled shortening of postoperative recovery, which returns dividends to the overall quality-adjusted life-year. As such, the Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) was proposed to predict 6-week survival in patients with spinal metastasis, whereas its utility for patients treated with nonsurgical treatment was untested externally. This study aims to validate the survival prediction of the 6-week SORG-MLA for patients with spinal metastasis and provide the measurement of model consistency (MC).

METHODS

Discrimination using area under the receiver operating characteristic curve, calibration, Brier score, and decision curve analysis were conducted to assess the model's performance in the Taiwanese-based cohort. MC was also applied to detect the proportion of paradoxical predictions among 6-week, 3-month, and 1-year survival predictions. The long-term prognosis should not be better than the shorter-term prognosis in that of an individual.

RESULTS

The 6-week survival rate was 84.2%. The SORG-MLA retained good discrimination with an area under the receiver operating characteristic curve of 0.78 (95% confidence interval, 0.75 to 0.80) and good prediction accuracy with a Brier score of 0.11 (null model Brier score 0.13). There is an underestimation of the 6-week survival rate when the predicted survival rate is less than 50%. Decision curve analysis showed that the model was suitable for use over all threshold probabilities. MC showed suboptimal consistency between 6-week and 90-day survival prediction (78%).

CONCLUSIONS

The results of this study supported the utility of the algorithm. The online tool ( https://sorg-apps.shinyapps.io/spinemetssurvival/ ) can be used by both clinicians and patients in informative decision-making discussion before management of spinal metastasis.

Neurologic Outcomes After Radiation Therapy for Severe Spinal Cord Compression in Multiple Myeloma: A Study of 162 Patients

BACKGROUND

Bone destruction is the most frequent disease-defining clinical feature of multiple myeloma (MM), resulting in skeletal-related events such as back pain, pathological fractures, or neurologic compromise including epidural spinal cord compression (ESCC). Up to 24% of patients with MM will be affected by ESCC. Radiation therapy has been proven to be highly effective in pain relief in patients with MM. However, a critical knowledge gap remains with regard to neurologic outcomes in patients with high-grade ESCC treated with radiation.

METHODS

We retrospectively included 162 patients with MM and high-grade ESCC (grade 2 or 3) who underwent radiation therapy of the spine between January 2010 and July 2021. The primary outcome was the American Spinal Injury Association (ASIA) score after 12 to 24 months, or the last known ASIA score if the patient had had a repeat treatment or died. Multivariable logistic regression was used to assess factors associated with poor neurologic outcomes after radiation, defined as neurologic deterioration or lack of improvement.

RESULTS

After radiation therapy, 34 patients (21%) had no improvement in their impaired neurologic function and 27 (17%) deteriorated neurologically. Thirty-six patients (22%) underwent either surgery or repeat irradiation after the initial radiation therapy. There were 100 patients who were neurologically intact at baseline (ASIA score of E), of whom 16 (16%) had neurologic deterioration. Four variables were independently associated with poor neurologic outcomes: baseline ASIA (odds ratio [OR] = 6.50; 95% confidence interval [CI] = 2.70 to 17.38; p < 0.001), Eastern Cooperative Oncology Group (ECOG) performance status (OR = 6.19; 95% CI = 1.49 to 29.49; p = 0.015), number of levels affected by ESCC (OR = 4.02; 95% CI = 1.19 to 14.18; p = 0.026), and receiving steroids prior to radiation (OR = 4.42; 95% CI = 1.41 to 16.10; p = 0.015).

CONCLUSIONS

Our study showed that 38% of patients deteriorated or did not improve neurologically after radiation therapy for high-grade ESCC. The results highlight the need for multidisciplinary input and efforts in the treatment of high-grade ESCC in patients with MM. Future studies will help to improve patient selection for specific and standardized treatments and to clearly delineate which patients are likely to benefit from radiation therapy.

LEVEL OF EVIDENCE

Therapeutic Level IV . See Instructions for Authors for a complete description of levels of evidence.

Neurological Outcomes and the Need for Retreatments Among Multiple Myeloma Patients With High-Grade Spinal Cord Compression: Radiotherapy vs Surgery

STUDY DESIGN

Retrospective cohort study.

OBJECTIVES

Up to 30% of Multiple Myeloma (MM) patients are expected to experience Epidural Spinal Cord Compression (ESCC) during the course of their disease. To prevent irreversible neurological damage, timely diagnosis and treatment are important. However, debate remains regarding the optimal treatment regimen. The aim of this study was to investigate the neurological outcomes and frequency of retreatments for MM patients undergoing isolated radiotherapy and surgical interventions for high-grade (grade 2-3) ESCC.

METHODS

This study included patients with MM and high-grade ESCC treated with isolated radiotherapy or surgery. Pre- and post-treatment American Spinal Injury Association (ASIA) impairment scale and retreatment rate were compared between the 2 groups. Adjusted multivariable logistic regression was utilized to examine differences in neurologic compromise, pain, and retreatments.

RESULTS

A total of 247 patients were included (Radiotherapy: n = 154; Surgery: n = 93). After radiotherapy, 82 patients (53%) achieved full neurologic function (ASIA E) at the end of follow-up. Of the surgically treated patients, 67 (64%) achieved full neurologic function. In adjusted analyses, patients treated with surgery were less likely to experience neurologic deterioration within 2 years (OR = .15; 95%CI .05-.44; P = .001) and had less pain (OR = .29; 95%CI .11-.74; P = .010). Surgical treatment was not associated with an increased risk of retreatments (OR = .64; 95%CI .28-1.47; P = .29) or death (HR = .62, 95%CI .28-1.38; P = .24).

CONCLUSIONS

After adjusting for baseline differences, surgically treated patients with high-grade ESCC showed better neurologic outcomes compared to patients treated with radiotherapy. There were no differences in risk of retreatment or death.

The Skeletal Oncology Research Group Machine Learning Algorithm (SORG-MLA) for predicting prolonged postoperative opioid prescription after total knee arthroplasty: an international validation study using 3,495 patients from a Taiwanese cohort

BACKGROUND

Preoperative prediction of prolonged postoperative opioid use (PPOU) after total knee arthroplasty (TKA) could identify high-risk patients for increased surveillance. The Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) has been tested internally while lacking external support to assess its generalizability. The aims of this study were to externally validate this algorithm in an Asian cohort and to identify other potential independent factors for PPOU.

METHODS

In a tertiary center in Taiwan, 3,495 patients receiving TKA from 2010-2018 were included. Baseline characteristics were compared between the external validation cohort and the original developmental cohorts. Discrimination (area under receiver operating characteristic curve [AUROC] and precision-recall curve [AUPRC]), calibration, overall performance (Brier score), and decision curve analysis (DCA) were applied to assess the model performance. A multivariable logistic regression was used to evaluate other potential prognostic factors.

RESULTS

There were notable differences in baseline characteristics between the validation and the development cohort. Despite these variations, the SORG-MLA ( https://sorg-apps.shinyapps.io/tjaopioid/ ) remained its good discriminatory ability (AUROC, 0.75; AUPRC, 0.34) and good overall performance (Brier score, 0.029; null model Brier score, 0.032). The algorithm could bring clinical benefit in DCA while somewhat overestimating the probability of prolonged opioid use. Preoperative acetaminophen use was an independent factor to predict PPOU (odds ratio, 2.05).

CONCLUSIONS

The SORG-MLA retained its discriminatory ability and good overall performance despite the different pharmaceutical regulations. The algorithm could be used to identify high-risk patients and tailor personalized prevention policy.

Does the Presence of Missing Data Affect the Performance of the SORG Machine-learning Algorithm for Patients With Spinal Metastasis? Development of an Internet Application Algorithm

BACKGROUND

The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA) was developed to predict the survival of patients with spinal metastasis. The algorithm was successfully tested in five international institutions using 1101 patients from different continents. The incorporation of 18 prognostic factors strengthens its predictive ability but limits its clinical utility because some prognostic factors might not be clinically available when a clinician wishes to make a prediction.

QUESTIONS/PURPOSES

We performed this study to (1) evaluate the SORG-MLA's performance with data and (2) develop an internet-based application to impute the missing data.

METHODS

A total of 2768 patients were included in this study. The data of 617 patients who were treated surgically were intentionally erased, and the data of the other 2151 patients who were treated with radiotherapy and medical treatment were used to impute the artificially missing data. Compared with those who were treated nonsurgically, patients undergoing surgery were younger (median 59 years [IQR 51 to 67 years] versus median 62 years [IQR 53 to 71 years]) and had a higher proportion of patients with at least three spinal metastatic levels (77% [474 of 617] versus 72% [1547 of 2151]), more neurologic deficit (normal American Spinal Injury Association [E] 68% [301 of 443] versus 79% [1227 of 1561]), higher BMI (23 kg/m2 [IQR 20 to 25 kg/m2] versus 22 kg/m2 [IQR 20 to 25 kg/m2]), higher platelet count (240 × 103/µL [IQR 173 to 327 × 103/µL] versus 227 × 103/µL [IQR 165 to 302 × 103/µL], higher lymphocyte count (15 × 103/µL [IQR 9 to 21× 103/µL] versus 14 × 103/µL [IQR 8 to 21 × 103/µL]), lower serum creatinine level (0.7 mg/dL [IQR 0.6 to 0.9 mg/dL] versus 0.8 mg/dL [IQR 0.6 to 1.0 mg/dL]), less previous systemic therapy (19% [115 of 617] versus 24% [526 of 2151]), fewer Charlson comorbidities other than cancer (28% [170 of 617] versus 36% [770 of 2151]), and longer median survival. The two patient groups did not differ in other regards. These findings aligned with our institutional philosophy of selecting patients for surgical intervention based on their level of favorable prognostic factors such as BMI or lymphocyte counts and lower levels of unfavorable prognostic factors such as white blood cell counts or serum creatinine level, as well as the degree of spinal instability and severity of neurologic deficits. This approach aims to identify patients with better survival outcomes and prioritize their surgical intervention accordingly. Seven factors (serum albumin and alkaline phosphatase levels, international normalized ratio, lymphocyte and neutrophil counts, and the presence of visceral or brain metastases) were considered possible missing items based on five previous validation studies and clinical experience. Artificially missing data were imputed using the missForest imputation technique, which was previously applied and successfully tested to fit the SORG-MLA in validation studies. Discrimination, calibration, overall performance, and decision curve analysis were applied to evaluate the SORG-MLA's performance. The discrimination ability was measured with an area under the receiver operating characteristic curve. It ranges from 0.5 to 1.0, with 0.5 indicating the worst discrimination and 1.0 indicating perfect discrimination. An area under the curve of 0.7 is considered clinically acceptable discrimination. Calibration refers to the agreement between the predicted outcomes and actual outcomes. An ideal calibration model will yield predicted survival rates that are congruent with the observed survival rates. The Brier score measures the squared difference between the actual outcome and predicted probability, which captures calibration and discrimination ability simultaneously. A Brier score of 0 indicates perfect prediction, whereas a Brier score of 1 indicates the poorest prediction. A decision curve analysis was performed for the 6-week, 90-day, and 1-year prediction models to evaluate their net benefit across different threshold probabilities. Using the results from our analysis, we developed an internet-based application that facilitates real-time data imputation for clinical decision-making at the point of care. This tool allows healthcare professionals to efficiently and effectively address missing data, ensuring that patient care remains optimal at all times.

RESULTS

Generally, the SORG-MLA demonstrated good discriminatory ability, with areas under the curve greater than 0.7 in most cases, and good overall performance, with up to 25% improvement in Brier scores in the presence of one to three missing items. The only exceptions were albumin level and lymphocyte count, because the SORG-MLA's performance was reduced when these two items were missing, indicating that the SORG-MLA might be unreliable without these values. The model tended to underestimate the patient survival rate. As the number of missing items increased, the model's discriminatory ability was progressively impaired, and a marked underestimation of patient survival rates was observed. Specifically, when three items were missing, the number of actual survivors was up to 1.3 times greater than the number of expected survivors, while only 10% discrepancy was observed when only one item was missing. When either two or three items were omitted, the decision curves exhibited substantial overlap, indicating a lack of consistent disparities in performance. This finding suggests that the SORG-MLA consistently generates accurate predictions, regardless of the two or three items that are omitted. We developed an internet application (https://sorg-spine-mets-missing-data-imputation.azurewebsites.net/) that allows the use of SORG-MLA with up to three missing items.

CONCLUSION

The SORG-MLA generally performed well in the presence of one to three missing items, except for serum albumin level and lymphocyte count (which are essential for adequate predictions, even using our modified version of the SORG-MLA). We recommend that future studies should develop prediction models that allow for their use when there are missing data, or provide a means to impute those missing data, because some data are not available at the time a clinical decision must be made.

CLINICAL RELEVANCE

The results suggested the algorithm could be helpful when a radiologic evaluation owing to a lengthy waiting period cannot be performed in time, especially in situations when an early operation could be beneficial. It could help orthopaedic surgeons to decide whether to intervene palliatively or extensively, even when the surgical indication is clear.

Comparison of eight modern preoperative scoring systems for survival prediction in patients with extremity metastasis

BACKGROUND

Survival is an important factor to consider when clinicians make treatment decisions for patients with skeletal metastasis. Several preoperative scoring systems (PSSs) have been developed to aid in survival prediction. Although we previously validated the Skeletal Oncology Research Group Machine-learning Algorithm (SORG-MLA) in Taiwanese patients of Han Chinese descent, the performance of other existing PSSs remains largely unknown outside their respective development cohorts. We aim to determine which PSS performs best in this unique population and provide a direct comparison between these models.

METHODS

We retrospectively included 356 patients undergoing surgical treatment for extremity metastasis at a tertiary center in Taiwan to validate and compare eight PSSs. Discrimination (c-index), decision curve (DCA), calibration (ratio of observed:expected survivors), and overall performance (Brier score) analyses were conducted to evaluate these models' performance in our cohort.

RESULTS

The discriminatory ability of all PSSs declined in our Taiwanese cohort compared with their Western validations. SORG-MLA is the only PSS that still demonstrated excellent discrimination (c-indexes>0.8) in our patients. SORG-MLA also brought the most net benefit across a wide range of risk probabilities on DCA with its 3-month and 12-month survival predictions.

CONCLUSIONS

Clinicians should consider potential ethnogeographic variations of a PSS's performance when applying it onto their specific patient populations. Further international validation studies are needed to ensure that existing PSSs are generalizable and can be integrated into the shared treatment decision-making process. As cancer treatment keeps advancing, researchers developing a new prediction model or refining an existing one could potentially improve their algorithm's performance by using data gathered from more recent patients that are reflective of the current state of cancer care.

Are Detailed, Patient-level Social Determinant of Health Factors Associated With Physical Function and Mental Health at Presentation Among New Patients With Orthopaedic Conditions?

BACKGROUND

It is well documented that routinely collected patient sociodemographic characteristics (such as race and insurance type) and geography-based social determinants of health (SDoH) measures (for example, the Area Deprivation Index) are associated with health disparities, including symptom severity at presentation. However, the association of patient-level SDoH factors (such as housing status) on musculoskeletal health disparities is not as well documented. Such insight might help with the development of more-targeted interventions to help address health disparities in orthopaedic surgery.

QUESTIONS/PURPOSES

(1) What percentage of patients presenting for new patient visits in an orthopaedic surgery clinic who were unemployed but seeking work reported transportation issues that could limit their ability to attend a medical appointment or acquire medications, reported trouble paying for medications, and/or had no current housing? (2) Accounting for traditional sociodemographic factors and patient-level SDoH measures, what factors are associated with poorer patient-reported outcome physical health scores at presentation? (3) Accounting for traditional sociodemographic factor patient-level SDoH measures, what factors are associated with poorer patient-reported outcome mental health scores at presentation?

METHODS

New patient encounters at one Level 1 trauma center clinic visit from March 2018 to December 2020 were identified. Included patients had to meet two criteria: they had completed the Patient-Reported Outcome Measure Information System (PROMIS) Global-10 at their new orthopaedic surgery clinic encounter as part of routine clinical care, and they had visited their primary care physician and completed a series of specific SDoH questions. The SDoH questionnaire was developed in our institution to improve data that drive interventions to address health disparities as part of our accountable care organization work. Over the study period, the SDoH questionnaire was only distributed at primary care provider visits. The SDoH questions focused on transportation, housing, employment, and ability to pay for medications. Because we do not have a way to determine how many patients had both primary care provider office visits and new orthopaedic surgery clinic visits over the study period, we were unable to determine how many patients could have been included; however, 9057 patients were evaluated in this cross-sectional study. The mean age was 61 ± 15 years, and most patients self-reported being of White race (83% [7561 of 9057]). Approximately half the patient sample had commercial insurance (46% [4167 of 9057]). To get a better sense of how this study cohort compared with the overall patient population seen at the participating center during the time in question, we reviewed all new patient clinic encounters (n = 135,223). The demographic information between the full patient sample and our study subgroup appeared similar. Using our study cohort, two multivariable linear regression models were created to determine which traditional metrics (for example, self-reported race or insurance type) and patient-specific SDoH factors (for example, lack of reliable transportation) were associated with worse physical and mental health symptoms (that is, lower PROMIS scores) at new patient encounters. The variance inflation factor was used to assess for multicollinearity. For all analyses, p values < 0.05 designated statistical significance. The concept of minimum clinically important difference (MCID) was used to assess clinical importance. Regression coefficients represent the projected change in PROMIS physical or mental health symptom scores (that is, the dependent variable in our regression analyses) accounting for the other included variables. Thus, a regression coefficient for a given variable at or above a known MCID value suggests a clinical difference between those patients with and without the presence of that given characteristic. In this manuscript, regression coefficients at or above 4.2 (or at and below -4.2) for PROMIS Global Physical Health and at or above 5.1 (or at and below -5.1) for PROMIS Global Mental Health were considered clinically relevant.

RESULTS

Among the included patients, 8% (685 of 9057) were unemployed but seeking work, 4% (399 of 9057) reported transportation issues that could limit their ability to attend a medical appointment or acquire medications, 4% (328 of 9057) reported trouble paying for medications, and 2% (181 of 9057) had no current housing. Lack of reliable transportation to attend doctor visits or pick up medications (β = -4.52 [95% CI -5.45 to -3.59]; p < 0.001), trouble paying for medications (β = -4.55 [95% CI -5.55 to -3.54]; p < 0.001), Medicaid insurance (β = -5.81 [95% CI -6.41 to -5.20]; p < 0.001), and workers compensation insurance (β = -5.99 [95% CI -7.65 to -4.34]; p < 0.001) were associated with clinically worse function at presentation. Trouble paying for medications (β = -6.01 [95% CI -7.10 to -4.92]; p < 0.001), Medicaid insurance (β = -5.35 [95% CI -6.00 to -4.69]; p < 0.001), and workers compensation (β = -6.07 [95% CI -7.86 to -4.28]; p < 0.001) were associated with clinically worse mental health at presentation.

CONCLUSION

Although transportation issues and financial hardship were found to be associated with worse presenting physical function and mental health, Medicaid and workers compensation insurance remained associated with worse presenting physical function and mental health as well even after controlling for these more detailed, patient-level SDoH factors. Because of that, interventions to decrease health disparities should focus on not only sociodemographic variables (for example, insurance type) but also tangible patient-specific SDoH characteristics. For example, this may include giving patients taxi vouchers or ride-sharing credits to attend clinic visits for patients demonstrating such a need, initiating financial assistance programs for necessary medications, and/or identifying and connecting certain patient groups with social support services early on in the care cycle.

LEVEL OF EVIDENCE

Level III, prognostic study.

Clockwise torque results in higher reoperation rates in left-sided femur fractures

PURPOSE

Effects of clockwise torque rotation onto proximal femoral fracture fixation have been subject of ongoing debate: fixated right-sided trochanteric fractures seem more rotationally stable than left-sided fractures in the biomechanical setting, but this theoretical advantage has not been demonstrated in the clinical setting to date. The purpose of this study was to identify a difference in early reoperation rate between patients undergoing surgery for left- versus right-sided proximal femur fractures using cephalomedullary nailing (CMN).

MATERIALS AND METHODS

The American College of Surgeons National Surgical Quality Improvement Program was queried from 2016-2019 to identify patients aged 50 years and older undergoing CMN for a proximal femoral fracture. The primary outcome was any unplanned reoperation within 30 days following surgery. The difference was calculated using a Chi-square test, and observed power calculated using post-hoc power analysis.

RESULTS

In total, of 20,122 patients undergoing CMN for proximal femoral fracture management, 1.8% (n=371) had to undergo an unplanned reoperation within 30 days after surgery. Overall, 208 (2.0%) were left-sided and 163 (1.7%) right-sided fractures (p=0.052, risk ratio [RR] 1.22, 95% confidence interval [CI] 1.00-1.50), odds ratio [OR] 1.23 (95%CI 1.00-1.51), power 49.2% (α=0.05).

CONCLUSION

This study shows a higher risk of reoperation for left-sided compared to right-sided proximal femur fractures after CMN in a large sample size. Although results may be underpowered and statistically insignificant, this finding might substantiate the hypothesis that clockwise rotation during implant insertion and (postoperative) weightbearing may lead to higher reoperation rates.

LEVEL OF EVIDENCE

Therapeutic level II.

Impact of Health Literacy on Self-Reported Health Outcomes in Spine Patients

STUDY DESIGN

Cross-sectional survey study.

OBJECTIVE

The aim was to determine if health literacy level is associated with patient-reported outcomes and self-reported health status among patients presenting to an academic outpatient spine center.

SUMMARY OF BACKGROUND DATA

Patient reports are critical to assessing symptom severity and treatment success in orthopedic spine patients. Patient-reported outcome measures (PROMs) are important instruments commonly used for this purpose. However, the influence of patient health literacy on PROMs has not yet been given much consideration in spine literature.

MATERIALS AND METHODS

Consecutive English-speaking patients over the age of 18 years and new to our clinic verbally completed the Newest Vital Sign health literacy assessment tool and a sociodemographic survey, including self-reported health status. In addition, seven Patient-Reported Outcomes Measurement Information System scores were extracted from patient records. Regression modeling was performed with PROMs considered as dependent variables, health literacy level as the primary predictor, and all other factors (age, sex, race, ethnicity, native English speaker, highest educational degree, grade-level reading, marital status, employment status, annual household income, and type of insurance) as covariates.

RESULTS

Among the 318 included patients, 33% had limited health literacy. Adjusted regression analysis demonstrated that patients with limited health literacy had worse PROM scores across all seven domains (Physical Function: P =0.028; Depression: P =0.035; Global Health-Physical: P =0.001; Global Health-Mental: P =0.007; Pain Interference: P =0.036; Pain Intensity: P =0.002; Anxiety: P =0.047). In addition, patients with limited health literacy reported worse self-reported health status ( P <0.001).

CONCLUSIONS

Spine patients with limited health literacy have worse baseline PROM scores confounders and report worse general health. Further investigations are necessary to elucidate if limited health literacy is a marker or the root cause of these disparities. Findings from this study urge the consideration of patient health literacy when interpreting PROMs as well as the implications for patient assessment and discussion of treatment options.

Development and internal validation of machine learning algorithms for predicting complications after primary total hip arthroplasty

INTRODUCTION

Complications after total hip arthroplasty (THA) may result in readmission or reoperation and impose a significant cost on the healthcare system. Understanding which patients are at-risk for complications can potentially allow for targeted interventions to decrease complication rates through pursuing preoperative health optimization. The purpose of the current was to develop and internally validate machine learning (ML) algorithms capable of performing patient-specific predictions of all-cause complications within two years of primary THA.

METHODS

This was a retrospective case-control study of clinical registry data from 616 primary THA patients from one large academic and two community hospitals. The primary outcome was all-cause complications at a minimum of 2-years after primary THA. Recursive feature elimination was applied to identify preoperative variables with the greatest predictive value. Five ML algorithms were developed on the training set using tenfold cross-validation and internally validated on the independent testing set of patients. Algorithms were assessed by discrimination, calibration, Brier score, and decision curve analysis to quantify performance.

RESULTS

The observed complication rate was 16.6%. The stochastic gradient boosting model achieved the best performance with an AUC = 0.88, calibration intercept = 0.1, calibration slope = 1.22, and Brier score = 0.09. The most important factors for predicting complications were age, drug allergies, prior hip surgery, smoking, and opioid use. Individual patient-level explanations were provided for the algorithm predictions and incorporated into an open access digital application: https://sorg-apps.shinyapps.io/tha_complication/ CONCLUSIONS: The stochastic boosting gradient algorithm demonstrated good discriminatory capacity for identifying patients at high-risk of experiencing a postoperative complication and proof-of-concept for creating office-based applications from ML that can perform real-time prediction. However, this clinical utility of the current algorithm is unknown and definitions of complications broad. Further investigation on larger data sets and rigorous external validation is necessary prior to the assessment of clinical utility with respect to risk-stratification of patients undergoing primary THA.

LEVEL OF EVIDENCE

III, therapeutic study.

Development of machine-learning algorithms for 90-day and one-year mortality prediction in the elderly with femoral neck fractures based on the HEALTH and FAITH trials

To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials. This study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without), calibration (observed outcome compared to the predicted probability), and the Brier score (composite of discrimination and calibration). The developed algorithms distinguished between patients at high and low risk for 90-day and one-year mortality. The penalized logistic regression algorithm had the best performance metrics for both 90-day (c-statistic 0.80, calibration slope 0.95, calibration intercept -0.06, and Brier score 0.039) and one-year (c-statistic 0.76, calibration slope 0.86, calibration intercept -0.20, and Brier score 0.074) mortality prediction in the hold-out set. Using high-quality data, the ML-based prediction models accurately predicted 90-day and one-year mortality in patients aged 50 years or older with a FNF. The final models must be externally validated to assess generalizability to other populations, and prospectively evaluated in the process of shared decision-making.

Quality of Life in Chordoma Co-Survivors: Results from the Chordoma Foundation Survivorship Survey

INTRODUCTION

Chordomas are a rare form of aggressive bone cancer and are associated with poor quality of life (QOL). The present study sought to characterize demographic and clinical characteristics associated with QOL in chordoma co-survivors (caregivers of chordoma patients) and assess whether co-survivors are accessing care for QOL challenges.

METHODS

The Chordoma Foundation Survivorship Survey was electronically distributed to chordoma co-survivors. Survey questions assessed emotional/cognitive and social QOL, with significant QOL challenges being defined as experiencing >5 challenges within either of these domains. Fisher's exact test and the Mann-Whitney U test were used to analyze bivariate associations between patient/caretaker characteristics and QOL challenges.

RESULTS

Among the 229 respondents to our survey, nearly half (48.5%) reported a high number (>5) of emotional/cognitive QOL challenges. Co-survivors under 65 years of age were significantly more likely to experience a high number of emotional/cognitive QOL challenges (p<0.0001) while co-survivors greater than ten years past the end of treatment were significantly less likely to experience a high number of emotional/cognitive QOL (p=0.012). When asked about access to resources, a lack of knowledge of resources to address their emotional/cognitive and social QOL issues (34% and 35%, respectively) was the most common response.

CONCLUSION

Our findings suggest younger co-survivors are at high-risk for adverse emotional QOL outcomes. Additionally, over one-third of co-survivors did not know about resources to address their QOL issues. Our study may help guide organizational efforts to provide care and support to chordoma patients and their loved ones.

Prevalence of and factors associated with limited health literacy in spine patients

BACKGROUND

Limited health literacy exacerbates health inequity and has serious implications for patient care. It hinders successful communication and comprehension of relevant health information, which can lead to suboptimal care. Despite the evidence regarding the significance of health literacy, the topic has received little consideration in orthopedic spine patients.

PURPOSE

To investigate the prevalence of and factors associated with limited health literacy among outpatients presenting to a tertiary urban academic hospital-based orthopedic spine center.

STUDY DESIGN

Cross-sectionals.

PATIENT SAMPLE

Patients 18 years of age or older seen at a tertiary urban academic hospital-based multi-surgeon outpatient spine center.

OUTCOME MEASURES

The Newest Vital Sign (NVS) health literacy assessment.

METHODS

Between December 2021 and March 2022, 447 consecutive English-speaking patients over the age of 18 years and new to the outpatient spine clinic were approached for participation in a cross-sectional survey study, of which 405 agreed to participate. Patients completed the Newest Vital Sign (NVS) health literacy assessment tool, the Rapid Estimation of Adult Literacy in Medicine Short Form (REALM-SF), and a sociodemographic survey (including race/ethnicity, level of education, employment status, income, and marital status). The NVS scores were divided into limited (0-3) and adequate (4-6) health literacy. REALM-SF scores were classified into reading levels below ninth grade (0-6) or at least ninth grade (7). Additional demographic data was extracted from patient records. Online mapping tools were used to collect the Social Vulnerability Index (SVI) and the Area Deprivation Index (ADI) for each patient. Subsequently, multivariable regression modeling was performed to identify independent factors associated with limited health literacy.

RESULTS

The prevalence of limited health literacy in patients presenting to an urban academic outpatient spine center was 33% (135/405). Unadjusted analysis found that patients who were socioeconomically disadvantaged (eg, unemployed, lower household income, publicly insured and higher SVI) and had more unfavorable social determinant of health features (eg, housing concerns, higher ADI, less years of education, below ninth grade reading level, unmarried) had high rates of limited health literacy. Adjusted regression analysis demonstrated that limited health literacy was independently associated with higher ADI state decile, living less than 10 years at current address, having housing concerns, not being employed, non-native English speaking, having less years of education and below ninth grade reading level.

CONCLUSIONS

This study found that a substantial portion of the patients presenting to an outpatient spine center have limited health literacy, more so if they are socially disadvantaged. Future efforts should investigate the impact of limited health literacy on access to care, treatment outcomes and health care utilization in orthopedic patients. Neighborhood social vulnerability measures may be a feasible way to identify patients at risk of limited health literacy in clinical practice and offer opportunities for tailored patient care. This may contribute to prioritizing the mitigation of disparities and aid in the development of meaningful interventions to improve health equity in orthopedics.

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.

Social determinants of health in prognostic machine learning models for orthopaedic outcomes: A systematic review

RATIONAL

Social determinants of health (SDOH) are being considered more frequently when providing orthopaedic care due to their impact on treatment outcomes. Simultaneously, prognostic machine learning (ML) models that facilitate clinical decision making have become popular tools in the field of orthopaedic surgery. When ML-driven tools are developed, it is important that the perpetuation of potential disparities is minimized. One approach is to consider SDOH during model development. To date, it remains unclear whether and how existing prognostic ML models for orthopaedic outcomes consider SDOH variables.

OBJECTIVE

To investigate whether prognostic ML models for orthopaedic surgery outcomes account for SDOH, and to what extent SDOH variables are included in the final models.

METHODS

A systematic search was conducted in PubMed, Embase and Cochrane for studies published up to 17 November 2020. Two reviewers independently extracted SDOH features using the PROGRESS+ framework (place of residence, race/ethnicity, Occupation, gender/sex, religion, education, social capital, socioeconomic status, 'Plus+' age, disability, and sexual orientation).

RESULTS

The search yielded 7138 studies, of which 59 met the inclusion criteria. Across all studies, 96% (57/59) considered at least one PROGRESS+ factor during development. The most common factors were age (95%; 56/59) and gender/sex (96%; 57/59). Differential effect analyses, such as subgroup analysis, covariate adjustment, and baseline comparison, were rarely reported (10%; 6/59). The majority of models included age (92%; 54/59) and gender/sex (69%; 41/59) as final input variables. However, factors such as insurance status (7%; 4/59), marital status (7%; 4/59) and income (3%; 2/59) were seldom included.

CONCLUSION

The current level of reporting and consideration of SDOH during the development of prognostic ML models for orthopaedic outcomes is limited. Healthcare providers should be critical of the models they consider using and knowledgeable regarding the quality of model development, such as adherence to recognized methodological standards. Future efforts should aim to avoid bias and disparities when developing ML-driven applications for orthopaedics.

Prognostic Significance of Percentage and Size of Dedifferentiation in Dedifferentiated Chondrosarcoma

Dedifferentiated chondrosarcoma is rare, aggressive, and microscopically bimorphic. How pathologic features such as the amounts of dedifferentiation affect prognosis remains unclear. We evaluated the percentages and sizes of dedifferentiation in a consecutive institutional series of dedifferentiated chondrosarcomas from 1999 to 2021. The statistical analysis included cox proportional hazard models and log-rank tests. Of the 67 patients (26 women, 41 men; age, 39 to >89 [median 61] years; 2 with Ollier disease), 58 presented de novo; 9 were identified with conventional chondrosarcomas 0.6-13.2 years (median, 5.5 years) prior. Pathologic fracture and distant metastases were noted in 27 and 7 patients at presentation. The tumors involved the femur (n = 27), pelvis (n = 22), humerus (n = 7), tibia (n = 4), scapula/ribs (n = 4), spine (n = 2), and clivus (n = 1). In the 56 resections, the tumors ranged in size from 3.5 to 46.0 cm (median, 11.5 cm) and contained 1%-99.5% (median, 70%) dedifferentiated components that ranged in size from 0.6 to 24.0 cm (median, 7.3 cm). No correlation was noted between total size and percentage of dedifferentiation. The dedifferentiated components were typically fibrosarcomatous or osteosarcomatous, whereas the associated cartilaginous components were predominantly grade 1-2, rarely enchondromas or grade 3. The entire cohort's median overall survival and progression-free survival were 11.8 and 5.4 months, respectively. In the resected cohort, although the total size was not prognostic, the percentage of dedifferentiation ≥20% and size of dedifferentiation >3.0 cm each predicted worse overall survival (9.9 vs 72.5 months; HR, 3.76; 95% CI, 1.27-11.14; P = .02; 8.7 vs 58.9 months; HR, 3.03; 95% CI, 1.21-7.57; P = .02, respectively) and progression-free survival (5.3 vs 62.1 months; HR, 3.05; 95% CI, 1.13-8.28; P = .03; 5.3 vs 56.6 months; HR, 2.50; 95% CI, 1.06-5.88; P = .04, respectively). In conclusion, both the percentages and sizes of dedifferentiation were better prognostic predictors than total tumor sizes in dedifferentiated chondrosarcomas, highlighting the utility of their pathologic evaluations.

Transcriptional Profiling Supports the Notochordal Origin of Chordoma and Its Dependence on a TGFΒ1-TBXT Network

Chordoma is a rare malignant tumor demonstrating notochordal differentiation. It is dependent on brachyury (TBXT), a hallmark notochordal gene and transcription factor, and shares histologic features and the same anatomic location as the notochord. In this study, we perform a molecular comparison of chordoma and notochord to identify dysregulated cellular pathways. The lack of a molecular reference from appropriate control tissue limits our understanding of chordoma and its relationship to notochord. Accordingly, we conducted an unbiased comparison of chordoma, human notochord, and an atlas of normal and cancerous tissue using gene expression profiling to clarify the chordoma/notochord relationship and potentially identify novel drug targets. We found striking consistency in gene expression profiles between chordoma and notochord, supporting the hypothesis that chordoma develops from notochordal remnants. We identified a 12-gene diagnostic chordoma signature and found that the TBXT/transforming growth factor (TGF)-β/SOX6/SOX9 pathway is hyperactivated in the tumor, suggesting that pathways associated with chondrogenesis are a central driver of chordoma development. Experimental validation in chordoma cells confirms these findings and emphasizes the dependence of chordoma proliferation and survival on TGF-β. Our computational and experimental evidence provides the first molecular connection between notochord and chordoma and identifies core members of a chordoma regulatory pathway involving TBXT. This pathway provides new therapeutic targets for this unique malignant neoplasm and highlights TGF-β as a prime druggable candidate.

Intercontinental validation of a clinical prediction model for predicting 90-day and 2-year mortality in an Israeli cohort of 2033 patients with a femoral neck fracture aged 65 or above

PURPOSE

Mortality prediction in elderly femoral neck fracture patients is valuable in treatment decision-making. A previously developed and internally validated clinical prediction model shows promise in identifying patients at risk of 90-day and 2-year mortality. Validation in an independent cohort is required to assess the generalizability; especially in geographically distinct regions. Therefore we questioned, is the SORG Orthopaedic Research Group (SORG) femoral neck fracture mortality algorithm externally valid in an Israeli cohort to predict 90-day and 2-year mortality?

METHODS

We previously developed a prediction model in 2022 for estimating the risk of mortality in femoral neck fracture patients using a multicenter institutional cohort of 2,478 patients from the USA. The model included the following input variables that are available on clinical admission: age, male gender, creatinine level, absolute neutrophil, hemoglobin level, international normalized ratio (INR), congestive heart failure (CHF), displaced fracture, hemiplegia, chronic obstructive pulmonary disease (COPD), history of cerebrovascular accident (CVA) and beta-blocker use. To assess the generalizability, we used an intercontinental institutional cohort from the Sheba Medical Center in Israel (level I trauma center), queried between June 2008 and February 2022. Generalizability of the model was assessed using discrimination, calibration, Brier score, and decision curve analysis.

RESULTS

The validation cohort included 2,033 patients, aged 65 years or above, that underwent femoral neck fracture surgery. Most patients were female 64.8% (n = 1317), the median age was 81 years (interquartile range = 75-86), and 80.4% (n = 1635) patients sustained a displaced fracture (Garden III/IV). The 90-day mortality was 9.4% (n = 190) and 2-year mortality was 30.0% (n = 610). Despite numerous baseline differences, the model performed acceptably to the validation cohort on discrimination (c-statistic 0.67 for 90-day, 0.67 for 2-year), calibration, Brier score, and decision curve analysis.

CONCLUSIONS

The previously developed SORG femoral neck fracture mortality algorithm demonstrated good performance in an independent intercontinental population. Current iteration should not be relied on for patient care, though suggesting potential utility in assessing patients at low risk for 90-day or 2-year mortality. Further studies should evaluate this tool in a prospective setting and evaluate its feasibility and efficacy in clinical practice. The algorithm can be freely accessed: https://sorg-apps.shinyapps.io/hipfracturemortality/ .

LEVEL OF EVIDENCE

Level III, Prognostic study.

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.

Health Literacy in Orthopedic Surgery: A Systematic Review

Background: Limited health literacy has been associated with adverse health outcomes. Undergoing orthopedic surgery often requires patients to make complex decisions and adhere to complicated instructions, suggesting that health literacy skills might have a profound impact on orthopedic surgery outcomes. Purpose: We sought to review the literature for studies investigating the level of health literacy in patients undergoing orthopedic surgery and also to assess how those studies report factors affecting health equity. Methods: We conducted a systematic search of PubMed, Embase, and Cochrane Library for all health literacy studies published in the orthopedic surgery literature up to February 8, 2022. Search terms included synonyms for health literacy and for all orthopedic surgery subspecialties. Two reviewers independently extracted study data in addition to indicators of equity reporting using the PROGRESS+ checklist (Place of Residence, Race/Ethnicity, Occupation, Gender/sex, Religion, Education, Social capital, Socioeconomic status, plus age, disability, and sexual orientation). Results: The search resulted in 616 studies; 9 studies remained after exclusion criteria were applied. Most studies were of arthroplasty (4/9; 44%) or trauma (3/9; 33%) patients. Validated health literacy assessments were used in 4 of the included studies, and only 3 studies reported the rate of limited health literacy in the patients studied, which ranged between 34% and 38.5%. At least one PROGRESS+ item was reported in 88% (8/9) of the studies. Conclusions: We found a paucity of appropriately designed studies that used validated measures of health literacy in the field of orthopedic surgery. The potential impact of health literacy on orthopedic patients and their outcomes has yet to be elucidated. Thoughtful, high-quality trials across diverse demographics and geographies are warranted.

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.

Predictors of Symptomatic Venous Thromboembolism in Patients with Soft Tissue Sarcoma in the Lower Extremity

Orthopedic surgery and soft-tissue sarcoma (STS) both independently increase the risk of developing symptomatic venous thromboembolic events (SVTE), but there are no established risk factors or guidelines for how to prophylactically treat patients with STS undergoing surgery. The objectives of this study were to (1) identify the prevalence of SVTE in patients undergoing STS surgery, (2) identify risk factors for SVTE, and (3) determine the risk of wound complications associated with VTE prophylaxis. This retrospective study was conducted in a tertiary level, academic hospital. A total of 642 patients were treated for soft-tissue sarcoma in the lower extremity with follow up for at least 90 days for the development of SVTE such as deep venous thrombosis and pulmonary embolism. Multivariate logistic regression was used to identify predictors for these events by controlling for patient characteristics, surgical characteristics, and treatment variables, with significance held at p < 0.05. Twenty eight patients (4.36%) were diagnosed with SVTE. Multivariate analysis found six significant predictors ordered based on standardized coefficients: pre-operative (PTT) partial thromboplastin time (p < 0.001), post-operative PTT (p = 0.010), post-op chemotherapy (p = 0.013), metastasis at diagnosis (p = 0.025), additional surgery for metastasis or local recurrence (p = 0.004), and tumor size larger than 10 cm (p < 0.001). The risk of wound complications (p = 0.04) and infection (p = 0.017) increased significantly in patients who received chemical prophylaxis. Our study identifies risk factors for patients at increased risk of developing VTE. Further prospective research is necessary to identify which protocols would be beneficial in preventing SVTE in high-risk patients with a low profile of wound complications.

The impact of radiotherapy on survival after surgical resection of chordoma with minimum five-year follow-up

BACKGROUND CONTEXT

Local control remains a vexing problem in the management of chordoma despite advances in operative techniques and radiotherapy (RT) protocols. Existing studies show satisfactory local control rates with different treatment modalities. However, those studies with minimum follow-up more than 4 years demonstrate increasing rates of local failure. Therefore, mid-term local survival rates may be inadvertently elevated by studies with less than 4 years follow-up.

PURPOSE

The purpose of this study is to report the mid-term results of primary spinal chordoma treated with en bloc resection and proton-based RT with minimum 5 years of follow-up.

STUDY DESIGN/SETTING

Retrospective, single-center, cohort study.

PATIENT SAMPLE

Patients undergoing primary surgical excision of a spine or sacral chordoma tumor between 1990 and 2016 at a single-institution were included. Patients were included if they had a local failure at any time, or they had a minimum of 5 years of follow up with no local failure. Patients were excluded if a prior surgical excision was performed or metastases were present at the time of referral.

OUTCOME MEASURES

The outcome measures were local recurrence-free interval (LRFI) and overall survival (OS).

METHODS

Demographic, clinical, oncologic and surgical variables, including margin status, as well as radiation doses and schedule (neoadjuvant, adjuvant, or both) were compared using Wilcoxon rank-sum or chi-squared testing. The goal RT dose was 70 Gray (total) and patients were stratified based on completing (C70) or receiving incomplete (I70) dosing. Overall survival (OS) and local-recurrence free interval (LRFI) were calculated using the Kaplan-Meier method.

FUNDING STATEMENT

No funding was obtained for this work.

RESULTS

Seventy-six patients were included in the final analysis. All patients had a minimum of 5-year follow-up (median 9.3 years, range 5.1-24.7 years). There were no significant clinical differences between the C70 and I70 RT groups. OS was greater for the C70 RT group (5-year OS 82% vs. 63%, p=.001). There was similar OS for the positive margin group (5-year OS 70% vs. 61%, p=.266). LRFI was greater for the C70 RT group (5-year OS 93% vs. 78%, p=.017). There was similar LRFI for the positive margin group (5-year OS 90% versus 87%, p=.810).

CONCLUSION

Chordoma outcomes trend towards diminishing LRFI rates in the literature. Here we report the results of the operative management of primary spinal chordoma with minimum five year follow-up, the addition of C70 RT to surgical excision conferred a benefit to OS and local recurrence.

Reliability of self-reported health literacy screening in spine patients

BACKGROUND CONTEXT

Limited health literacy has previously been associated with increased health care utilization, worse general health status and self-reported health, and increased mortality. Identifying and accommodating patients with limited health literacy may offer an avenue towards mitigating adverse health outcomes and reduce unnecessary health care expenditure. Due to the challenges associated with implementation of lengthy health literacy assessments, the Brief Health Literacy Screening Instrument was developed. However, to our knowledge, there are no reports on the accuracy of this screening questionnaire, with or without the inclusion of sociodemographic characteristics, when predicting limited health literacy in orthopaedic spine patients.

PURPOSE

To evaluate the reliability and predictive accuracy of self-reported health literacy screening questions with and without the inclusion of sociodemographic variables in orthopaedic spine patients.

STUDY DESIGN

Cross-sectional.

PATIENT SAMPLE

Patients seen at a tertiary urban academic hospital-based multi-surgeon spine center OUTCOME MEASURES: Brief Health Literacy Screening Instrument (BRIEF), and the Newest Vital Sign (NVS) health literacy assessment tool.

METHODS

Between December 2021 and February 2022, consecutive English-speaking patients over the age of 18 presenting as new patients to an urban, hospital-based outpatient spine clinic were approached for participation. A sociodemographic survey, the BRIEF, and the NVS Health Literacy Assessment Tool were administered verbally. Simple and multivariable logistic regression was utilized to assess the accuracy of each BRIEF question individually, and collectively, at predicting limited health literacy as defined by the NVS. Further regression analysis included sociodemographic variables (age, body mass index, race, ethnicity, highest educational degree, employment status, marital status, annual household income, insurance status, and self-reported health.

RESULTS

A total of 262 patients [mean age (years), 57 ± 17] were included in this study. One hundred thirty-four (51%) were male, 223 (85%) were White, and 151 (58%) were married. Patient BRIEF scores were as follows: 23 (9%) limited, 43 (16%) marginal, and 196 (75%) adequate. NVS scores identified 87 (33%) patients with possible limited health literacy. BRIEF items collectively demonstrated fair accuracy in the prediction of limited health literacy (area under the receiver operating characteristic curve, 0.76; 95% CI, 0.70-0.82). Individually, the fourth BRIEF item ("How confident are you in filling out medical forms by yourself?") was the best predictor of limited health literacy (area under the receiver operating characteristic curve, 0.67; 95% CI, 0.60-0.73). The predictive accuracy of the BRIEF items, both individually and collectively, increased with the inclusion of sociodemographic variables within the logistic regression. Specific characteristics independently associated with limited health literacy were self-identified Black race, retired or disabled employment status, single or divorced marital status, high school education or below, and self-reported "poor" health.

CONCLUSIONS

Limited health literacy has implications for patient outcomes and health care costs. Our results show that the BRIEF questionnaire is a low-cost screening tool that demonstrates fair predictability in determining limited health literacy within a population of spine patients. Self-reported health literacy assessments may be more feasible in daily practice and easier to implement into clinical workflow.

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.

Tumor-induced osteomalacia treated with T12 tumor resection

Summary

Tumor-induced osteomalacia (TIO) is a rare form of osteomalacia caused by fibroblast growth factor-23 (FGF23)-secreting tumors. Most of these tumors are phosphaturic mesenchymal tumors (PMTs) typically involving soft tissue in the extremities and bone of the appendicular skeleton and cranium. We report the case of a 60-year-old woman with about 3 years of persistent bone pain and multiple fractures, initially diagnosed as osteoporosis, who was found to have hypophosphatemia with low 1,25-dihydroxyvitamin D and elevated alkaline phosphatase and inappropriately normal FGF23 consistent with TIO. Her symptoms improved with phosphate supplementation, vitamin D and calcitriol. 68Ga-DOTATATE imaging revealed a T12 vertebral body lesion confirmed on biopsy to be a PMT. She underwent resection of the PMT with resolution of TIO and increased bone density. This rare case of TIO secondary to a PMT of the thoracic spine highlights some of the common features of PMT-associated TIO and draws attention to PMT-associated TIO as a possible cause of unexplained persistent bone pain, a disease entity that often goes undiagnosed and untreated for years.

Learning points

Tumor-induced osteomalacia (TIO) is typically caused by phosphaturic mesenchymal tumors (PMTs) that are usually found in the soft tissue of the extremities and bone of the appendicular skeleton/cranium and rarely in the spine. TIO may be misdiagnosed as osteoporosis or spondyloarthritis, and the correct diagnosis is often delayed for years. However, osteoporosis, in the absence of fracture, is not associated with bone pain. The hallmark of TIO is hypophosphatemia with inappropriately normal or low 1,25-dihydroxyvitamin D and elevated or inappropriately normal fibroblast growth factor-23 (FGF23) levels. In patients with unexplained persistent bone pain, a serum phosphate should be measured. Consider PMT-associated TIO as a potential cause of unexplained persistent bone pain and hypophosphatemia. PMTs express somatostatin receptors and may be identified with 68Ga-DOTATATE imaging. Complete surgical resection is the preferred treatment for spinal PMTs associated with TIO.

Predictors of reoperation after surgery for spinal epidural abscess

BACKGROUND CONTEXT

Spinal epidural abscess is a rare but severe condition with high rates of postoperative adverse events.

PURPOSE

The objective of the study was to identify independent prognostic factors for reoperation using two datasets: an institutional and national database.

STUDY DESIGN/SETTING

Retrospective Review.

PATIENT SAMPLE

Database 1: Review of five medical centers from 1993 to 2016. Database 2: The National Surgical Quality Improvement Program (NSQIP) was queried between 2012 and 2016.

OUTCOME MEASURES

Thirty-day and ninety-day reoperation rate.

METHODS

Two independent datasets were reviewed to identify patients with spinal epidural abscesses undergoing spinal surgery. Multivariate analyses were used to determine independent prognostic factors for reoperation while including factors identified in bivariate analyses.

RESULTS

Overall, 642 patients underwent surgery for a spinal epidural abscess in the institutional cohort, with a 90-day unplanned reoperation rate of 19.9%. In the NSQIP database, 951 patients were identified with a 30-day unplanned reoperation rate of 12.3%. On multivariate analysis in the NSQIP database, cervical spine abscess was the only factor that reached significance for 30-day reoperation (OR=1.71, 95% CI=1.11-2.63, p=.02, Area under the curve (AUC)=0.61). On multivariate analysis in the institutional cohort, independent prognostic factors for 30-day reoperation were: preoperative urinary incontinence, ventral location of abscess relative to thecal sac, cervical abscess, preoperative wound infection, and leukocytosis (AUC=0.65). Ninety-day reoperation rate also found hypoalbuminemia as a significant predictor (AUC=0.66).

CONCLUSION

Six novel independent prognostic factors were identified for 90-day reoperation after surgery for a spinal epidural abscess. The multivariable analysis fairly predicts reoperation, indicating that there may be additional factors that need to be uncovered in future studies. The risk factors delineated in this study through the use of two large cohorts of spinal epidural abscess patients can be used to improve preoperative risk stratification and patient management.

Does the SORG Orthopaedic Research Group Hip Fracture Delirium Algorithm Perform Well on an Independent Intercontinental Cohort of Patients With Hip Fractures Who Are 60 Years or Older?

BACKGROUND

Postoperative delirium in patients aged 60 years or older with hip fractures adversely affects clinical and functional outcomes. The economic cost of delirium is estimated to be as high as USD 25,000 per patient, with a total budgetary impact between USD 6.6 to USD 82.4 billion annually in the United States alone. Forty percent of delirium episodes are preventable, and accurate risk stratification can decrease the incidence and improve clinical outcomes in patients. A previously developed clinical prediction model (the SORG Orthopaedic Research Group hip fracture delirium machine-learning algorithm) is highly accurate on internal validation (in 28,207 patients with hip fractures aged 60 years or older in a US cohort) in identifying at-risk patients, and it can facilitate the best use of preventive interventions; however, it has not been tested in an independent population. For an algorithm to be useful in real life, it must be valid externally, meaning that it must perform well in a patient cohort different from the cohort used to "train" it. With many promising machine-learning prediction models and many promising delirium models, only few have also been externally validated, and even fewer are international validation studies.

QUESTION/PURPOSE

Does the SORG hip fracture delirium algorithm, initially trained on a database from the United States, perform well on external validation in patients aged 60 years or older in Australia and New Zealand?

METHODS

We previously developed a model in 2021 for assessing risk of delirium in hip fracture patients using records of 28,207 patients obtained from the American College of Surgeons National Surgical Quality Improvement Program. Variables included in the original model included age, American Society of Anesthesiologists (ASA) class, functional status (independent or partially or totally dependent for any activities of daily living), preoperative dementia, preoperative delirium, and preoperative need for a mobility aid. To assess whether this model could be applied elsewhere, we used records from an international hip fracture registry. Between June 2017 and December 2018, 6672 patients older than 60 years of age in Australia and New Zealand were treated surgically for a femoral neck, intertrochanteric hip, or subtrochanteric hip fracture and entered into the Australian & New Zealand Hip Fracture Registry. Patients were excluded if they had a pathological hip fracture or septic shock. Of all patients, 6% (402 of 6672) did not meet the inclusion criteria, leaving 94% (6270 of 6672) of patients available for inclusion in this retrospective analysis. Seventy-one percent (4249 of 5986) of patients were aged 80 years or older, after accounting for 5% (284 of 6270) of missing values; 68% (4292 of 6266) were female, after accounting for 0.06% (4 of 6270) of missing values, and 83% (4690 of 5661) of patients were classified as ASA III/IV, after accounting for 10% (609 of 6270) of missing values. Missing data were imputed using the missForest methodology. In total, 39% (2467 of 6270) of patients developed postoperative delirium. The performance of the SORG hip fracture delirium algorithm on the validation cohort was assessed by discrimination, calibration, Brier score, and a decision curve analysis. Discrimination, known as the area under the receiver operating characteristic curves (c-statistic), measures the model's ability to distinguish patients who achieved the outcomes from those who did not and ranges from 0.5 to 1.0, with 1.0 indicating the highest discrimination score and 0.50 the lowest. Calibration plots the predicted versus the observed probabilities, a perfect plot has an intercept of 0 and a slope of 1. The Brier score calculates a composite of discrimination and calibration, with 0 indicating perfect prediction and 1 the poorest.

RESULTS

The SORG hip fracture algorithm, when applied to an external patient cohort, distinguished between patients at low risk and patients at moderate to high risk of developing postoperative delirium. The SORG hip fracture algorithm performed with a c-statistic of 0.74 (95% confidence interval 0.73 to 0.76). The calibration plot showed high accuracy in the lower predicted probabilities (intercept -0.28, slope 0.52) and a Brier score of 0.22 (the null model Brier score was 0.24). The decision curve analysis showed that the model can be beneficial compared with no model or compared with characterizing all patients as at risk for developing delirium.

CONCLUSION

Algorithms developed with machine learning are a potential tool for refining treatment of at-risk patients. If high-risk patients can be reliably identified, resources can be appropriately directed toward their care. Although the current iteration of SORG should not be relied on for patient care, it suggests potential utility in assessing risk. Further assessment in different populations, made easier by international collaborations and standardization of registries, would be useful in the development of universally valid prediction models. The model can be freely accessed at: https://sorg-apps.shinyapps.io/hipfxdelirium/ .

LEVEL OF EVIDENCE

Level III, therapeutic study.

Prognostic significance of lab data and performance comparison by validating survival prediction models for patients with spinal metastases after radiotherapy

BACKGROUND AND PURPOSE

Well-performing survival prediction models (SPMs) help patients and healthcare professionals to choose treatment aligning with prognosis. This retrospective study aims to investigate the prognostic impacts of laboratory data and to compare the performances of Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy (METSSS) model, New England Spinal Metastasis Score (NESMS), and Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) for spinal metastases (SM).

MATERIALS AND METHODS

From 2010 to 2018, patients who received radiotherapy (RT) for SM at a tertiary center were enrolled and the data were retrospectively collected. Multivariate logistic and Cox-proportional-hazard regression analyses were used to assess the association between laboratory values and survival. The area under receiver-operating characteristics curve (AUROC), calibration analysis, Brier score, and decision curve analysis were used to evaluate the performance of SPMs.

RESULTS

A total of 2786 patients were included for analysis. The 90-day and 1-year survival rates after RT were 70.4% and 35.7%, respectively. Higher albumin, hemoglobin, or lymphocyte count were associated with better survival, while higher alkaline phosphatase, white blood cell count, neutrophil count, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, or international normalized ratio were associated with poor prognosis. SORG-MLA has the best discrimination (AUROC 90-day, 0.78; 1-year 0.76), best calibrations, and the lowest Brier score (90-day 0.16; 1-year 0.18). The decision curve of SORG-MLA is above the other two competing models with threshold probabilities from 0.1 to 0.8.

CONCLUSION

Laboratory data are of prognostic significance in survival prediction after RT for SM. Machine learning-based model SORG-MLA outperforms statistical regression-based model METSSS model and NESMS in survival predictions.

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.

Can We Geographically Validate a Natural Language Processing Algorithm for Automated Detection of Incidental Durotomy Across Three Independent Cohorts From Two Continents?

BACKGROUND

Incidental durotomy is an intraoperative complication in spine surgery that can lead to postoperative complications, increased length of stay, and higher healthcare costs. Natural language processing (NLP) is an artificial intelligence method that assists in understanding free-text notes that may be useful in the automated surveillance of adverse events in orthopaedic surgery. A previously developed NLP algorithm is highly accurate in the detection of incidental durotomy on internal validation and external validation in an independent cohort from the same country. External validation in a cohort with linguistic differences is required to assess the transportability of the developed algorithm, referred to geographical validation. Ideally, the performance of a prediction model, the NLP algorithm, is constant across geographic regions to ensure reproducibility and model validity.

QUESTION/PURPOSE

Can we geographically validate an NLP algorithm for the automated detection of incidental durotomy across three independent cohorts from two continents?

METHODS

Patients 18 years or older undergoing a primary procedure of (thoraco)lumbar spine surgery were included. In Massachusetts, between January 2000 and June 2018, 1000 patients were included from two academic and three community medical centers. In Maryland, between July 2016 and November 2018, 1279 patients were included from one academic center, and in Australia, between January 2010 and December 2019, 944 patients were included from one academic center. The authors retrospectively studied the free-text operative notes of included patients for the primary outcome that was defined as intraoperative durotomy. Incidental durotomy occurred in 9% (93 of 1000), 8% (108 of 1279), and 6% (58 of 944) of the patients, respectively, in the Massachusetts, Maryland, and Australia cohorts. No missing reports were observed. Three datasets (Massachusetts, Australian, and combined Massachusetts and Australian) were divided into training and holdout test sets in an 80:20 ratio. An extreme gradient boosting (an efficient and flexible tree-based algorithm) NLP algorithm was individually trained on each training set, and the performance of the three NLP algorithms (respectively American, Australian, and combined) was assessed by discrimination via area under the receiver operating characteristic curves (AUC-ROC; this measures the model's ability to distinguish patients who obtained the outcomes from those who did not), calibration metrics (which plot the predicted and the observed probabilities) and Brier score (a composite of discrimination and calibration). In addition, the sensitivity (true positives, recall), specificity (true negatives), positive predictive value (also known as precision), negative predictive value, F1-score (composite of precision and recall), positive likelihood ratio, and negative likelihood ratio were calculated.

RESULTS

The combined NLP algorithm (the combined Massachusetts and Australian data) achieved excellent performance on independent testing data from Australia (AUC-ROC 0.97 [95% confidence interval 0.87 to 0.99]), Massachusetts (AUC-ROC 0.99 [95% CI 0.80 to 0.99]) and Maryland (AUC-ROC 0.95 [95% CI 0.93 to 0.97]). The NLP developed based on the Massachusetts cohort had excellent performance in the Maryland cohort (AUC-ROC 0.97 [95% CI 0.95 to 0.99]) but worse performance in the Australian cohort (AUC-ROC 0.74 [95% CI 0.70 to 0.77]).

CONCLUSION

We demonstrated the clinical utility and reproducibility of an NLP algorithm with combined datasets retaining excellent performance in individual countries relative to algorithms developed in the same country alone for detection of incidental durotomy. Further multi-institutional, international collaborations can facilitate the creation of universal NLP algorithms that improve the quality and safety of orthopaedic surgery globally. The combined NLP algorithm has been incorporated into a freely accessible web application that can be found at https://sorg-apps.shinyapps.io/nlp_incidental_durotomy/ . Clinicians and researchers can use the tool to help incorporate the model in evaluating spine registries or quality and safety departments to automate detection of incidental durotomy and optimize prevention efforts.

LEVEL OF EVIDENCE

Level III, diagnostic study.

Chondroitin sulfate proteoglycan 4 expression in chondrosarcoma: A potential target for antibody-based immunotherapy

Chondrosarcoma is a common primary bone malignancy whose phenotype increases with its histologic grade. They are relatively resistant to chemotherapy and radiation therapy limiting curative options for disseminated disease. Chondroitin sulfate proteoglycan 4 (CSPG4) is a cell surface proteoglycan that is highly expressed across various human cancers, including chondrosarcoma, and has restricted distribution in healthy tissues, making it an attractive target for the antibody-based therapy. CSPG4 specific chimeric antigen receptor (CAR) T cell therapies have been shown to be effective in treating other cancers such as melanoma and triple negative breast cancer. The goal of this study was to assess the prevalence of CSPG4 in human chondrosarcoma and to assess the efficacy of CSPG4 specific CAR T cells in lysing chondrosarcoma cells in vitro. Using immunohistochemistry (IHC), we stained a tissue microarray containing primary conventional and dedifferentiated chondrosarcoma from 76 patients with CSPG4 specific monoclonal antibodies (mAbs). In addition, we incubated 2 chondrosarcoma cell lines with CSPG4-targeting CAR T cells and subsequently evaluated cell survival. Our results showed medium to high expression of CSPG4 in 29 of 41 (71%) conventional chondrosarcoma tumors and in 3 of 20 (15%) dedifferentiated chondrosarcoma tumors. CSPG4 expression showed a positive association with time to metastasis and survival in both subtypes. CSPG4 CAR T treated cell lines showed a lysis of respectively >80% and 70% demonstrating CSPG4-targeted CAR T cells effective in killing CSPG4-positive chondrosarcoma tumors.

Preoperative embolization in surgical treatment of spinal metastases originating from non-hypervascular primary tumors: a propensity score matched study using 495 patients

BACKGROUND CONTEXT

Preoperative embolization (PE) reduces intraoperative blood loss during surgery for spinal metastases of hypervascular primary tumors such as thyroid and renal cell tumors. However, most spinal metastases originate from primary breast, prostate, and lung tumors and it remains unclear whether these and other spinal metastases benefit from PE.

PURPOSE

To assess the (1) efficacy of PE on the amount of intraoperative blood loss and safety in patients with spinal metastases originating from non-hypervascular primary tumors, and (2) secondary outcomes including perioperative allogeneic blood transfusion, anesthesia time, hospitalization, postoperative complication within 30 days, reoperation, 90-day mortality, and 1-year mortality.

STUDY DESIGN

Retrospective propensity-score matched, case-control study at 2 academic tertiary medical centers.

PATIENT SAMPLE

Patients 18 years of age or older undergoing surgery for spinal metastases originating from primary non-thyroid, non-renal cell, and non-hepatocellular tumors between January 1, 2002 and December 31, 2016 were included.

OUTCOME MEASURES

The primary outcomes were estimated amount of intraoperative blood loss and complications attributable to PE, such as neurologic injury, wound infection, thrombosis, or dissection. The secondary outcomes included perioperative allogeneic blood transfusion, anesthesia time, hospitalization, postoperative complication within 30 days, reoperation, 90-day mortality, and 1-year mortality.

METHODS

In total, 495 patients were identified, of which 54 (11%) underwent PE. After propensity score matching on 21 variables, including primary tumor, number of spinal levels, and surgical treatment, 53 non-PE patients were matched to 53 PE patients. Matching was adequate measured by comparing the matched variables, testing the standardized mean differences (<0.25), and inspecting Kernel density plots. The degree of embolization was noted to be complete, until stasis, or successful in 43 (80%) patients.

RESULTS

Intraoperative blood loss did not differ between both groups with a median blood loss in liters of 0.6 (IQR, 0.4-1.2) for non-PE patients and 0.9 (IQR, 0.6-1.2) for PE patients (p=.32). No complications occurred during embolization or the time between embolization and surgery. No differences were found in terms of the secondary outcomes.

CONCLUSIONS

Our data suggest that, although no complications occurred and the embolization procedure can be considered safe, patients with non-hypervascular spinal metastases might not benefit from PE. A larger, prospective study could confirm or refute these study findings and aid in elucidating a subset of spinal metastases that might benefit from PE.

Surgical Intervention is Associated With Improvements in the ASIA Impairment Scale in Gunshot-induced Spinal Injuries of the Thoracic and Lumbar Spine

STUDY DESIGN

Retrospective cohort study of patients from the National Spinal Cord Injury Statistical Center (NSCISC).

OBJECTIVE

The aim was to compare the outcomes of patients with gunshot-induced spinal injuries (GSIs) treated operatively and nonoperatively.

SUMMARY OF BACKGROUND DATA

The treatment of neurological deficits associated with gunshot wounds to the spine has been controversial. Treatment has varied widely, ranging from nonoperative to aggressive surgery.

METHODS

Patient demographics, clinical information, and outcomes were extracted. Surgical intervention was defined as a "laminectomy, neural canal restoration, open reduction, spinal fusion, or internal fixation of the spine." The primary outcome was the American Spinal Injury Association (ASIA) Impairment Scale. Statistical comparisons of baseline demographics and neurological outcomes between operative and nonoperative cohorts were performed.

RESULTS

In total, 961 patients with GSI and at least 1-year follow-up were identified from 1975 to 2015. The majority of patients were Black/African American (55.6%), male (89.7%), and 15-29 years old (73.8%). Of those treated surgically (19.7% of all patients), 34.2% had improvement in their ASIA Impairment Scale score at 1 year, compared with 20.6% treated nonoperatively. Overall, surgery was associated with a 2.0 [95% confidence interval (CI): 1.4-2.8] times greater likelihood of ASIA Impairment Scale improvement at 1 year. Specifically, benefit was seen in thoracic (odds ratio: 2.5; 95% CI: 1.4-4.6) and lumbar injuries (odds ratio: 1.7; 95% CI: 1.1-3.1), but not cervical injuries.

CONCLUSIONS

While surgical indications are always determined on an individualized basis, in our review of GSIs, surgical intervention was associated with a greater likelihood of neurological recovery. Specifically, patients with thoracic and lumbar GSIs had a 2.5 and 1.7-times greater likelihood of improvement in their ASIA Impairment Scale score 1 year after injury, respectively, if they underwent surgical intervention.

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.

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.