Racial Differences in Perioperative Complications, Readmissions, and Mortalities After Elective Spine Surgery in the United States: A Systematic Review Using AI-Assisted Bibliometric Analysis.

STUDY DESIGN: Systematic Review and Meta-analysis. OBJECTIVES: To evaluate the impact of race on post-operative outcomes and complications following elective spine surgery in the United States. METHODS: PUBMED, MEDLINE(R), ERIC, EMBASE, and SCOPUS were searched for studies documenting peri-operative events for White and African American (AA) patients following elective spine surgery. Pooled odds ratios were calculated for each 90-day outcome and meta-analyses were performed for 4 peri-operative events and 7 complication categories. Sub-analyses were performed for each outcome on single institution (SI) studies and works that included <100,000 patients. RESULTS: 53 studies (5,589,069 patients, 9.8% AA) were included. Eleven included >100,000 patients. AA patients had increased rates of 90-day readmission (OR 1.33, P = .0001), non-routine discharge (OR 1.71, P = .0001), and mortality (OR 1.66, P = .0003), but not re-operation (OR 1.16, P = .1354). AA patients were more likely to have wound-related complications (OR 1.47, P = .0001) or medical complications (OR 1.35, P = .0006), specifically cardiovascular (OR 1.33, P = .0126), deep vein thrombosis/pulmonary embolism (DVT/PE) (OR 2.22, P = .0188) and genitourinary events (OR 1.17, P = .0343). SI studies could only detect racial differences in re-admissions and non-routine discharges. Studies with <100,000 patients replicated the above findings but found no differences in cardiovascular complications. Disparities in mortality were only detected when all studies were included. CONCLUSIONS: AA patients faced a greater risk of morbidity across several distinct categories of peri-operative events. SI studies can be underpowered to detect more granular complication types (genitourinary, DVT/PE). Rare events, such as mortality, require larger sample sizes to identify significant racial disparities.

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.

Health Literacy in Orthopaedics.

Health literacy is a dynamic, multifaceted skill set that relies on patients, healthcare providers, and the healthcare system. In addition, health literacy assessment provides an avenue for evaluating patient understanding and offers insights into their health management capabilities. Inadequate health literacy results in poor patient outcomes and compromised care by considerably hindering successful communication and comprehension of relevant health information between the patient and the provider. In this narrative review, we explore why limited health literacy poses serious implications for orthopaedic patient health and safety, expectations, treatment outcomes, and healthcare costs. Furthermore, we elaborate on the complexity of health literacy, provide an overview of key concepts, and offer recommendations for clinical practice and research investigations.

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.

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.

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.

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.

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 (ß = -4.52 [95% CI -5.45 to -3.59]; p < 0.001), trouble paying for medications (ß = -4.55 [95% CI -5.55 to -3.54]; p < 0.001), Medicaid insurance (ß = -5.81 [95% CI -6.41 to -5.20]; p < 0.001), and workers compensation insurance (ß = -5.99 [95% CI -7.65 to -4.34]; p < 0.001) were associated with clinically worse function at presentation. Trouble paying for medications (ß = -6.01 [95% CI -7.10 to -4.92]; p < 0.001), Medicaid insurance (ß = -5.35 [95% CI -6.00 to -4.69]; p < 0.001), and workers compensation (ß = -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.

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.

Quality assessment of machine learning models for diagnostic imaging in orthopaedics: A systematic review.

BACKGROUND: Machine learning (ML) models are emerging at a rapid pace in orthopaedic imaging due to their ability to facilitate timely diagnostic and treatment decision making. However, despite a considerable increase in model development and ML-related publications, there has been little evaluation regarding the quality of these studies. In order to successfully move forward with the implementation of ML models for diagnostic imaging in orthopaedics, it is imperative that we ensure models are held at a high standard and provide applicable, reliable and accurate results. Multiple reporting guidelines have been developed to help authors and reviewers of ML models, such as the Checklist for AI in Medical Imaging (CLAIM) and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Previous investigations of prognostic orthopaedic ML models have reported concerns with regard to the rate of transparent reporting. Therefore, an assessment of whether ML models for diagnostic imaging in orthopaedics adequately and clearly report essential facets of their model development is warranted. PURPOSES: To evaluate (1) the completeness of the CLAIM checklist and (2) the risk of bias according to the QUADAS-2 tool for ML-based orthopaedic diagnostic imaging models. This study sought to identify ML details that researchers commonly fail to report and to provide recommendations to improve reporting standards for diagnostic imaging ML models. METHODS: A systematic review was performed to identify ML-based diagnostic imaging models in orthopaedic surgery. Articles published within the last 5 years were included. Two reviewers independently extracted data using the CLAIM checklist and QUADAS-2 tool, and discrepancies were resolved by discussion with at least two additional reviewers. RESULTS: After screening 7507 articles, 91 met the study criteria. The mean completeness of CLAIM items was 63 % (SD ± 28 %). Among the worst reported CLAIM items were item 28 (metrics of model performance), item 13 (the handling of missing data) and item 9 (data preprocessing steps), with only 2 % (2/91), 8 % (7/91) and 13 % (12/91) of studies correctly reporting these items, respectively. The QUADAS-2 tool revealed that the patient selection domain was at the highest risk of bias: 18 % (16/91) of studies were at high risk of bias and 32 % (29/91) had an unknown risk of bias. CONCLUSIONS: This review demonstrates that the reporting of relevant information, such as handling missing data and data preprocessing steps, by diagnostic ML studies for orthopaedic imaging studies is limited. Additionally, a substantial number of works were at high risk of bias. Future studies describing ML-based models for diagnostic imaging should adhere to acknowledged methodological standards to maximize the quality and applicability of their models.

Machine learning prediction models in orthopedic surgery: A systematic review in transparent reporting.

Machine learning (ML) studies are becoming increasingly popular in orthopedics but lack a critically appraisal of their adherence to peer-reviewed guidelines. The objective of this review was to (1) evaluate quality and transparent reporting of ML prediction models in orthopedic surgery based on the transparent reporting of multivariable prediction models for individual prognosis or diagnosis (TRIPOD), and (2) assess risk of bias with the Prediction model Risk Of Bias ASsessment Tool. A systematic review was performed to identify all ML prediction studies published in orthopedic surgery through June 18th, 2020. After screening 7138 studies, 59 studies met the study criteria and were included. Two reviewers independently extracted data and discrepancies were resolved by discussion with at least two additional reviewers present. Across all studies, the overall median completeness for the TRIPOD checklist was 53% (interquartile range 47%-60%). The overall risk of bias was low in 44% (n = 26), high in 41% (n = 24), and unclear in 15% (n = 9). High overall risk of bias was driven by incomplete reporting of performance measures, inadequate handling of missing data, and use of small datasets with inadequate outcome numbers. Although the number of ML studies in orthopedic surgery is increasing rapidly, over 40% of the existing models are at high risk of bias. Furthermore, over half incompletely reported their methods and/or performance measures. Until these issues are adequately addressed to give patients and providers trust in ML models, a considerable gap remains between the development of ML prediction models and their implementation in orthopedic practice.

Clinical Outcome Differences in the Treatment of Impending Versus Completed Pathological Long-Bone Fractures.

BACKGROUND: The outcome differences following surgery for an impending versus a completed pathological fracture have not been clearly defined. The purpose of the present study was to assess differences in outcomes following the surgical treatment of impending versus completed pathological fractures in patients with long-bone metastases in terms of (1) 90-day and 1-year survival and (2) intraoperative blood loss, perioperative blood transfusion, anesthesia time, duration of hospitalization, 30-day postoperative systemic complications, and reoperations. METHODS: We retrospectively performed a matched cohort study utilizing a database of 1,064 patients who had undergone operative treatment for 462 impending and 602 completed metastatic long-bone fractures. After matching on 22 variables, including primary tumor, visceral metastases, and surgical treatment, 270 impending pathological fractures were matched to 270 completed pathological fractures. The primary outcome was assessed with the Cox proportional hazard model. The secondary outcomes were assessed with the McNemar test and the Wilcoxon signed-rank test. RESULTS: The 90-day survival rate did not differ between the groups (HR, 1.13 [95% CI, 0.81 to 1.56]; p = 0.48), but the 1-year survival rate was worse for completed pathological fractures (46% versus 38%) (HR, 1.28 [95% CI, 1.02 to 1.61]; p = 0.03). With regard to secondary outcomes, completed pathological fractures were associated with higher intraoperative estimated blood loss (p = 0.03), a higher rate of perioperative blood transfusions (p = 0.01), longer anesthesia time (p = 0.04), and more reoperations (OR, 2.50 [95% CI, 1.92 to 7.86]; p = 0.03); no differences were found in terms of the rate of 30-day postoperative complications or the duration of hospitalization. CONCLUSIONS: Patients undergoing surgery for impending pathological fractures had lower 1-year mortality rates and better secondary outcomes as compared with patients undergoing surgery for completed pathological fractures when accounting for 22 covariates through propensity matching. Patients with an impending pathological fracture appear to benefit from prophylactic stabilization as stabilizing a completed pathological fracture seems to be associated with increased mortality, blood loss, rate of blood transfusions, duration of surgery, and reoperation risk. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review.

Background and purpose - External validation of machine learning (ML) prediction models is an essential step before clinical application. We assessed the proportion, performance, and transparent reporting of externally validated ML prediction models in orthopedic surgery, using the Transparent Reporting for Individual Prognosis or Diagnosis (TRIPOD) guidelines.Material and methods - We performed a systematic search using synonyms for every orthopedic specialty, ML, and external validation. The proportion was determined by using 59 ML prediction models with only internal validation in orthopedic surgical outcome published up until June 18, 2020, previously identified by our group. Model performance was evaluated using discrimination, calibration, and decision-curve analysis. The TRIPOD guidelines assessed transparent reporting.Results - We included 18 studies externally validating 10 different ML prediction models of the 59 available ML models after screening 4,682 studies. All external validations identified in this review retained good discrimination. Other key performance measures were provided in only 3 studies, rendering overall performance evaluation difficult. The overall median TRIPOD completeness was 61% (IQR 43-89), with 6 items being reported in less than 4/18 of the studies.Interpretation - Most current predictive ML models are not externally validated. The 18 available external validation studies were characterized by incomplete reporting of performance measures, limiting a transparent examination of model performance. Further prospective studies are needed to validate or refute the myriad of predictive ML models in orthopedics while adhering to existing guidelines. This ensures clinicians can take full advantage of validated and clinically implementable ML decision tools.

Augmented and virtual reality in spine surgery, current applications and future potentials.

BACKGROUND CONTEXT: The field of artificial intelligence (AI) is rapidly advancing, especially with recent improvements in deep learning (DL) techniques. Augmented (AR) and virtual reality (VR) are finding their place in healthcare, and spine surgery is no exception. The unique capabilities and advantages of AR and VR devices include their low cost, flexible integration with other technologies, user-friendly features and their application in navigation systems, which makes them beneficial across different aspects of spine surgery. Despite the use of AR for pedicle screw placement, targeted cervical foraminotomy, bone biopsy, osteotomy planning, and percutaneous intervention, the current applications of AR and VR in spine surgery remain limited. PURPOSE: The primary goal of this study was to provide the spine surgeons and clinical researchers with the general information about the current applications, future potentials, and accessibility of AR and VR systems in spine surgery. STUDY DESIGN/SETTING: We reviewed titles of more than 250 journal papers from google scholar and PubMed with search words: augmented reality, virtual reality, spine surgery, and orthopaedic, out of which 89 related papers were selected for abstract review. Finally, full text of 67 papers were analyzed and reviewed. METHODS: The papers were divided into four groups: technological papers, applications in surgery, applications in spine education and training, and general application in orthopaedic. A team of two reviewers performed paper reviews and a thorough web search to ensure the most updated state of the art in each of four group is captured in the review. RESULTS: In this review we discuss the current state of the art in AR and VR hardware, their preoperative applications and surgical applications in spine surgery. Finally, we discuss the future potentials of AR and VR and their integration with AI, robotic surgery, gaming, and wearables. CONCLUSIONS: AR and VR are promising technologies that will soon become part of standard of care in spine surgery.

Postoperative adverse events secondary to iatrogenic vascular injury during anterior lumbar spinal surgery.

BACKGROUND: Anterior lumbar spine surgery (ALSS) requires mobilization of the great vessels, resulting in a high risk of iatrogenic vascular injury (VI). It remains unclear whether VI is associated with increased risk of postoperative complications and other related adverse outcomes. PURPOSE: The purpose of this study was to (1) assess the incidence of postoperative complications attributable to VI during ALSS, and (2) outcomes secondary to VI such as procedural blood loss, transfusion of blood products, length of stay (LOS), and in hospital mortality. STUDY DESIGN: Retrospective propensity-score matched, case-control study at 2 academic and 3 community medical centers, PATIENT SAMPLE: Patients 18 years of age or older, undergoing ALSS between January 1st, 2000 and July 31st, 2019 were included in this analysis. OUTCOME MEASURES: The primary outcome was the incidence of postoperative complications attributable to VI, such as venous thromboembolism, compartment syndrome, transfusion reaction, limb ischemia, and reoperations. The secondary outcomes included estimated operative blood loss (milliliter), transfused blood products, LOS (days), and in-hospital mortality. METHODS: In total, 1,035 patients were identified, of which 75 (7.2%) had a VI. For comparative analyses, the 75 VI patients were paired with 75 comparable non-VI patients by propensity-score matching. The adequacy of the matching was assessed by testing the standardized mean differences (SMD) between VI and non-VI group (>0.25 SMD). RESULTS: Two patients (2.7%) had VI-related postoperative complications in the studied period, which consisted of two deep venous thromboembolisms (DVTs) occurring on day 3 and 7 postoperatively. Both DVTs were located in the distal left common iliac vein (CIV). The VI these patients suffered were to the distal inferior vena cava and the left CIV, respectively. Both patients did not develop additional complications in consequence of their DVTs, however, did require systemic anticoagulation and placement of an inferior vena cava filter. There was no statistical difference with the non-VI group where no instances (0%) of postoperative complications were reported (p=.157). No differences were found in LOS or in hospital mortality between the two groups (p=.157 and p=.999, respectively). Intraoperative blood loss and blood transfusion were both found to be higher in the VI group in comparison to the non-VI group (650 mL, interquartile range [IQR] 300-1400 vs. 150 mL, IQR 50-425, p≤.001; 0 units, IQR 0-3 vs. 0 units, IQR 0-1, p=.012, respectively). CONCLUSION: This study found a low number of serious postoperative complications related to VI in ALSS. In addition, these complications were not significantly different between the VI and matched non-VI ALSS cohort. Although not significant, the found DVT incidence of 2.7% after VI in ALSS warrants vigilance and preventive measures during the postoperative course of these patients.

Off-Hour Surgery Among Orthopedic Subspecialties at an Urban, Quaternary-Care, Level 1 Trauma Center.

PURPOSE: We sought to determine and quantify which subspecialties of orthopedic surgeons are operating off hours in an urban, quaternary-care, level 1 trauma center. MATERIALS AND METHODS: We used our clinical registry to identify 43,211 orthopedic surgeries performed between January 2008 and December 2011. Our outcome measures were the number and proportion of off-hour surgeries performed as well as the number and proportion of off-hours per subspecialty. The denominators were the total number of surgeries and the total number of surgical hours worked per subspecialty. Subspecialties-based on the primary surgeon who performed the surgery-were arthroplasty, foot and ankle, hand, pediatrics, shoulder, spine, sports, orthopedic trauma, and orthopedic oncology. RESULTS: A total of 2,431 (5.6%) surgeries were off-hours; the overall ratio of off-hour to on-hour surgeries was 1 to 17. There was a difference in the proportion of off-hour surgeries performed among orthopedic subspecialties: trauma (ratio, 1:5) and pediatric specialists (ratio, 1:5) had the lowest ratio, and shoulder (ratio, 1:152) and sports (ratio, 1:98) specialists the highest. The total number of surgical hours among all specialties was 59,026; of these hours, 3,833 (6.5%) were off-hour. The ratio of off-hour to on-hour surgical hours was 1 to 14. There was a difference in proportion of hours worked off-hour among orthopedic subspecialties; the ratios were greatest for trauma (1:5) and hand (1:5) specialists and the least for shoulder (1:157) and sports (1:92) specialists. Seven percent of hand surgery cases were off-hour, and 16% of the total surgical hours worked by hand surgeons were off-hour. CONCLUSIONS: In an urban, academic, level 1 trauma and microvascular replantation regional referral hospital, there is a large difference in off-hour surgical volume and duration among orthopedic subspecialties: trauma, pediatric, and hand surgeons performed more off-hour work than their colleagues, with hand and pediatric surgeons the most likely to be working at night. CLINICAL RELEVANCE: These data can inform how we organize, value, and incentivize off-hour care.