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Background National databases are being used with increasing frequency to conduct orthopaedic research. However, there are important differences in these databases, which could result in different answers to similar questions; this important potential limitation pertaining to database research in orthopaedic surgery has not been adequately explored. Questions/purposes The purpose of this study was to explore the interdatabase reliability of two commonly used national databases, the Nationwide Inpatient Sample (NIS) and the National Surgical Quality Improvement Program (NSQIP), in terms of (1) demographics; (2) comorbidities; and (3) adverse events. In addition, using the NSQIP database, we identified (4) adverse events that had a higher prevalence after rather than before discharge, which has important implications for interpretation of studies conducted in the NIS. Methods A retrospective cohort study of patients undergoing operative stabilization of transcervical and intertrochanteric hip fractures during 2009 to 2011 was performed in the NIS and NSQIP. Totals of 122,712 and 5021 patients were included from the NIS and NSQIP, respectively. Age, sex, fracture type, and lengths of stay were compared. Comorbidities common to both databases were compared in terms of more or less than twofold difference between the two databases. Similar comparisons were made for adverse events. Finally, adverse events that had a greater postdischarge prevalence were identified from the NSQIP database. Tests for statistical difference were thought to be of little value given the large sample size and the resulting fact that statistical differences would have been identified even for small, clinically inconsequential differences resulting from the associated high power. Because it is of greater clinical importance to focus on the magnitude of differences, the databases were compared by absolute differences. Results Demographics and hospital lengths of stay were not different between the two databases. In terms of comorbidities, the prevalences of nonmorbid obesity, coagulopathy, and anemia in found in the NSQIP were more than twice those in the NIS; the prevalence of peripheral vascular disease in the NIS was more than twice that in the NSQIP. Four other comorbidities had prevalences that were not different between the two databases. In terms of inpatient adverse events, the frequencies of acute kidney injury and urinary tract infection in the NIS were more than twice those in the NSQIP. Ten other inpatient adverse events had frequencies that were not different between the two databases. Because it does not collect data after patient discharge, it can be implied from the NSQIP data that the NIS does not capture more than ½ of the deaths and surgical site infections occurring during the first 30 postoperative days. Conclusions This study shows that two databases commonly used in orthopaedic research can identify similar populations of operative patients but may generate very different results for specific commonly studied comorbidities and adverse events. The NSQIP identified higher rates of morbid obesity, coagulopathy, and anemia. The NIS identified higher rates of peripheral vascular disease, acute kidney injury, and urinary tract infection. Level of Evidence Level II, prognostic study. See the Instructions for Authors for a complete description of levels of evidence.

Background Ankle fractures are common and can be associated with severe morbidity. Risk factors for short-term adverse events and readmission after open reduction and internal fixation (ORIF) of ankle fractures have not been fully characterized. Questions/purposes The purpose of our study was to determine patient rates and risk factors for (1) any adverse event; (2) severe adverse events; (3) infectious complications; and (4) readmission after ORIF of ankle fractures. Methods Patients who underwent ORIF for ankle fracture from 2005 to 2012 were identified in the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP ® ) database using International Classification of Diseases, 9 th Revision and Current Procedural Terminology codes. Patients with missing perioperative data were excluded from this study. Patient characteristics were tested for association with any adverse event, severe adverse events, infectious complications, and readmission using bivariate and multivariate logistic regression analyses. Results Of the 4412 patients identified, 5% had an adverse event. Any adverse event was associated with insulin-dependent diabetes mellitus (IDDM; odds ratio [OR], 2.05; 95% confidence interval [CI], 1.35–3.1; p = 0.001), age ≥ 60 years (OR, 1.97; 95% CI, 1.22–3.2; p = 0.006), American Society of Anesthesiologists classification ≥ 3 (OR, 1.69; 95% CI, 1.2–2.37; p = 0.002), bimalleolar fracture (OR, 1.6; 95% CI, 1.08–2.37; p = 0.020), hypertension (OR, 1.47; 95% CI, 1.04–2.09; p = 0.031), and dependent functional status (OR, 1.47; 95% CI, 1.02–2.14; p = 0.040) on multivariate analysis. Severe adverse events occurred in 3.56% and were associated with ASA classification ≥ 3 (OR, 2.01; p = 0.001), pulmonary disease (OR, 1.9; p = 0.004), dependent functional status (OR, 1.8; p = 0.005), and hypertension (OR, 1.65; p = 0.021). Infectious complications occurred in 1.75% and were associated with IDDM (OR, 3.51; p < 0.001), dependent functional status (OR, 2.4; p = 0.002), age ≥ 60 years (OR, 2.28; p = 0.028), and bimalleolar fracture (OR, 2.19; p = 0.030). Readmission occurred in 3.17% and was associated with ASA classification ≥ 3 (OR, 2.01; p = 0.017). Conclusions IDDM was associated with an increased rate of adverse events after ankle fracture ORIF, whereas noninsulin-dependent diabetes mellitus was not. IDDM management deserves future study, particularly with respect to glycemic control, a potential confounder that could not be assessed with the ACS-NSQIP registry. Increased ASA class was associated with readmission, and future prospective investigations should evaluate the effectiveness of increasing the discharge threshold, discharging to extended-care facilities, and/or home nursing evaluations in this at-risk population. Level of Evidence Level III, prognostic study.

PurposeSurgical treatment of herniated lumbar intervertebral disks is a common procedure worldwide. However, recurrent herniated nucleus pulposus (re-HNP) may develop, complicating outcomes and patient management. The purpose of this study was to utilize machine-learning (ML) analytics to predict lumbar re-HNP, whereby a personalized risk prediction can be developed as a clinical tool.MethodsA retrospective, single center study was conducted of 2630 consecutive patients that underwent lumbar microdiscectomy (mean follow-up: 22-months). Various preoperative patient pain/disability/functional profiles, imaging parameters, and anthropomorphic/demographic metrics were noted. An Extreme Gradient Boost (XGBoost) classifier was implemented to develop a predictive model identifying patients at risk for re-HNP. The model was exported to a web application software for clinical utility.ResultsThere were 1608 males and 1022 females, 114 of whom experienced re-HNP. Primary herniations were central (65.8%), paracentral (17.6%), and far lateral (17.1%). The XGBoost algorithm identified multiple re-HNP predictors and was incorporated into an open-access web application software, identifying patients at low or high risk for re-HNP. Preoperative VAS leg, disability, alignment parameters, elevated body mass index, symptom duration, and age were the strongest predictors.ConclusionsOur predictive modeling via an ML approach of our large-scale cohort is the first study, to our knowledge, that has identified significant risk factors for the development of re-HNP after initial lumbar decompression. We developed the re-herniation after decompression (RAD) profile index that has been translated into an online screening tool to identify low–high risk patients for re-HNP. Additional validation is needed for potential global implementation.

Background National databases are increasingly being used for research in spine surgery; however, one limitation of such databases that has received sparse mention is the frequency of missing data. Studies using these databases often do not emphasize the percentage of missing data for each variable used and do not specify how patients with missing data are incorporated into analyses. This study uses the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database to examine whether different treatments of missing data can influence the results of spine studies. Questions/purposes (1) What is the frequency of missing data fields for demographics, medical comorbidities, preoperative laboratory values, operating room times, and length of stay recorded in ACS-NSQIP? (2) Using three common approaches to handling missing data, how frequently do those approaches agree in terms of finding particular variables to be associated with adverse events? (3) Do different approaches to handling missing data influence the outcomes and effect sizes of an analysis testing for an association with these variables with occurrence of adverse events? Methods Patients who underwent spine surgery between 2005 and 2013 were identified from the ACS-NSQIP database. A total of 88,471 patients undergoing spine surgery were identified. The most common procedures were anterior cervical discectomy and fusion, lumbar decompression, and lumbar fusion. Demographics, comorbidities, and perioperative laboratory values were tabulated for each patient, and the percent of missing data was noted for each variable. These variables were tested for an association with “any adverse event” using three separate multivariate regressions that used the most common treatments for missing data. In the first regression, patients with any missing data were excluded. In the second regression, missing data were treated as a negative or “reference” value; for continuous variables, the mean of each variable’s reference range was computed and imputed. In the third regression, any variables with > 10% rate of missing data were removed from the regression; among variables with ≤ 10% missing data, individual cases with missing values were excluded. The results of these regressions were compared to determine how the different treatments of missing data could affect the results of spine studies using the ACS-NSQIP database. Results Of the 88,471 patients, as many as 4441 (5%) had missing elements among demographic data, 69,184 (72%) among comorbidities, 70,892 (80%) among preoperative laboratory values, and 56,551 (64%) among operating room times. Considering the three different treatments of missing data, we found different risk factors for adverse events. Of 44 risk factors found to be associated with adverse events in any analysis, only 15 (34%) of these risk factors were common among the three regressions. The second treatment of missing data (assuming “normal” value) found the most risk factors (40) to be associated with any adverse event, whereas the first treatment (deleting patients with missing data) found the fewest associations at 20. Among the risk factors associated with any adverse event, the 10 with the greatest effect size (odds ratio) by each regression were ranked. Of the 15 variables in the top 10 for any regression, six of these were common among all three lists. Conclusions Differing treatments of missing data can influence the results of spine studies using the ACS-NSQIP. The current study highlights the importance of considering how such missing data are handled. Clinical Relevance Until there are better guidelines on the best approaches to handle missing data, investigators should report how missing data were handled to increase the quality and transparency of orthopaedic database research. Readers of large database studies should note whether handling of missing data was addressed and consider potential bias with high rates or unspecified or weak methods for handling missing data.

Background Despite extensive research regarding risk factors for adverse events after total joint arthroplasty (TJA), there are few publications describing the timing at which such adverse events occur. Questions/purposes (1) On which postoperative day do certain adverse events occur? (2) What adverse events occur earlier after TKA than after THA? (3) For each adverse event, what proportion occurred after hospital discharge? Methods We screened the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) to identify all patients undergoing primary THA and primary TKA between 2005 and 2013, resulting in a study population of 124,657 patients evaluated as part of this retrospective database analysis. For each of eight different adverse events, the median postoperative day of diagnosis, interquartile range for day of diagnosis, and middle 80% for day of diagnosis were determined. Multivariate Cox proportional hazards modeling was used to test whether there is a difference of timing for each adverse event as stratified by TKA or THA. The proportion of adverse events occurring after versus before discharge was also calculated. Results The median day of diagnosis (and interquartile range; middle 80%) for stroke was 2 (1–10; 1–19), myocardial infarction 3 (2–6; 1–15), pulmonary embolism 3 (2–7; 1–19), pneumonia 4 (2–9; 2–17), deep vein thrombosis 6 (3–14; 2–23), urinary tract infection 8 (3–16; 2–24), sepsis 10 (5–19; 2–24), and surgical site infection 17 (11–23; 6–28). For the later occurring adverse events (surgical site infection, sepsis), the rate of occurrence remained high at the end of the 30-day postoperative period. Timing was earlier in patients undergoing TKA for pulmonary embolism (day 3 [interquartile range 2–6] versus 5 [ 3 – 17 ], p < 0.001) and deep vein thrombosis (day 5 [ 2 – 11 ] versus 13 [ 6 – 22 ], p < 0.001). The proportion of events occurring after discharge for myocardial infarction was 97 of 283 (34%), stroke 42 of 118 (36%), pulmonary embolism 223 of 625 (36%), pneumonia 171 of 426 (40%), deep vein thrombosis 576 of 956 (60%), urinary tract infection 958 of 1406 (68%), sepsis 284 of 416 (68%), and surgical site infection 1147 of 1212 (95%). Conclusions As lengths of hospital stay after TJA continue to decrease, our findings suggest that caution is in order because several acute and immediately life-threatening findings, including myocardial infarction and pulmonary embolism, might occur after discharge. Furthermore, the timing of surgical site infection and sepsis suggests that even the 30-day followup afforded by the ACS-NSQIP may not be sufficient to study the latest occurring adverse events. Additionally, both pulmonary embolism and deep vein thrombosis tend to occur earlier after TKA than THA, and this should guide clinical surveillance efforts in patients undergoing those procedures. These findings also indicate that inpatient-only databases (such as the Nationwide Inpatient Sample) may fail to capture a very large proportion of postoperative adverse events, weakening the conclusions of many published studies using those databases. Level of Evidence Level III, therapeutic study.

Background Industry payments made to physicians by drug and device manufacturers or group purchasing organizations are now reported to the Centers for Medicare and Medicaid Services (CMS) as a part of the Physician Payments Sunshine Act. Initial reports from the program show that orthopaedic surgeons lead all physician specialties in total and average industry payments. However, before further discussion of these payments and their implications can take place, it remains to be seen whether these figures are a true reflection of the field of orthopaedic surgery in general, rather than the result of a few outlier physicians in the field. In addition, the nature and sources of these funds should be determined to better inform the national dialogue surrounding these payments. Questions/Purposes We asked: (1) How do industry payments to orthopaedic surgeons compare with payments to physicians and surgeons in other fields, in terms of median payments and the Gini index of disparity? (2) How much do payments to the highest-receiving orthopaedic surgeons contribute to total payments? (3) What kind of industry payments are orthopaedic surgeons receiving? (4) How much do the highest-paying manufacturers contribute to total payments to orthopaedic surgeons? Materials and Methods We reviewed the most recent version of the CMS Sunshine Act Open Payments database released on December 19, 2014, containing data on payments made between August 1, 2013 and December 31, 2013. Data on total payments to individual physicians, physician specialty, the types of payments made, and the manufacturers making payments were reviewed. The Gini index of statistical dispersion was calculated for payments made to orthopaedic surgeons and compared with payments made to physicians and surgeons in all other medical specialties. A Gini index of 0 indicates complete equality of payments to everyone in the population, whereas an index of 1 indicates complete inequality, or all income going to one individual. Results A total of 15,376 orthopaedic surgeons receiving payments during the 5-month period were identified, accounting for USD 109,846,482. The median payment to orthopaedic surgeons receiving payments was USD 121 (interquartile range, USD 34–619). The top 10% of orthopaedic surgeons receiving payments (1538 surgeons) received at least USD 4160 and accounted for 95% of total payments. Royalties and patent licenses accounted for 69% of all industry payments to orthopaedic surgeons. Conclusions Even as a relatively small specialty, orthopaedic surgeons received substantial payments from industry (more than USD 110 million) during the 5-month study period. Whether there is a true return of value from these payments remains to be seen; however, future ethical and policy discussions regarding industry payments to orthopaedic surgeons should take into account the large disparities in payments that are present and also the nature of the payments being made. It is possible that patients and policymakers may view industry payments to orthopaedic surgeons more positively in light of these new findings. Level of Evidence Level III, Economic and Decision Analysis.

Background Posterior spinal fusion (PSF) is commonly performed for patients with adolescent idiopathic scoliosis (AIS). Identifying factors associated with perioperative morbidity and PSF may lead to strategies for reducing the frequency of adverse events (AEs) in patients and total hospital costs. Questions/purposes What is the frequency of and what factors are associated with postoperative: (1) AEs, (2) extended length of stay (LOS), and (3) readmission in patients with AIS undergoing PSF? Patients and Methods Patients, aged 11 to 18 years, who underwent PSF for AIS during 2012, were identified from the American College of Surgeons National Surgical Quality Improvement Program ® (ACS NSQIP ® ) Pediatric database. Patient were assessed for characteristics associated with AEs, extended LOS (defined as more than 6 days), and hospital readmission using multivariate logistic regression. Individual AEs captured in the database were grouped into two categories, “any adverse event” (AAE) and “severe adverse events” (SAEs) for analysis. A total of 733 patients met inclusion criteria. Results Twenty-seven patients (3.7%) had AAE and 19 patients (2.6%) had SAEs. Both AAE and SAEs were associated with BMI-for-age ninety-fifth percentile or greater (AAE: odds ratio [OR], 3.31; 95% CI, 1.43–7.65; p = 0.005. SAE: OR, 3.46; 95% CI, 1.32–9.09; p = 0.012). Extended LOS occurred for 60 patients (8.2%) and was associated with greater than 13 levels instrumented (OR, 2.00; 95% CI, 1.11–3.61; p = 0.021) and operative time of 365 minutes or more (OR, 2.57; 95% CI, 1.39–4.76; p = 0.003). Readmission occurred for 11 patients (1.5%), most often for surgical site infection, and was associated with the occurrence of any complication during the initial hospital stay (OR, 180.44; 95% CI, 35.47–917.97; p < 0.001). Conclusions Further research on prevention and management of obesity and surgical site infections may reduce perioperative morbidity for patients with AIS undergoing PSF. Level of Evidence Level III, prognostic study. See Instructions for Authors for a complete description of levels of evidence.

PurposeThe purpose of this study was to compare the rates of adjacent segment degeneration (ASD), sagittal alignment parameters, and patient-reported outcomes in patients who underwent multi-level versus single-level anterior cervical discectomy and fusion (ACDF).MethodsA retrospective cohort analysis was performed on consecutive patients who underwent an ACDF. Pre- and post-operative radiographic assessment included ASD, change in C2–C7 lordosis, T1 angle, levels fused, sagittal vertical axis (SVA), fusion mass lordosis, proximal and distal adjacent segment lordosis. Patient-reported outcomes were obtained.ResultsOf the 404 that underwent an ACDF with a minimum of 6 months of follow-up (average 28 months), there was no significant difference in the rate of radiographic ASD overall (p = 0.479) or in the proximal or distal adjacent segments on multivariate analysis. Secondarily, the multi-level fusions appear to restore significantly greater amounts of lordosis compared to single-level procedures (p < 0.001) and are able to maintain the corrected cervical lordosis and fusion segment lordosis over time. From the immediate post-operative period to final follow-up, the single-level ACDFs show continuing lordosis improvement (p = 0.005) that is significantly greater than that of the multi-level constructs. There were no significant differences between pre-operative, post-operative, or change in patient-reported outcomes.ConclusionsTwo years following an ACDF, patients who underwent multi-level fusions appear to restore significantly greater amounts of lordosis compared to single-level procedures, while single-level ACDFs show significantly greater amounts of lordosis improvement over time. Multi-level procedures may not be at a significantly greater risk of developing early radiographic evidence of ASD compared to single-level procedure.Graphical abstractThese slides can be retrieved under Electronic Supplementary Material.

Study Design: Original research, cross-sectional study. Objectives: Evaluate patient satisfaction with spine care delivered via telemedicine. Identify patient- and visit-based factors associated with increased satisfaction and visit preference. Methods: Telemedicine visits with a spine surgeon at 2 practices in the United States between March and May 2020 were eligible for inclusion in the study. Patients were sent an electronic survey recording overall satisfaction, technical or clinical issues encountered, and preference for a telemedicine versus an in-person visit. Factors associated with poor satisfaction and preference of telemedicine over an in-person visit were identified using multivariate logistic regression. Results: A total of 772 responses were collected. Overall, 87.7% of patients were satisfied with their telemedicine visit and 45% indicated a preference for a telemedicine visit over an in-person visit if given the option. Patients with technical or clinical issues were significantly less likely to achieve 5 out of 5 satisfaction scores and were significantly more likely to prefer an in-person visit. Patients who live less than 5 miles from their surgeon’s office and patients older than 60 years were also significantly more likely to prefer in-person visits. Conclusions: Spine telemedicine visits during the COVID-19 pandemic were associated with high patient satisfaction. Additionally, 45% of respondents indicated a preference for telemedicine versus an in-patient visit in the future. In light of these findings, telemedicine for spine care may be a preferable option for a subset of patients into the future.

Purpose Alpine skiing and snowboarding are both popular winter sports that can be associated with significant orthopaedic injuries. However, there is a lack of nationally representative injury data for the two sports. Methods The National Trauma Data Bank was queried for patients presenting to emergency departments due to injuries sustained from skiing and snowboarding during 2011 and 2012. Patient demographics, comorbidities, and injury patterns were tabulated and compared between skiing and snowboarding. Risk factors for increased injury severity score and lack of helmet use were identified using multivariate logistic regression. Results Of the 6055 patients identified, 55.2 % were skiers. Sixty-one percent had fractures. Lower extremity fractures were the most common injury and occurred more often in skiers ( p  < 0.001). Upper extremity fractures were more common in snowboarders, particularly distal radius fractures ( p  < 0.001). On multivariate analysis, increased injury severity was independently associated with age 18–29, 60–69, 70+, male sex, a positive blood test for alcohol, a positive blood test for an illegal substance, and wearing a helmet. Lack of helmet use was associated with age 18–29, 30–39, smoking, a positive drug test for an illegal substance, and snowboarding. Conclusions Young adults, the elderly, and those using substances were shown to be at greater risk of increased injury severity and lack of helmet use. The results of this study can be used clinically to guide the initial assessment of these individuals following injury, as well as for targeting preventive measures and education. Level of evidence Prognostic Level III.