Faculty Bibliography

BACKGROUND:Machine learning techniques can identify complex relationships in large healthcare datasets and build prediction models that better inform physicians in ways that can assist in patient treatment decision-making. In the domain of shoulder arthroplasty, machine learning appears to have the potential to anticipate patients' results after surgery, but this has not been well explored. QUESTIONS/PURPOSES/OBJECTIVE:(1) What is the accuracy of machine learning to predict the American Shoulder and Elbow Surgery (ASES), University of California Los Angeles (UCLA), Constant, global shoulder function, and VAS pain scores, as well as active abduction, forward flexion, and external rotation at 1 year, 2 to 3 years, 3 to 5 years, and more than 5 years after anatomic total shoulder arthroplasty (aTSA) or reverse total shoulder arthroplasty (rTSA)? (2) What is the accuracy of machine learning to identify whether a patient will achieve clinical improvement that exceeds the minimal clinically important difference (MCID) threshold for each outcome measure? (3) What is the accuracy of machine learning to identify whether a patient will achieve clinical improvement that exceeds the substantial clinical benefit threshold for each outcome measure? METHODS:A machine learning analysis was conducted on a database of 7811 patients undergoing shoulder arthroplasty of one prosthesis design to create predictive models for multiple clinical outcome measures. Excluding patients with revisions, fracture indications, and hemiarthroplasty resulted in 6210 eligible primary aTSA and rTSA patients, of whom 4782 patients with 11,198 postoperative follow-up visits had sufficient preoperative, intraoperative, and postoperative data to train and test the predictive models. Preoperative clinical data from 1895 primary aTSA patients and 2887 primary rTSA patients were analyzed using three commercially available supervised machine learning techniques: linear regression, XGBoost, and Wide and Deep, to train and test predictive models for the ASES, UCLA, Constant, global shoulder function, and VAS pain scores, as well as active abduction, forward flexion, and external rotation. Our primary study goal was to quantify the accuracy of three machine learning techniques to predict each outcome measure at multiple postoperative timepoints after aTSA and rTSA using the mean absolute error between the actual and predicted values. Our secondary study goals were to identify whether a patient would experience clinical improvement greater than the MCID and substantial clinical benefit anchor-based thresholds of patient satisfaction for each outcome measure as quantified by the model classification parameters of precision, recall, accuracy, and area under the receiver operating curve. RESULTS:Each machine learning technique demonstrated similar accuracy to predict each outcome measure at each postoperative point for both aTSA and rTSA, though small differences in prediction accuracy were observed between techniques. Across all postsurgical timepoints, the Wide and Deep technique was associated with the smallest mean absolute error and predicted the postoperative ASES score to ± 10.1 to 11.3 points, the UCLA score to ± 2.5 to 3.4, the Constant score to ± 7.3 to 7.9, the global shoulder function score to ± 1.0 to 1.4, the VAS pain score to ± 1.2 to 1.4, active abduction to ± 18 to 21°, forward elevation to ± 15 to 17°, and external rotation to ± 10 to 12°. These models also accurately identified the patients who did and did not achieve clinical improvement that exceeded the MCID (93% to 99% accuracy for patient-reported outcome measures (PROMs) and 85% to 94% for pain, function, and ROM measures) and substantial clinical benefit (82% to 93% accuracy for PROMs and 78% to 90% for pain, function, and ROM measures) thresholds. CONCLUSIONS:Machine learning techniques can use preoperative data to accurately predict clinical outcomes at multiple postoperative points after shoulder arthroplasty and accurately risk-stratify patients by preoperatively identifying who may and who may not achieve MCID and substantial clinical benefit improvement thresholds for each outcome measure. CLINICAL RELEVANCE/CONCLUSIONS:Three different commercially available machine learning techniques were used to train and test models that predicted clinical outcomes after aTSA and rTSA; this device-type comparison was performed to demonstrate how predictive modeling techniques can be used in the near future to help answer unsolved clinical questions and augment decision-making to improve outcomes after shoulder arthroplasty.

STUDY DESIGN/METHODS:Retrospective analysis of outcomes in single-level spine and primary hip and knee arthroplasty patients. OBJECTIVE:Compare baseline and post-operative outcomes in patients undergoing spine surgery procedures with total hip arthroplasty (THA) and total knee arthroplasty (TKA) to further define outcomes in orthopedic surgery. SUMMARY OF BACKGROUND DATA/BACKGROUND:Computer-adaptive Patient Reported Outcome Information System (PROMIS) allows for standardized assessment of the Health Related Quality of Life across different disease states. METHODS:Patients who underwent spine surgery (anterior cervical discectomy and fusion, cervical disc replacement, lumbar laminectomy, microscopic lumbar discectomy, transforaminal lumbar interbody fusion or adult reconstruction surgery (THA, TKA) were grouped. Mean Charlson Comorbidity Index (CCI), Baseline (BL) and 6-month (6 M) PROMIS scores of Physical Function, Pain Interference, and Pain Intensity were determined. Paired t-tests compared differences in CCI, BL, 6 M, and change in PROMIS scores for spine and adult reconstruction procedures. RESULTS:304 spine surgery patients (Age=58.1 ± 15.6; 42.9% Female) and 347 adult reconstruction patients (Age=62.9 ± 11.8; 54.1% Female) were compared. Spine surgery groups had more disability and pain at baseline than adult reconstruction patients according to Physical Function [(21.0, 22.2, 9.07, 12.6, 10.4) vs (35.8, 35.0), respectively, p < .01], Pain Interference [(80.1, 74.1, 89.6, 92.5, 90.6) vs (64.0, 63.9), respectively, p < .01] and Pain Intensity [(53.0, 53.1, 58.3, 58.5, 56.1) vs (53.4, 53.8), respectively, p < .01]. At 6 M, spine surgery patients remained more disabled and had more pain compared to adult reconstruction patients. Over the 6-month timespan, spine patients experienced greater improvements than adult reconstruction patients in terms of Physical Function [(+8.7, +22.2, +9.7, +12.9, +12.1) vs (+5.3, +3.9), respectively, p < .01] and Pain Interference scores [(-15.4, -28.1, -14.7, -13.1, -12.3) vs (-8.3, -6.0), respectively, p < .01]. CONCLUSIONS:Spinal surgery patients had lower BL and 6 M PROMIS scores, but greater relative improvement in PROMIS scores compared to adult reconstruction patients. LEVEL OF EVIDENCE/METHODS:3.

OBJECTIVES:(1) To demonstrate how a risk assessment tool modified to account for the COVID-19 virus during the current global pandemic is able to provide risk assessment for low-energy geriatric hip fracture patients. (2) To provide a treatment algorithm for care of COVID-19 positive/suspected hip fractures patients that accounts for their increased risk of morbidity and mortality. SETTING:One academic medical center including 4 Level 1 trauma centers, 1 university-based tertiary care referral hospital, and 1 orthopaedic specialty hospital. PATIENTS/PARTICIPANTS:One thousand two hundred seventy-eight patients treated for hip fractures between October 2014 and April 2020, including 136 patients treated during the COVID-19 pandemic between February 1, 2020 and April 15, 2020. INTERVENTION:The Score for Trauma Triage in the Geriatric and Middle-Aged ORIGINAL (STTGMAORIGINAL) score was modified by adding COVID-19 virus as a risk factor for mortality to create the STTGMACOVID score. Patients were stratified into quartiles to demonstrate differences in risk distribution between the scores. MAIN OUTCOME MEASUREMENTS:Inpatient and 30-day mortality, major, and minor complications. RESULTS:Both STTGMA score and COVID-19 positive/suspected status are independent predictors of inpatient mortality, confirming their use in risk assessment models for geriatric hip fracture patients. Compared with STTGMAORIGINAL, where COVID-19 patients are haphazardly distributed among the risk groups and COVID-19 inpatient and 30 days mortalities comprise 50% deaths in the minimal-risk and low-risk cohorts, the STTGMACOVID tool is able to triage 100% of COVID-19 patients and 100% of COVID-19 inpatient and 30 days mortalities into the highest risk quartile, where it was demonstrated that these patients have a 55% rate of pneumonia, a 35% rate of acute respiratory distress syndrome, a 22% rate of inpatient mortality, and a 35% rate of 30 days mortality. COVID-19 patients who are symptomatic on presentation to the emergency department and undergo surgical fixation have a 30% inpatient mortality rate compared with 12.5% for patients who are initially asymptomatic but later develop symptoms. CONCLUSION:The STTGMA tool can be modified for specific disease processes, in this case to account for the COVID-19 virus and provide a robust risk stratification tool that accounts for a heretofore unknown risk factor. COVID-19 positive/suspected status portends a poor outcome in this susceptible trauma population and should be included in risk assessment models. These patients should be considered a high risk for perioperative morbidity and mortality. Patients with COVID-19 symptoms on presentation should have surgery deferred until symptoms improve or resolve and should be reassessed for surgical treatment versus definitive nonoperative treatment with palliative care and/or hospice care. LEVEL OF EVIDENCE:Prognostic Level III. See Instructions for Authors for a complete description of Levels of Evidence.

Background/UNASSIGNED:Humeral stem lucencies are uncommon after uncemented anatomic total shoulder arthroplasty (aTSA), and their clinical significance is unknown. This study compares clinical outcomes of aTSA with and without humeral stem lucencies. Methods/UNASSIGNED:Two-hundred eighty aTSAs using an uncemented grit-blasted metaphyseal-fit humeral stem between 2005 and 2013 were retrospectively evaluated for radiographic humeral stem lucencies. All shoulders were evaluated at a minimum 5-year follow-up from a multicenter database. Clinical outcomes included range of motion (ROM) and American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form (ASES) score, Constant score, University of California-Los Angeles Shoulder Score (UCLA), Simple Shoulder Test (SST), and Shoulder Pain and Disability Index (SPADI) scores. Postoperative radiographs were evaluated and complications were recorded. Results/UNASSIGNED:Two-hundred forty-three humeral stems showed no radiolucent lines. Among the 37 humeral stems with lucent lines, lines were most common in zones 8, 4, 7, and 3. Preoperative ROM and functional outcomes were similar between groups. Postoperative change in outcomes exceeded the minimal clinically important difference (MCID) for all ROM and outcomes in both groups. Postoperative change between groups showed no significant difference in ROM or outcome scores, but improved mean abduction exceeded the MCID in the patients without humeral lines. The complication rate after omitting patients with humeral loosening was higher in patients with humeral lucencies, as was the revision rate. There was also a higher glenoid-loosening rate in patients with humeral lucencies. Conclusion/UNASSIGNED:Humeral lucent lines after uncemented stemmed aTSA have a small negative effect on ROM and functional outcomes compared with patients without lucent humeral lines, which may not be clinically significant. The complication and revision rates were significantly higher in patients with humeral lucencies.

OBJECTIVES/OBJECTIVE:To examine one health system's response to the essential care of its hip fracture population during the COVID-19 pandemic and report on its effect on patient outcomes. DESIGN/METHODS:Prospective cohort study SETTING:: Seven musculoskeletal care centers with New York City and Long Island. PATIENTS/PARTICIPANTS/METHODS:138 recent and 115 historical hip fracture patients. INTERVENTION/METHODS:Patients with hip fractures occurring between February 1, 2020 and April 15, 2020 or between February 1, 2019 and April 15, 2019 were prospectively enrolled in an orthopedic trauma registry and chart reviewed for demographic and hospital quality measures. Patients with recent hip fractures were identified as COVID positive (C+), COVID suspected (Cs) or COVID negative (C-). MAIN OUTCOME MEASUREMENTS/METHODS:Hospital quality measures, inpatient complications and mortality rates. RESULTS:Seventeen (12.2%) patients were confirmed C+ by testing and another 14 (10.1%) were suspected (Cs) of having had the virus but were never tested. The C+ cohort, when compared to Cs and C- cohorts, had: an increased mortality rate (35.3% vs 7.1% vs 0.9%), increased length of hospital stay, a greater major complication rate and a greater incidence of ventilator need postoperatively. CONCLUSIONS:COVID-19 had a devastating effect on the care of hip fracture patients during the pandemic. Although practice patterns generally remained unchanged, treating physicians need to understand the increased morbidity and mortality in hip fracture patients complicated by COVID-19. LEVEL OF EVIDENCE/METHODS:Prognostic Level III. See Instructions for Authors for a complete description of Levels of Evidence.

INTRODUCTION/BACKGROUND:Students seek gap years to enhance knowledge and improve chances of professional success. Although many institutions offer research opportunities, no studies have examined outcomes after these experiences. This study evaluates a dedicated year of orthopaedic research on a cohort's ultimate orthopaedic surgery match rate. METHODS:From 2001 to 2018, 129 learners spent a year with our Department of Orthopedic Surgery at a major academic medical center. The students were either completing a gap year after college, during or after medical school, or after an unsuccessful match. Participants were asked to respond to a survey, which included demographics, educational information, and metrics related to the program. For the subcohort of students who ranked orthopaedic surgery, the match rate was compared with the mean for the US orthopaedic surgery match rates from 2006 to 2018 using a chi-square analysis. In addition, a Mann-Whitney U test was used to compare the number of publications before and after the year. RESULTS:One hundred three students (80%) returned completed questionnaires. Of all learners who applied to and ranked orthopaedic surgery, 91% matched into an orthopaedic surgery residency program. These results compared favorably with the US orthopaedic match from 2006 to 2018 (67.9%; P < 0.001), despite a 4-point lower United States Medical Licensing Examination (USMLE) Step 1 score for the research cohort. Finally, the research cohort had a greater percentage of women (23%) and minorities (40%) than the proportion of woman and minority practicing orthopaedic surgeons. CONCLUSION/CONCLUSIONS:Students who completed a gap year in research matched into orthopaedics at a higher rate than the national average, despite a lower Step score. Mentors may also target traditionally underrepresented groups to help increase the pool of diverse applicants.

As the world grapples with the COVID-19 pandemic, we as health care professionals thrive to continue to help our patients, and as orthopedic surgeons, this goal is ever more challenging. As part of a major academic tertiary medical center in New York City, the orthopedic department at New York University (NYU) Langone Health has evolved and adapted to meet the challenges of the COVID pandemic. In our report, we will detail the different aspects and actions taken by NYU Langone Health as well as NYU Langone Orthopedic Hospital and the orthopedic department in particular. Among the steps taken, the department has reconfigured its staff's assignments to help both with the institution's efforts and our patients' needs from reassigning operating room nurses to medical COVID floors to having attending surgeons cover urgent care locations. We have reorganized our residency and fellowship rotations and assignments as well as adapting our educational programs to online learning. While constantly evolving to meet the institution's and our patient demands, our leadership starts planning for the return to a new "normal".

BACKGROUND:We sought to identify the influence of shoulder arthroplasty (SA) type (primary anatomic, primary reverse, revision) and indication (fracture, arthritis) on the risk of postoperative packed red blood cell transfusion (pRBCT) and intravenous fluid bolus (IVFB). METHODS:Patients who underwent SA from 2013 through 2016 at our institution were categorized into four groups: primary anatomic (pTSA; N = 298), primary reverse (pRTSA; N = 292), revision (RevSA; N = 133), and shoulder arthroplasty for fracture (SAF; N = 58). Basic demographics, intraoperative metrics, preoperative lab values, and postoperative interventions (pRBCT and IVFB) were retrieved from electronic records. RESULTS:There were 781 SAs, of which 176 cases involved at least one postoperative intervention: pRBCT (6.3%) or IVFB (18.8%). Compared to pTSA, the odds of pRBCT in pRTSA, revSA, and SAF were: 3.0 (95% CI 0.9-10.0), 3.4 (95% CI 0.9-2.7), and 8.6 (95% CI 2.2-32.9), respectively. Independent risk factors for pRBCT included increasing age (p = 0.003), underweight body mass index (p = 0.019), Charlson Comorbidity Index ≥ 3 (p = 0.002), inpatient discharge to higher level of care (p = 0.011), estimated blood loss (p = 0.003), and preoperative hemoglobin (p ≤ 0.001). Also, compared to pTSA, the odds for IVFB in pRTSA, revSA, and SAF were: 2.8 (95% CI 1.7-4.6), 2.2 (95% CI 1.2-4.0), and 4.7 (95% CI 2.2-9.9), respectively. Other independent risk factors for IVFB included female sex (0.002), CCI ≥ 3 (p = 0.017), and operative time (p = 0.047). CONCLUSION/CONCLUSIONS:Shoulder arthroplasty for fracture is an independent risk factor for higher risk of postoperative pRBCT and IVFB.

BACKGROUND:Osteoarthritis of the glenohumeral joint is often associated with posterior glenoid wear. The purpose of this study was to determine the clinical and radiographic outcomes of a posteriorly augmented glenoid in patients who have a Walch B glenoid deformity when treated with anatomic total shoulder arthroplasty (aTSA). METHODS:At total of 68 primary aTSA patients with osteoarthritis and a Walch B glenoid deformity were treated with an 8° posteriorly augmented glenoid. All patients were evaluated and underwent scoring preoperatively and at latest follow-up with 5 clinical outcome scoring metrics; active range of motion (ROM) was also measured. The mean follow-up period was 50 months, with a 2-year minimum follow-up period. RESULTS:All patients experienced significant improvements in pain and function following aTSA with a posteriorly augmented glenoid, and 90% of patients exceeded the minimal clinically important difference threshold for the clinical outcome metric scores and ROM measures. Two-thirds of patients exceeded the substantial clinical benefit threshold for the clinical outcome metrics and ROM. Preoperatively, the humeral head was posteriorly subluxated an average of 73% for each Walch B glenoid type, and at latest follow-up, all humeral heads were re-centered on the posteriorly augmented glenoid. Two patients with augmented glenoids who had Walch B2 glenoids underwent revision for aseptic glenoid loosening. DISCUSSION/CONCLUSIONS:Anatomic total shoulder arthroplasty patients with Walch B glenoids receiving an 8° posteriorly augmented wedge glenoid experienced excellent clinical and radiographic outcomes with a patient satisfaction rate greater than 97% and a low complication rate at a mean follow-up of 50 months. Humeral head centering was maintained for each type of Walch B glenoid.