Predicting Factors for Blood Transfusion in Primary Total Knee Arthroplasty Using a Machine Learning Method.

INTRODUCTION: Acute blood loss anemia requiring allogeneic blood transfusion is still a postoperative complication of total knee arthroplasty (TKA). This study aimed to use machine learning models for the prediction of blood transfusion after primary TKA and to identify contributing factors. METHODS: A total of 2,093 patients who underwent primary TKA at our institution were evaluated using data extracted from the hospital quality improvement database to identify patient demographics and surgical variables that may be associated with blood transfusion. A multilayer perceptron neural network (MPNN) machine learning algorithm was used to predict risk factors for blood transfusion and factors associated with increased length of stay. Statistical analyses including bivariate correlate analysis, Chi-Square test, and Student t-test were performed for demographic analysis and to determine the correlation between blood transfusion and other variables. RESULTS: The results demonstrated important factors associated with transfusion rates, including preoperative hemoglobin level, preoperative creatinine level, length of surgery, simultaneous bilateral surgeries, tranexamic acid usage, American Society of Anesthesiologists Physical Status score, preoperative albumin level, ethanol usage, preoperative anticoagulation medications, age, and TKA type (conventional versus robotic-assisted). Patients who underwent a blood transfusion had a markedly greater length of stay than those who did not. The MPNN machine learning model achieved excellent performance across discrimination (AUC = 0.894). DISCUSSION: The MPNN machine learning model showed its power as a statistical analysis tool to predict the ranking of factors for blood transfusion. Traditional statistics are unable to differentiate importance or predict in the same manner as a machine learning model. CONCLUSION: This study demonstrated that MPNN for the prediction of patient-specific blood transfusion rates after TKA represented a novel application of machine learning with the potential to improve preoperative planning for treatment outcomes.

Total Hip Arthroplasty in the Ultrayoung.

Background: Total hip arthroplasty (THA) procedures provide a surgical option for "ultrayoung" patients ≤30 years old with end-stage hip arthropathy. This has historically been coupled with concerns over early component failure and challenging surgical technique leading to increased risk of overall morbidity. The purpose of this study is to better elucidate the poorly defined indications and outcomes for THA in ultrayoung patients with end-stage hip disease. Methods: A total of 40 THAs in 35 patients ≤30 years old performed at our institution from 2009 to 2016 were retrospectively followed for an average of 2 years (median 11 months, interquartile range 1-31.25). Primary outcome measure was THA revision. Patient demographics were compared against outcomes. The effects on revision rate of hip joint pathology and type of bearing surface were investigated. T-test, chi-square test, and bivariate correlation were performed to determine statistical significance (P < .05). Machine learning was used to determine the normalized important factor leading to THA revision. Results: Fifteen male and 25 female patients were included. Median patient age was 23 (interquartile range 19-27) years, with an average body mass index of 27.0 ± 7.9. A majority of THAs were indicated for osteonecrosis (32) and bearing surface type was predominantly metal-on-highly cross-linked polyethylene (36). The overall revision rate was 7.5%, without a correlation between revision and demographic characteristics. Revision surgery was significantly correlated with bearing surface type (P = .028). Important factors for revision were age (100%), bearing surface type (84.7%), and body mass index (52.1%). Conclusions: In patients ≤30 years old, THAs performed with the use of modern implants and surgical methods show satisfactory survivorship and functional outcomes with short-term follow-up.

Antibiotic Cement-Coated Interlocked Intramedullary Nails for the Treatment of Infected Nonunion After Intramedullary Nailing.

OBJECTIVE: To evaluate outcomes using an interlocking antibiotic cement-coated nail and culture-specific systematic antibiotics in the treatment of infected nonunion after intramedullary nailing. DESIGN: Retrospective observational cohort study. SETTING: Urban level I trauma center. PATIENTS/PARTICIPANTS: Forty-one nonconsecutive patients who presented to a level I trauma center who underwent interlocked antibiotic nailing for treatment of infected nonunion status after primary intramedullary nailing. OUTCOMES: Eradication of infection, radiographic union by 2-year follow-up. RESULTS: Antibiotic nailing successfully eradicated infection and led to fracture healing in 35 patients (85.4%), while 6 patients (14.6%) had persistent infection and required further surgical treatment. Of the 6 patients who required further treatment, 5 eventually went on to heal with fracture union and eradication of their infection, while 1 required a salvage procedure. Of the 5 patients who eventually went on to heal, 4 of them healed with repeat antibiotic or intramedullary nails, while 1 required segmental resection and bone grafting before healing. CONCLUSIONS: This study suggests that the proposed interlocked antibiotic nailing technique is a viable therapeutic option to eradicate infected nonunion and support fracture healing. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Computer Vision and Machine Learning-Based Gait Pattern Recognition for Flat Fall Prediction.

BACKGROUND: Gait recognition has been applied in the prediction of the probability of elderly flat ground fall, functional evaluation during rehabilitation, and the training of patients with lower extremity motor dysfunction. Gait distinguishing between seemingly similar kinematic patterns associated with different pathological entities is a challenge for the clinician. How to realize automatic identification and judgment of abnormal gait is a significant challenge in clinical practice. The long-term goal of our study is to develop a gait recognition computer vision system using artificial intelligence (AI) and machine learning (ML) computing. This study aims to find an optimal ML algorithm using computer vision techniques and measure variables from lower limbs to classify gait patterns in healthy people. The purpose of this study is to determine the feasibility of computer vision and machine learning (ML) computing in discriminating different gait patterns associated with flat-ground falls. METHODS: We used the Kinect® Motion system to capture the spatiotemporal gait data from seven healthy subjects in three walking trials, including normal gait, pelvic-obliquity-gait, and knee-hyperextension-gait walking. Four different classification methods including convolutional neural network (CNN), support vector machine (SVM), K-nearest neighbors (KNN), and long short-term memory (LSTM) neural networks were used to automatically classify three gait patterns. Overall, 750 sets of data were collected, and the dataset was divided into 80% for algorithm training and 20% for evaluation. RESULTS: The SVM and KNN had a higher accuracy than CNN and LSTM. The SVM (94.9 ± 3.36%) had the highest accuracy in the classification of gait patterns, followed by KNN (94.0 ± 4.22%). The accuracy of CNN was 87.6 ± 7.50% and that of LSTM 83.6 ± 5.35%. CONCLUSIONS: This study revealed that the proposed AI machine learning (ML) techniques can be used to design gait biometric systems and machine vision for gait pattern recognition. Potentially, this method can be used to remotely evaluate elderly patients and help clinicians make decisions regarding disposition, follow-up, and treatment.

The Implementation of Lean Six Sigma Principles to Improve the Value of Care Delivery for Total Joint Arthroplasty Patients: The Perioperative Institute of Surgical Excellence Experience.

BACKGROUND: With the projected increase in the volume of total joint arthroplasty (TJA), minimizing variations in surgery times, hospital length of stay (LOS), discharge dispositions, and inhospital complication rates would help reduce costs and improve the quality of care. As the move toward bundle payment models gains further traction, providers will be reimbursed based on the quality and cost associated with the surgical episode. As such, it remains critical to design and implement high-quality cost-effective perioperative delivery care models. Lean Six Sigma (LSS) methodology has been well described in the healthcare field as a superior strategy in designing processes aimed at reducing waste while minimizing error rates. We present an institutional experience with the design and implementation of a LSS quality improvement process specific to the TJA pathway, with a hypothesis of expected decrease in case cancellation rate, inhospital LOS, 30-day readmissions, and inpatient rehabilitation utilization after program implementation. METHODS: In 2017, the Perioperative Institute of Surgical Excellence (PISE) program for lower limb TJA was designed and implemented at our institution over a 4-month duration. The program was designed following LSS principles as a low-cost easily adoptable model with a goal to reduce hospital LOS, case cancellation rate, 30-day readmissions, and inpatient rehabilitation utilization. RESULTS: A total of 328 patients (128 total hip arthroplasty and 200 total knee arthroplasty) were included in PISE compared with a total of 255 patients (106 total hip arthroplasty and 149 total knee arthroplasty) for the preimplementation cohort. After implementation of the model, and compared with a similar 4-month preimplementation duration, the pilot results revealed an increase in monthly case load by 28.6%, decrease in the 30-day readmission rate by 1.16%, inpatient rehabilitation utilization by 60%, a reduction of the average LOS by 0.8 days, and a case cancellations decrease by 51%. CONCLUSION: The implementation of the pilot protocol for PISE within our institution was successful in decreasing LOS, inpatient rehabilitation utilization, 30-day readmission, and case cancellation. Further assessment is needed to ascertain sustainability of the protocol over a longer duration and generalizability of the results at different institutions and surgeons.

Accountable Operating Room Teams.

With Medicare reimbursement diminishing and the aging population consuming more health care, hospitals continue to push for reforms to improve the efficiency of health care delivery, decrease consumption, and elevate the quality of care. Operating rooms command a large share of hospital resources but are also major revenue generators. Surgical care has evolved to become more efficient and accountable. Defining the characteristics of an accountable operating room team has been more elusive and inconsistent. This review defines the characteristics of accountable operating room teams and recommends measures by which to evaluate them. [Orthopedics. 2021;44(4):e463-e470.].

Assessing knee anatomy using Makoplasty software a case series of 99 knees.

BACKGROUND: Role of MAKOplasty software in determining femoral neck version, distal-femoral resection angle, tibial axis difference, distal-femoral rotation, medial/lateral tibial slope, and tibial tubercle alignment has yet to be fully explored. METHODS: Preoperative CT scans and plain films of 99 patients were obtained for each patient according to predetermined MAKO-protocol by four observers. Reliability analyses (Cronbach's Alpha-test) was performed to determine agreement between raters for angle measures. RESULTS: Anatomic measurements were similar to previously published literature, and cronbachs'alpha analysis demonstrated agreement amidst all observers. CONCLUSION: MAKOplasty software produces similar results to anatomic measurements in planning for TKA with good reproducibility.

Chronic kidney disease impact on total joint arthroplasty outcomes: A National Inpatient Sample-based study.

INTRODUCTION: In the United States, chronic kidney disease (CKD) affects roughly 11% of the population or 19.2 million people. As the prevalence of CKD and demand for total joint arthroplasty (TJA) continue to rise, it is critical to assess the impact of CKD on postoperative clinical and economic outcomes. METHODS: Discharge data from 2006 to 2011 National Inpatient Sample were used for this study. A total of 851,150 TJA patients were divided into three cohorts: group 1 included no CKD, CKD stage I, and CKD stage II; group 2 included CKD stage III and stage IV; group 3 included CKD stage V. Inverse probability of treatment weighting/propensity score weighting was used to predict outcome variables as a function of age, sex, and Elixhauser comorbidities. Patients were compared against group I for in-hospital postoperative outcomes. RESULTS: Stage III/IV CKD patients undergoing primary TJA had higher odds of any complication (odds ratio (OR), 2.63; p < 0.0001), longer length of stay (LOS), and higher total charge (LOS, 4.34 vs. 3.48 days; total charge, US$56,003 vs. US$46,115; p < 0.0001) when compared to patients with no CKD/stage I or II. Similarly, stage V CKD patients undergoing primary TJA had higher odds of any complication (OR, 1.64; p < 0.0001), longer LOS, and higher total charges (LOS, 5.81 vs. 3.48 days; total charge, US$59,869 vs. US$46,115) than their counterparts with no CKD/stage I or II CKD. DISCUSSION: Our results indicate that stage III, IV, or V CKD, compared with those with no CKD, stage I or II patients are at a greater risk for postoperative complications and consume more resources following TJA.

Interventions for Obesity and Nutritional Status in Arthroplasty Patients.

Nutritional risk in patients undergoing total joint arthroplasty has been well-studied with regard to diagnostic criteria; however, therapeutic management of abnormal body mass index (BMI) values and serum markers remains to be studied in patients undergoing joint replacement surgery. Patients with a BMI value of >40 kg/m2 are at increased risk for postoperative complications; weight loss programs and bariatric surgery are therapeutic modalities that can be used in the prehabilitation and long-term rehabilitation of patients undergoing total joint arthroplasty. Management of patients with abnormal nutritional status should be multidisciplinary and allow for the incorporation of dietitians and nutritionists in therapeutic planning. Hypoalbuminemia correction can be completed intravenously or orally; however, arthroplasty studies remain lacking with regard to the preferred modalities of correction.

Prevalence of Bacterial Contamination of Casting Material in a Pediatric Population.

Surgical site infection is a relatively common and devastating complication following pediatric orthopedic surgery. Many infections have been determined to be the result of settled airborne particles on surgical equipment and the sterile field. Fiberglass casts are commonly used orthopedic fixation devices before and after surgery; however, fiberglass casting material is expelled during the removal process and represents an uninvestigated area for the possibility of cast saw dust as a source of airborne bacterial contamination in an operating room setting. This study evaluates the prevalence and distribution of microbiota on 90 pediatric casts by collecting and culturing fiberglass cast material from 90 pediatric casts. Bacterial identification was performed using a Bruker Biotyper Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry device. 81 out of 90 casts (90%) showed evidence of microbial contamination. Isolated species were very diverse and ranged from normal skin flora to opportunistic pathogens. The 5 most commonly isolated organisms were Acinetobacter pittii, Enterobacter cloacae, Micrococcus luteus, Staphylococcus epidermidis, and Staphylococcus hominis. Further investigation is required to determine if casting material is truly a cause of surgical site infection.

Assessing Preoperative Risk Factors With Sex Disparities in Total Joint Arthroplasty Patients and Financial Outcomes From the National Inpatient Sample Database.

INTRODUCTION: Disparities in the healthcare system imply potential risks for vulnerable groups whose needs are not appropriately met. Total joint arthroplasty (TJA) is successful in treating end-stage arthritis, resulting in increased demand for the procedure, however remains underused in both sexes, especially in women. Although multiple studies assessed the differences in postoperative morbidities between sexes, there remains a lack in understanding patients' preoperative clinical profile and nonclinical demographics. The aim of this study is to provide a population-based epidemiologic assessment of preoperative risk factors and sex disparities and assess differences in outcomes following TJA. METHODS: The National Inpatient Sample database from 2006 to 2011 was analyzed. Patients who underwent primary total knee and hip arthroplasty were identified and stratified into two cohorts of male and female, and demographic data and comorbidities were collected. Postoperative complications, length of stay, total charges, and discharge destination were measured for matched cohorts. RESULTS: Female patients present for TJAs at an older average age, are less likely to present with AIDS, alcohol abuse, coagulopathy, congestive heart failure, drug abuse, liver disease, peripheral vascular disease, and renal failure, and are more likely to present with anemia, autoimmune disorders, chronic obstructive pulmonary disease, depression, obesity, and valvular disease. Postoperatively, the average length of stay for female patients was markedly higher (3.52 versus 3.39) and a lower percentage went home (59% versus 73%). Overall, female patients experience greater odds of any complication while in-patient. DISCUSSION: This study highlighted sex differences in areas that could account for the underuse of the procedure in both sexes, with women affected to a greater extent. Understanding these factors will help address the unmet needs of both sexes after TJA by encouraging future studies and provider education to ensure that all patients are able to access the necessary procedures for pain relief and functional improvement.

Review article: Patient characteristics that act as risk factors for intraoperative complications in hip, knee, and shoulder arthroplasties.

The number of annual THA's, TKA's, and TSA's is set to increase significantly by the year 2030, making it imperative to understand the risks for negative outcomes in these procedures. While research has studied the patient risk factors for perioperative and postoperative complications, there has been relatively little research for intraoperative complications. After a thorough literature review, the most supported finding was that patients with a BMI >30 had significantly more intraoperative blood loss than those with a BMI <30. All other relationships between patient risk factors and intraoperative complications of interest were inadequately studied.

The Joint Utilization Management Program-Implementation of a Bundle Payment Model and Comparison Between Year 1 and 2 Results.

BACKGROUND: Health care spending is projected to increase throughout the next decade alongside the number of total joint arthroplasties (TJAs) performed. Such growth places significant financial burden on the economic system. To address these concerns, Bundled Payments for Care Improvement (BPCI) is becoming a favorable reimbursement model. The aim of this study is to present the outcomes with BPCI model focused on the post-acute care (PAC) phase and compare the outcomes between years 1 and 2 of implementation. METHODS: The Joint Utilization Management Program (JUMP) was implemented in January 2014. Inclusion criteria were Medicare patients undergoing primary unilateral in-patient TJA procedures, outpatient procedures that resulted in an in-hospital admission, and trauma episodes that required TJA. Scorecards monitoring surgeons' performance and tracking length of stay (LOS) in the PAC setting were established. The data generated from these scorecards guided percentage sum-allocation from the total gain-shared sum among the participating providers. RESULTS: A total of 683 JUMP patients were assessed over two years. PAC utilization decreased between 2014 and 2015. The average LOS was longer in year 1 than year 2 (4.50 vs 3.19 days). In-patient rehabilitation (IPR) decreased from 6.45% to 3.22%, with a decrease in IPR average LOS of 1.47 days. The rate of 30-day readmission was lower for JUMP patients in 2015 than 2014 (8.77% vs 10.56%), with day of readmission being earlier (11.91 days vs 13.71 days) in 2014. CONCLUSION: Under the BPCI program, our experience with the JUMP model demonstrates higher efficiency of care in the PAC setting through reduced LOS, IPR admission rates, and 30-day readmission rate.

Arthrofibrosis After Total Knee Arthroplasty: Pathophysiology, Diagnosis, and Management.

Arthrofibrosis is the pathologic stiffening of a joint caused by an exaggerated inflammatory response. As a common complication following total knee arthroplasty (TKA), this benign-appearing connective tissue hyperplasia can cause significant disability among patients because the concomitant knee pain and restricted range of motion severely hinder postoperative rehabilitation, clinical outcomes, and basic activities of daily living. The most effective management for arthrofibrosis in the setting of TKA is prevention, including preoperative patient education programs, aggressive postoperative physical therapy regimens, and anti-inflammatory medications. Operative treatments include manipulation under anesthesia, arthroscopic debridement, and quadricepsplasty.

Review article: Current literature on surgical checklists and handoff tools and application for orthopaedic surgery.

Despite the adaptation of checklists for specific surgeries being developed, there remains a lack of an available standard for an orthopaedic-specific checklist. Benefits of implementing checklists include cost-effectiveness as well as the ability to significantly reduce both mortality and complication rates in a variety of healthcare settings. The aim of this review is to analyze the evidence surrounding the effectiveness of checklists as well as recommend for the development of a standard checklist for specific orthopaedic surgeries such as total joint arthroplasty (TJA).

Implementation of a Hip Fracture Care Pathway Using Lean Six Sigma Methodology in a Level I Trauma Center.

INTRODUCTION: The application of Lean Six Sigma (LSS) methodology with regard to hip fracture care remains unexamined. The aim of this study is to illustrate the application of LSS principles in the implementation of a hip fracture integrated care pathway (ICP). METHODS: A multidisciplinary team at a level I trauma center formed a hip fracture ICP using LSS principles. An ICP aimed toward decreasing time to surgery to <48 hours was implemented in April 2012. RESULTS: A total of 505 hip fracture patients met inclusion criteria. A total of 221 patients entered the preimplementation cohort, and 284 were incorporated in the postimplementation cohort. The percentage of patients who received surgical fixation beyond 48 hours significantly decreased (9.50% versus 4.23%; P = 0.01). Significantly more complications were detected in the postimplementation cohort (62.44% versus 80.10%; P < 0.01). The postimplementation cohort showed a significantly shorter length of stay (P = 0.02) and decreased hospital cost (P = 0.016). CONCLUSION: Our findings suggest that using LSS methods in an ICP at our institution resulted in markedly greater percentage of patients receiving surgical care within 48 hours, greater detection of complication, and reduced resource consumption.

Improving Total Joint Replacement with Continuous Quality Improvement Methods and Tools.

Faced with increasing pressure to reduce costs, hospitals must find new ways to eliminate waste while simultaneously maintaining the highest quality of care. For any institution, these can types of changes can be complex and burdensome. This article outlines several methods that have been successful in reducing costs while maintaining high quality and highlights feasible methodologies that can help health care providers implement new quality improvement protocols.