Predictive Modeling of Medical and Orthopaedic-Related 90-Day-Readmissions Following Primary Total Knee Arthroplasty.

BACKGROUND: As the demand for total knee arthroplasty (TKA) escalates, 90-day readmissions have emerged as a pressing clinical and economic concern for the current value-based health care system. Consequently, health care providers have focused on estimating the risk levels of readmitted patients; however, it is unknown if specific factors are associated with different types of complications (ie, medical or orthopaedic-related) that lead to readmissions. Therefore, this study aimed to (1) determine the overall, medical-related, and orthopaedic-related 90-day readmission rate and (2) develop a predictive model for risk factors affecting overall, medical-related, and orthopaedic-related 90-day readmissions following TKA. METHODS: A prospective cohort of primary unilateral TKAs performed at a large tertiary academic center in the United States from 2016 to 2020 was included (n = 10,521 patients). Unplanned readmissions were reviewed individually to determine their primary cause, either medical or orthopaedic-related. Orthopaedic-related readmissions were specific complications affecting the joint, prosthesis, or surgical wound. Medical readmissions were due to any other cause requiring medical management. Multivariable logistic regression models were used to investigate associations between prespecified risk factors and 90-day readmissions, as well as medical and orthopaedic-related readmissions independently. RESULTS: Overall, the rate of 90-day readmissions was 6.7% (n = 704). Over 82% of these readmissions were due to medical-related causes (n = 580), with the remaining 18% being orthopaedic-related (n = 124) readmissions. The area under the curve for the 90-day readmission model was 0.68 (95% confidence interval: 0.67 to 0.70). Sex, smoking, length of stay, and discharge disposition were associated with orthopaedic readmission, while age, sex, race, the Charlson Comorbidity Index, insurance, surgery day, opioid overdose risk score, length of stay, and discharge disposition were associated with medical-related 90-day readmissions. CONCLUSIONS: Medical-related readmissions after TKA are more prevalent than orthopaedic-related readmissions. Through successfully constructing and validating multiple 90-day readmission predictive models, we highlight the distinct risk profiles for medical and orthopaedic-related readmissions. This emphasizes the necessity for nuanced, patient-specific risk stratification and preventive measures.

Predictive Modeling of Medical- and Orthopaedic-Related 90-Day Readmissions Following Primary Total Hip Arthroplasty.

BACKGROUND: The rate of unplanned hospital readmissions following total hip arthroplasty (THA) varies from 3 to 10%, representing a major economic burden. However, it is unknown if specific factors are associated with different types of complications (ie, medical or orthopaedic-related) that lead to readmissions. Therefore, this study aimed to: (1) determine the overall, medical-related, and orthopaedic-related 90-day readmission rate; and (2) develop a predictive model for risk factors affecting overall, medical-related, and orthopaedic-related 90-day readmissions following THA. METHODS: A prospective cohort of primary unilateral THAs performed at a large tertiary academic center in the United States from 2016 to 2020 was included (n = 8,893 patients) using a validated institutional data collection system. Orthopaedic-related readmissions were specific complications affecting the prosthesis, joint, and surgical wound. Medical readmissions were due to any other cause requiring medical management. Multivariable logistic regression models were used to investigate associations between prespecified risk factors and 90-day readmissions, as well as medical and orthopaedic-related readmissions independently. RESULTS: Overall, the rate of 90-day readmissions was 5.6%. Medical readmissions (4.2%) were found to be more prevalent than orthopaedic-related readmissions (1.4%). The area under the curve for the 90-day readmission model was 0.71 (95% confidence interval: 0.69 to 0.74). Factors significantly associated with medical-related readmissions were advanced age, Black race, education, Charlson Comorbidity Index, surgical approach, opioid overdose risk score, and nonhome discharge. In contrast, risk factors linked to orthopaedic-related readmissions encompassed body mass index, patient-reported outcome measure phenotype, nonosteoarthritis indication, opioid overdose risk, and nonhome discharge. CONCLUSIONS: Of the overall 90-day readmissions following primary THA, 75% were due to medical-related complications. Our successful predictive model for complication-specific 90-day readmissions highlights how different risk factors may disproportionately influence medical versus orthopaedic-related readmissions, suggesting that patient-specific, tailored preventive measures could reduce postoperative readmissions in the current value-based health care setting.

Conversion Birmingham Hip Resurfacing in Managing Post-traumatic Arthritis With Retained Femoral Hardware: A Case Report.

CASE: A 70-year-old man with a year-long history of arthritic pain in his left hip presented to our clinic. He had a left intertrochanteric hip fracture 6 years ago, fixed with an open reduction internal fixation with a cephalomedullary nail. He underwent a conversion Birmingham Hip Resurfacing (BHR) with removal of the proximal helicoidal blade and retention of the intramedullary nail. At 7-year follow-up, the patient reported satisfactory clinical outcomes and excellent radiographic fixation. CONCLUSION: This case highlights using conversion BHR in patients with post-traumatic arthritis with retained femoral hardware as an alternative to conventional total hip arthroplasty.

Surgical Management of Chronic Morel-Lavallée Lesion with Minimal Cosmetic Scarring: A Case Report.

Introduction: Morel-Lavallée lesion (MLL) is a closed degloving injury that occurs after traumatic damage to soft tissue, leading to the formation of an encapsulated serosanguinous collection of fluid. Although some MLLs resolve spontaneously, chronic MLLs present with a significant risk of infection and may impede patients' quality of life. Chronic lesions require surgical intervention to evacuate and debride the hematoma, often resulting in severe cosmetic damage postoperatively. Case Report: We documented a large 19.4 cm × 4.2 cm × 15.10 cm MLL on the right lateral hip that presented a significant impediment to the patient's daily functions. After the failure of conservative management, the patient was treated surgically through a minimal incision debridement procedure, utilizing a wound drain and vacuum-assisted compressional dressing upon closure. Excellent 1-year post-operative outcomes were achieved with no recurrence of the lesion and limited cosmetic evidence of the MLL. Conclusion: This case highlights the value of a limited incisional debridement procedure for the management of a chronic Morel-Lavellée lesion. When using this technique, surgeons can effectively treat these lesions with promising short-term outcomes and minimal wound scarring.

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence: A Critical Analysis Review.

¼ The application of artificial intelligence (AI) in the field of orthopaedic surgery holds potential for revolutionizing health care delivery across 3 crucial domains: (I) personalized prediction of clinical outcomes and adverse events, which may optimize patient selection, surgical planning, and enhance patient safety and outcomes; (II) diagnostic automated and semiautomated imaging analyses, which may reduce time burden and facilitate precise and timely diagnoses; and (III) forecasting of resource utilization, which may reduce health care costs and increase value for patients and institutions.¼ Computer vision is one of the most highly studied areas of AI within orthopaedics, with applications pertaining to fracture classification, identification of the manufacturer and model of prosthetic implants, and surveillance of prosthesis loosening and failure.¼ Prognostic applications of AI within orthopaedics include identifying patients who will likely benefit from a specified treatment, predicting prosthetic implant size, postoperative length of stay, discharge disposition, and surgical complications. Not only may these applications be beneficial to patients but also to institutions and payors because they may inform potential cost expenditure, improve overall hospital efficiency, and help anticipate resource utilization.¼ AI infrastructure development requires institutional financial commitment and a team of clinicians and data scientists with expertise in AI that can complement skill sets and knowledge. Once a team is established and a goal is determined, teams (1) obtain, curate, and label data; (2) establish a reference standard; (3) develop an AI model; (4) evaluate the performance of the AI model; (5) externally validate the model, and (6) reinforce, improve, and evaluate the model's performance until clinical implementation is possible.¼ Understanding the implications of AI in orthopaedics may eventually lead to wide-ranging improvements in patient care. However, AI, while holding tremendous promise, is not without methodological and ethical limitations that are essential to address. First, it is important to ensure external validity of programs before their use in a clinical setting. Investigators should maintain high quality data records and registry surveillance, exercise caution when evaluating others' reported AI applications, and increase transparency of the methodological conduct of current models to improve external validity and avoid propagating bias. By addressing these challenges and responsibly embracing the potential of AI, the medical field may eventually be able to harness its power to improve patient care and outcomes.

Lower 90-day inpatient readmission and 1-year reoperation in patients undergoing robotic versus manual total hip arthroplasty through an anterior approach.

BACKGROUND: The value of robotic-assisted total hip arthroplasty (rTHA) has yet to be determined compared to conventional manual THA (mTHA). OBJECTIVE: Evaluate 90-day inpatient readmission rates, rates of reoperation, and clinically significant improvement of patient-reported outcome measures (PROMs) at 1-year in a cohort of patients who underwent mTHA or rTHA through a direct anterior (DA) approach. METHODS: A single-surgeon, prospective institutional cohort of 362 patients who underwent primary THA for osteoarthritis via the DA approach between February 2019 and November 2020 were included. Patient demographics, surgical time, discharge disposition, length of stay, acetabular cup size, 90-day inpatient readmission, 1-year reoperation, and 1-year PROMs were collected for 148 manual and 214 robotic THAs, respectively. RESULTS: Patients undergoing rTHA had lower 90-day readmission (3.74% vs 9.46%, p= 0.04) and lower 1-year reoperation (0.93% vs 4.73% mTHA, p= 0.04). rTHA acetabular cup sizes were smaller (rTHA median 52, interquartile range [IQR] 50; 54, mTHA median 54, IQR 52; 58, p< 0.001). Surgical time was longer for rTHA (114 minutes vs 101 minutes, p< 0.001). At 1-year post-operatively, there was no difference in any of the PROMs evaluated. CONCLUSION: Robotic THA demonstrated lower 90-day readmissions and 1-year reoperation rates than manual THA via the DA approach. PROMs were not significantly different between the two groups at one year.

Advancements in treatment strategies for periprosthetic joint infections: A comprehensive review.

Periprosthetic joint infection (PJI) presents a critical challenge in orthopedic care, contributing to significant patient morbidity and healthcare costs. This burden is expected to increase secondary to growing demand for total joint arthroplasty (TJA). Despite the profound significance of PJI, there is currently no universally accepted "gold standard" diagnostic criteria using serum biomarker thresholds; latest criteria fail to differentiate acute infections from chronic or consider time since initial surgery. Furthermore, contemporary PJI treatment, which conventionally requires 2-stage revision surgery in conjunction with rigorous antibiotic treatment, can be particularly taxing on patients. Fortunately, recent years have seen marked evolution in both PJI diagnosis and treatment methods. Contemporary research supports time-dependent serum biomarker thresholds with greater sensitivity and specificity than previously reported, as well as alternative surgical options which may be more suitable for certain patients. The following narrative review aims to describe the significance and pathogenesis of PJI before characterizing current challenges, novel innovations, and the future landscape of PJI diagnosis and management. Here, we spotlight the emerging utility of novel biomarkers and metagenomic next-generation sequencing for diagnosis, advancements in patient-centered surgical outcome prediction tools for PJI risk assessment and prevention, and evolving surgical techniques including 1-stage and a "hybrid" 1.5-stage revision surgeries. Additionally, we explore cutting-edge therapeutic modalities including peptide and bacteriophage-based treatments, intraoperative anti-biofilm gel, the VT-X7 antibiotic pump, and promising immune-based interventions. Ultimately, these advancements hold the potential to revolutionize PJI management, offering hope for improved outcomes and reduced burdens on healthcare systems.

Nuclear Imaging in Orthopaedic Practice: A Critical Analysis Review.

¼ Nuclear imaging techniques, including bone scintigraphy, labeled leukocyte scintigraphy, positron emission tomography (PET), and single-photon emission computed tomography (SPECT) combined with computed tomography (CT), have wide applications in orthopaedics for evaluating trauma, painful total joint arthroplasty, musculoskeletal infection, and orthopaedic oncology.¼ Three-phase bone scintigraphy is a first-line, highly sensitive nuclear medicine study for evaluating orthopaedic pathology when initial studies are inconclusive. However, its specificity is limited, and findings may be falsely positive for up to 2 years after total joint arthroplasty because of physiologic bone remodeling.¼ Labeled leukocyte scintigraphy or gallium scintigraphy can improve diagnostic accuracy in patients with a positive bone scan and suspected musculoskeletal or periprosthetic joint infection.¼ 18-Fluorodeoxyglucose PET/CT demonstrates high sensitivity and specificity for diagnosing bone neoplasms, infections, and metabolic disorders. Emerging PET/magnetic resonance imaging technology offers reduced radiation exposure and greater soft-tissue detail but presents technical and cost challenges.¼ SPECT/CT provides valuable functional and anatomic detail for characterizing the extent and location of bone pathology, serving as an important adjunct to other imaging modalities.¼ Ultimately, the choice of nuclear imaging modality should consider the specific clinical context, diagnostic accuracy, impact on management, and cost-effectiveness on a case-by-case basis.

A Longitudinal analysis of weight changes before and after total hip arthroplasty: Weight trends, patterns, and predictors.

BACKGROUND: It is crucial to understand weight trends in patients undergoing total hip arthroplasty (THA). OBJECTIVE: To evaluate preoperative and postoperative weight trends for patients undergoing primary THA and factors associated with clinically significant weight change. METHODS: A prospective cohort who underwent primary unilateral THA (n= 3,011) at a tertiary healthcare system (January 2016 to December 2019) were included in the study. The primary outcomes were clinically significant weight change (> 5% change in body mass index [BMI]) during the one-year preoperative and one-year postoperative periods. RESULTS: Preoperatively, 66.6% maintained a stable weight, 16.0% gained and 17.4% lost weight, respectively. Postoperatively, 64.0% maintained a stable weight, while 22.6% gained and 13.4% lost weight, respectively. Female sex, Black race, obesity, higher Charlson Comorbidity Index (CCI) scores, and older age were associated with preoperative weight loss. Female sex, obesity, higher CCI scores, and Medicare insurance were associated with postoperative weight loss. Preoperative weight loss was associated with postoperative weight gain (OR = 3.37 [CI: 2.67 to 4.25]; p< 0.001), and preoperative weight gain was associated with postoperative weight loss (OR = 1.74 [CI: 1.30 to 2.3]; p< 0.001). CONCLUSION: Most patients maintained a stable BMI one-year before and one-year after THA. Several factors are associated with weight loss before and after THA. Preoperative weight changes were associated with a reciprocal rebound in BMI post-operatively.