A Nationwide Analysis of the Impact of Socioeconomic Status on Complications and Healthcare Utilizations After Total Knee Arthroplasty Using the Area Deprivation Index: Consideration of the Disadvantaged Patient.

INTRODUCTION: Socioeconomic status (SES) has been demonstrated to be an important prognostic risk factor among patients undergoing total joint arthroplasty. We evaluated patients living near neighborhoods with higher socioeconomic risk undergoing total knee arthroplasty (TKA) and if they were associated with differences in: 1) medical complications; 2) emergency department (ED) utilizations; 3) readmissions; and 4) costs of care. METHODS: A query of a national database from 2010 to 2020 was performed for primary TKAs. The Area Deprivation Index (ADI) is a weighted index comprised of 17 census-based markers of material deprivation and poverty. Higher numbers indicate a greater disadvantage. Patients undergoing TKA in zip codes associated with high ADI (90%+) were 1:1 propensity-matched to a comparison group by age, sex, and Elixhauser Comorbidity Index (ECI). This yielded 225,038 total patients, evenly matched between cohorts. Outcomes studied included complications, ED utilizations, readmission rates, and 90-day costs. Logistic regression models computed the odds ratios (OR) of ADI on the dependent variables. P-values less than 0.003 were significant. RESULTS: High ADI led to higher rates and odds of any medical complications (11.7 versus 11.0%; OR: 1.05, P = 0.0006), respiratory failures (0.4 versus 0.3%; OR: 1.28, P = 0.001), and acute kidney injuries (1.7 versus 1.5%; OR: 1.15, P < 0.0001). Despite lower readmission rates (2.9 versus 3.5%), high ADI patients had greater 90-day ED visits (4.2 versus 4.0%; OR: 1.07, P = 0.0008). The 90-day expenditures ($15,066 versus $12,459; P < 0.0001) were higher in patients who have a high ADI. CONCLUSION: Socioeconomically disadvantaged patients have increased complications and ED utilizations. Neighborhood disadvantage may inform healthcare policy and improve post-discharge care. The SES metrics, including ADI (which captures community effects), should be used to adequately risk-adjust or risk-stratify patients so that access to care for deprived regions and patients is not lost.

24-Year-Old Patient with Klippel-Trenaunay Syndrome Underwent Cementless Robotic Cruciate-Retaining TKA: A Case Report.

CASE: A 24-year-old man with Klippel-Trenaunay syndrome (KTS) presented with severe knee osteoarthritis unresponsive to conservative measures. Owing to end-stage, debilitating arthritic symptoms, surgery was pursued. Careful preoperative, multidisciplinary planning/treatment included magnetic resonance imaging to characterize the venous malformations throughout the right lower extremity, preoperative sclerotherapy, sirolimus, and robotic-assisted cementless total knee arthroplasty (TKA). CONCLUSION: Cementless robotic-assisted TKA with selective patellar resurfacing can be a viable option for young KTS patients with severe osteoarthritis when a meticulous multidisciplinary approach, including sclerotherapy and advanced imaging, is undertaken to analyze vascular abnormalities, minimize surgical risks, preserve bone stock, and optimize outcomes.

High Area Deprivation Index is Associated With Not Achieving the Patient-acceptable Symptom State After TKA.

BACKGROUND: The Area Deprivation Index (ADI) approximates a patient's relative socioeconomic deprivation. The ADI has been associated with increased healthcare use after TKA, but it is unknown whether there is an association with patient-reported outcome measures (PROMs). Given that a high proportion of patients are dissatisfied with their results after TKA, and the large number of these procedures performed, knowledge of factors associated with PROMs may indicate opportunities to provide support to patients who might benefit from it. QUESTIONS/PURPOSES: (1) Is the ADI associated with achieving the minimum clinically important difference (MCID) for the Knee Injury and Osteoarthritis Outcome Score (KOOS) for pain, Joint Replacement (JR), and Physical Function (PS) short forms after TKA? (2) Is the ADI associated with achieving the patient-acceptable symptom state (PASS) thresholds for the KOOS pain, JR, and PS short forms? METHODS: This was a retrospective study of data drawn from a longitudinally maintained database. Between January 2016 and July 2021, a total of 12,239 patients underwent unilateral TKA at a tertiary healthcare center. Of these, 92% (11,213) had available baseline PROM data and were potentially eligible. An additional 21% (2400) of patients were lost before the minimum study follow-up of 1 year or had incomplete data, leaving 79% (8813) for analysis here. The MCID is the smallest change in an outcome score that a patient is likely to perceive as a clinically important improvement, and the PASS refers to the threshold beyond which patients consider their symptoms acceptable and consistent with adequate functioning and well-being. MCIDs were calculated using a distribution-based method. Multivariable logistic regression models were created to investigate the association of ADI with 1-year PROMs while controlling for patient demographic variables. ADI was stratified into quintiles based on their distribution in our sample. Achievement of MCID and PASS thresholds was determined by the improvement between preoperative and 1-year PROMs. RESULTS: After controlling for patient demographic factors, ADI was not associated with an inability to achieve the MCID for the KOOS pain, KOOS PS, or KOOS JR. A higher ADI was independently associated with an increased risk of inability to achieve the PASS for KOOS pain (for example, the odds ratio of those in the ADI category of 83 to 100 compared with those in the 1 to 32 category was 1.34 [95% confidence interval 1.13 to 1.58]) and KOOS JR (for example, the OR of those in the ADI category of 83 to 100 compared with those in the 1 the 32 category was 1.29 [95% CI 1.10 to 1.53]), but not KOOS PS (for example, the OR of those in the ADI category of 83 to 100 compared with those in the 1 the 32 category was 1.09 [95% CI 0.92 to 1.29]). CONCLUSION: Our findings suggest that social and economic factors are associated with patients' perceptions of their overall pain and function after TKA, but such factors are not associated with patients' perceptions of their improvement in symptoms. Patients from areas with higher deprivation may be an at-risk population and could benefit from targeted interventions to improve their perception of their healthcare experience, such as through referrals to nonemergent medical transportation and supporting applications to local care coordination services before proceeding with TKA. Future research should investigate the mechanisms underlying why socioeconomic disadvantage is associated with inability to achieve the PASS, but not the MCID, after TKA. LEVEL OF EVIDENCE: Level III, therapeutic study.

Custom Triflange Acetabular Implants for Complex Hip Revisions: A Case Series.

Revision total hip arthroplasty (THA) presents a formidable challenge when addressing extensive acetabular defects, particularly in severe cases classified under Paprosky types 3A and 3B and American Academy of Orthopaedic Surgeons types 3 and 4. Traditional methods often fall short, prompting the potential use of custom triflange acetabular components or patient-specific acetabular implants (PSAIs). These implants are specifically designed to conform to an individual's anatomy, aiming to enhance defect reconstruction and pelvic stabilization. This case series describes the utilization of advanced 3-dimensional printing and rapid prototyping technologies to construct customized acetabular components, which can be instrumental in enabling precise preoperative planning and surgical execution for these difficult acetabular cases and potentially leading to improved surgical outcomes.

How-To Create an Orthopaedic Systematic Review: A Step-by-Step Guide Part I: Study Design.

Systematic reviews are conducted through a consistent and reproducible method to search, appraise, and summarize information. Within the evidence-based pyramid, systematic reviews can be at the apex when incorporating high-quality studies, presenting the strongest form of evidence given their synthesis of results from multiple primary studies to level IV evidence, depending on the studies they incorporate. When combined and supplemented with a meta-analysis using statistical methods to pool the results of three or more studies, systematic reviews are powerful tools to help answer research questions. The aim of this review is to serve as a guide on how to: 1) design; 2) execute; and 3) publish an orthopaedic arthroplasty systematic review and meta-analysis. In Part I, we discuss how to develop an appropriate research question as well as source and screen databases. To date, commonly used databases to source studies include PubMed/MEDLINE, Embase, Cochrane Library, Scopus, and Web of Science. Although not all-encompassing, this paper serves as a starting point for those interested in performing and/or critically reviewing lower extremity arthroplasty systematic reviews and meta-analyses.

How-To Create an Orthopaedic Systematic Review: A Step-by-Step Guide. Part III: Executing a Meta-Analysis.

At the top of the evidence-based pyramid, systematic reviews stand out as the most powerful, synthesizing findings from numerous primary studies. Specifically, a quantitative systematic review, known as a meta-analysis, combines results from various studies to address a specific research question. This review serves as a guide on how to: (1) design; (2) perform; and (3) publish an orthopedic arthroplasty systematic review. In Part III, we focus on how to design and perform a meta-analysis. We delineate the advantages and disadvantages of meta-analyses compared to systematic reviews, acknowledging their potential challenges due to time constraints and the complexities posed by study heterogeneity and data availability. Despite these obstacles, a well-executed meta-analysis contributes precision and heightened statistical power, standing at the apex of the evidence-based pyramid. The design of a meta-analysis closely mirrors that of a systematic review, but necessitates the inclusion of effect sizes, variability measures, sample sizes, outcome measures, and overall study characteristics. Effective data presentation involves the use of forest plots, along with analyses for heterogeneities and subgroups. Widely-used software tools are common in this domain, and there is a growing trend toward incorporating artificial intelligence software. Ultimately, the intention is for these papers to act as foundational resources for individuals interested in conducting systematic reviews and meta-analyses in the context of orthopaedic arthroplasty, where applicable.

Patient satisfaction and patient-reported outcomes do not vary by BMI class in total hip arthroplasty.

PURPOSE: Obesity has been identified as a risk factor for postoperative complications in patients undergoing total hip arthroplasty (THA). This study aimed to investigate patient-reported outcomes, pain, and satisfaction as a function of body mass index (BMI) class in patients undergoing THA. METHODS: 1736 patients within a prospective observational study were categorized into BMI classes. Pre- and postoperative Hip disability and Osteoarthritis Outcome Score for Joint Replacement (HOOS JR), satisfaction, and pain scores were compared by BMI class using one-way ANOVA. RESULTS: Healthy weight patients reported the highest preoperative HOOS JR (56.66 ± 13.35) compared to 45.51 ± 14.45 in Class III subjects. Healthy weight and Class III patients reported the lowest (5.65 ± 2.01) and highest (7.06 ± 1.98, p < 0.0001) preoperative pain, respectively. Changes in HOOS JR scores from baseline suggest larger improvements with increasing BMI class, where Class III patients reported an increase of 33.7 ± 15.6 points at 90 days compared to 26.1 ± 17.1 in healthy weight individuals (p = 0.002). Fewer healthy weight patients achieved the minimal clinically important difference (87.4%) for HOOS JR compared to Class II (96.5%) and III (94.7%) obesity groups at 90 days postoperatively. Changes in satisfaction and pain scores were largest in the Class III patients. Overall, no functional outcomes varied by BMI class postoperatively. CONCLUSION: Patients of higher BMI class reported greater improvements following THA. While risk/benefit shared decision-making remains a personalized requirement of THA, this study highlights that utilization of BMI cutoff may not be warranted based on pain and functional improvement.

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.

How to Raise the Bar in the Capture of Patient-Reported Outcome Measures in Total Joint Arthroplasty: Results from Active and Passive Follow-up Measures.

BACKGROUND: With the upcoming U.S. Centers for Medicare & Medicaid Services 2027 policy for mandatory reporting of patient-reported outcome measures (PROMs) for total hip or knee arthroplasty (THA or TKA), it is important to evaluate the resources required to achieve adequate PROM collection and reporting at a clinically relevant rate of follow-up. This study aimed to (1) determine follow-up rates for 1-year PROMs when the follow-up was conducted with active methods (attempted contact by staff) and passive (automated) methods, and (2) evaluate factors associated with higher odds of requiring active follow-up or being lost to follow-up following THA or TKA. METHODS: A prospective cohort of patients undergoing primary elective THA (n = 7,436) or TKA (n = 10,119) between January 2016 and December 2020 at a single institution were included. The primary outcome was the response rate achieved with active and passive follow-up methods at our institution. Patient characteristics, health-care utilization parameters, PROM values, and patient satisfaction were compared between follow-up methods. RESULTS: Passive and active measures were successful for 38% (2,859) and 40% (3,004) of the THA cohort, respectively, while 21% (1,573) were lost to follow-up. Similarly, passive and active measures were successful for 40% (4,001) and 41% (4,161) of the TKA cohort, respectively, while 20% (2,037) were lost to follow-up. Younger age, male sex, Black or another non-White race, fewer years of education, smoking, Medicare or Medicaid insurance, and specific baseline PROM phenotypes (i.e., with scores in the lower half for pain, function, and/or mental health) were associated with loss to follow-up. Older age, male sex, Black race, and a residence with a higher Area Deprivation Index were associated with requiring active follow-up. CONCLUSIONS: One of 5 patients were lost to follow-up despite active and passive measures following THA or TKA. These patients were more likely to be younger, be male, be of Black or another non-White race, have fewer years of education, be a smoker, have Medicaid insurance, and have specific baseline PROM phenotypes. Innovative strategies aimed at targeting individuals with these baseline characteristics may help raise the bar and increase follow-up while mitigating costs after total joint arthroplasty. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

The Mark Coventry Award: PhotothermAA Gel Combined With Debridement, Antibiotics, and Implant Retention Significantly Decreases Implant Biofilm Burden and Soft-Tissue Infection in a Rabbit Model of Knee Periprosthetic Joint Infection.

BACKGROUND: Chronic periprosthetic joint infection (PJI) is a major complication of total joint arthroplasty. The underlying pathogenesis often involves the formation of bacterial biofilm that protects the pathogen from both host immune responses and antibiotics. The gold standard treatment requires implant removal, a procedure that carries associated morbidity and mortality risks. Strategies to preserve the implant while treating PJI are desperately needed. Our group has developed an anti-biofilm treatment, PhotothermAA gel, which has shown complete eradication of 2-week-old mature biofilm in vitro. In this study, we tested the anti-biofilm efficacy and safety of PhotothermAA in vivo when combined with debridement, antibiotics and implant retention (DAIR) in a rabbit model of knee PJI. METHODS: New Zealand white rabbits (n = 21) underwent knee joint arthrotomy, titanium tibial implant insertion, and inoculation with Xen36 (bioluminescent Staphylococcus aureus) after capsule closure. At 2 weeks, rabbits underwent sham surgery (n = 6), DAIR (n = 6), or PhotothermAA with DAIR (n = 9) and were sacrificed 2 weeks later to measure implant biofilm burden, soft-tissue infection, and tissue necrosis. RESULTS: The combination of anti-biofilm PhotothermAA with DAIR significantly decreased implant biofilm coverage via scanning electron microscopy compared to DAIR alone (1.8 versus 81.0%; P < .0001). Periprosthetic soft-tissue cultures were significantly decreased in the PhotothermAA with DAIR treatment group (log reduction: Sham 1.6, DAIR 2.0, combination 5.6; P < .0001). Treatment-associated necrosis was absent via gross histology of tissue adjacent to the treatment area (P = .715). CONCLUSIONS: The addition of an anti-biofilm solution like PhotothermAA as a supplement to current treatments that allow implant retention may prove useful in PJI treatment.

New CMS Policy on the Mandatory Collection of Patient-Reported Outcome Measures for Total Hip and Knee Arthroplasty by 2027: What Orthopaedic Surgeons Should Know.

ABSTRACT: The Centers for Medicare & Medicaid Services (CMS) has finalized a landmark national policy to standardize and expand the collection and reporting of patient-reported outcome measures (PROMs) following total hip arthroplasty (THA) and total knee arthroplasty (TKA). This policy will be rolled out through phased implementation, beginning with voluntary reporting starting in 2023 and transitioning to mandatory reporting starting in 2025, which will be tied to hospital payment determinations in fiscal year 2028. The overarching goal of this policy is to gather meaningful pre- and postoperative PROM data directly from patients to enhance clinical care, shared decision-making, and quality measurement for these common elective procedures. This national initiative underscores the value of incorporating patient perspectives and priorities into assessments of surgical care quality. For orthopaedic surgeons and hospitals, participating in the initial voluntary reporting period provides an opportunity to integrate PROM collection into clinical workflows and to leverage these data to improve patient care. The achievement of robust PROM response rates and a strong performance on the underlying THA/TKA Patient-Reported Outcome-Based Performance Measure may have increasing relevance as payment models shift toward value-based care. The aim of the present forum was to provide an in-depth review of this new CMS policy and key details regarding required PROM instruments, data-collection time frames, and other specifications that surgical teams should understand as they prepare for implementation. The goal was to equip orthopaedic surgeons with actionable information as they embark on this new era of national PROM collection and reporting.

Market resilience of orthopaedic hip/knee arthroplasty sales during COVID-19.

INTRODUCTION: The coronavirus 2019 (COVID-19) pandemic led to a marked decrease in elective surgical volume and orthopaedic device sales. The aim of this paper was to quantify this decrease and the related financial impact on the largest hip/knee arthroplasty companies by: (1) tracking individual hip/knee company valuations; (2) calculating aggregate changes in overall hip/knee arthroplasty market valuations; and (3) quantifying quarterly hip/knee revenues relative to prior years. MATERIALS AND METHODS: Financial data on the top five hip/knee arthroplasty companies by size between January 1, 2019, and October 1, 2020, was collected from a Wall Street financial database, S&P Capital IQ. Changes in valuation of these companies were compared against benchmark market indices, the S&P500 and Vanguard Healthcare ETF. U.S. hip/knee arthroplasty-specific revenue for Q1 and Q2 of 2019 and 2020 was collected from Securities Exchange Commission 10-Q forms. Quarterly revenue changes were calculated using 1-2Q19 revenues as baselines and aggregate to approximate the overall hip/knee arthroplasty market. RESULTS: The top five hip/knee companies lost $179.2 billion (32.7% loss) in market value from pre COVID-19 market highs to COVID-19 market lows (March 2020), while S&P500 and Vanguard Healthcare ETF decreased 36.1 and 33.2%, respectively. From market lows to October 2020, arthroplasty companies rallied 38.6% while the S&P500 and Vanguard Healthcare ETF regained 43.5 and 56.4% respectively. Notably, this occurred while aggregate 1Q/2Q20 revenue lagged 7.1/41.8% relative to 2019, with an overall decrease of $1.58B (24.8%). CONCLUSIONS: Similar to the overall market and healthcare sector, the top five hip/knee arthroplasty companies have recovered from their COVID market lows. Our results reveal that the valuations of hip/knee companies remained robust during COVID, even as revenues fell, likely due to strong investor confidence in the industry outlook and the greater overall healthcare system utilization.

Outpatient Total Hip Arthroplasty Volume up Nearly 8-Fold After Regulatory Changes With Expanding Demographics and Unchanging Outcomes: A 10-Year Analysis.

BACKGROUND: With the removal of total hip arthroplasty (THA) from the inpatient-only (IPO) lists, the orthopedic landscape across the United States has changed rapidly. Thus, this study aimed to: 1) characterize the change in THA volume for outpatient and inpatient surgeries; 2) elucidate demographical differences before and after removal from the IPO list; and 3) analyze 30-day complications, readmissions, and reoperations. METHODS: The National Surgical Quality Improvement Program database was queried for primary THAs between January 2010 and December 2021. The primary outcome was the annual volume of outpatient and inpatient THAs. Secondary outcomes involved 30-day complications, readmissions, and reoperations. The variables between cohorts were analyzed using goodness-of-fit Chi-square tests with summary statistics. RESULTS: Of the 332,423 THAs between 2010 and 2021, 88% were inpatient THAs (n = 292,974) and 12% were outpatient THAs (n = 39,449). From 2019 to 2021, the volume of inpatient THA decreased by 55% (42,779 to 19,075), while outpatient THA increased by 751% (2,518 to 21,424). Patients who had a THA after 2019 were older (P < .001), more commonly women (P < .001), white (P < .001), and more likely American Society of Anesthesiologists Class III (P < .001). The outpatient cohort had fewer 30-day complications, readmissions, and reoperations. The length of stay for both cohorts decreased until 2019, before increasing in 2020 and 2021 for inpatient THAs, while home discharge and operative time increased for both. CONCLUSIONS: The volume of outpatient THA increased almost eightfold after its removal from the IPO lists in 2020. Despite expanding eligibility with older patients and more comorbidities, 30-day complications, readmissions, and reoperations remain low. These findings support the safe transition to outpatient THA with appropriate patient selection and optimization.

What Are the Diagnosis-Specific Thresholds of Minimal Clinically Important Difference and Patient Acceptable Symptom State in Hip Disability and Osteoarthritis Outcome Score After Primary Total Hip Arthroplasty?

BACKGROUND: This study aimed to determine the minimal clinically important difference (MCID) and Patient Acceptable Symptom State (PASS) thresholds for Hip Disability and Osteoarthritis Outcome Score (HOOS) pain, physical short form (PS), and joint replacement (JR) 1 year after primary total hip arthroplasty stratified by preoperative diagnosis of osteoarthritis (OA) versus non-OA. METHODS: A prospective institutional cohort of 5,887 patients who underwent primary total hip arthroplasty (January 2016 to December 2018) was included. There were 4,184 patients (77.0%) who completed a one-year follow-up. Demographics, comorbidities, and baseline and one-year HOOS pain, PS, and JR scores were recorded. Patients were stratified by preoperative diagnosis: OA or non-OA. Minimal detectable change (MDC) and MCIDs were estimated using a distribution-based approach. The PASS values were estimated using an anchor-based approach, which corresponded to a response to a satisfaction question at one year post surgery. RESULTS: The MCID thresholds were slightly higher in the non-OA cohort versus OA patients. (HOOS-Pain: OA: 8.35 versus non-OA: 8.85 points; HOOS-PS: OA: 9.47 versus non-OA: 9.90 points; and HOOS-JR: OA: 7.76 versus non-OA: 8.46 points). Similarly, all MDC thresholds were consistently higher in the non-OA cohort compared to OA patients. The OA cohort exhibited similar or higher PASS thresholds compared to the non-OA cohort for HOOS-Pain (OA: ≥80.6 versus non-OA: ≥77.5 points), HOOS-PS (OA: ≥83.6 versus non-OA: ≥83.6 points), and HOOS-JR (OA: ≥76.8 versus non-OA: ≥73.5 points). A similar percentage of patients achieved MCID and PASS thresholds regardless of preoperative diagnosis. CONCLUSIONS: While MCID and MDC thresholds for all HOOS subdomains were slightly higher among non-OA than OA patients, PASS thresholds for HOOS pain and JR were slightly higher in the OA group. The absolute magnitude of the difference in these thresholds may not be sufficient to cause major clinical differences. However, these subtle differences may have a significant impact when used as indicators of operative success in a population setting.

Assessing Ability for ChatGPT to Answer Total Knee Arthroplasty-Related Questions.

BACKGROUND: Artificial intelligence in the field of orthopaedics has been a topic of increasing interest and opportunity in recent years. Its applications are widespread both for physicians and patients, including use in clinical decision-making, in the operating room, and in research. In this study, we aimed to assess the quality of ChatGPT answers when asked questions related to total knee arthroplasty. METHODS: ChatGPT prompts were created by turning 15 of the American Academy of Orthopaedic Surgeons Clinical Practice Guidelines into questions. An online survey was created, which included screenshots of each prompt and answers to the 15 questions. Surgeons were asked to grade ChatGPT answers from 1 to 5 based on their characteristics: (1) relevance, (2) accuracy, (3) clarity, (4) completeness, (5) evidence-based, and (6) consistency. There were 11 Adult Joint Reconstruction fellowship-trained surgeons who completed the survey. Questions were subclassified based on the subject of the prompt: (1) risk factors, (2) implant/intraoperative, and (3) pain/functional outcomes. The average and standard deviation for all answers, as well as for each subgroup, were calculated. Inter-rater reliability (IRR) was also calculated. RESULTS: All answer characteristics were graded as being above average (ie, a score > 3). Relevance demonstrated the highest scores (4.43 ± 0.77) by surgeons surveyed, and consistency demonstrated the lowest scores (3.54 ± 1.10). ChatGPT prompts in the Risk Factors group demonstrated the best responses, while those in the Pain/Functional Outcome group demonstrated the lowest. The overall IRR was found to be 0.33 (poor reliability), with the highest IRR for relevance (0.43) and the lowest for evidence-based (0.28). CONCLUSIONS: ChatGPT can answer questions regarding well-established clinical guidelines in total knee arthroplasty with above-average accuracy but demonstrates variable reliability. This investigation is the first step in understanding large language model artificial intelligence like ChatGPT and how well they perform in the field of arthroplasty.

Does Your Patient Need to Lose Weight? Weight Change Before and After Total Hip Arthroplasty Does Not Affect Health Care Utilization and Achievement of the Minimal Clinically Important Difference.

BACKGROUND: Despite the potential negative impact of preoperative obesity on total hip arthroplasty (THA) outcomes, the association between preoperative and postoperative weight change and outcomes is much less understood. Therefore, this study aimed to determine the impact of preoperative and postoperative weight change and preoperative body mass index (BMI) on health care utilization, satisfaction, and achievement of minimal clinically important difference (MCID) for Hip Disability and Osteoarthritis Outcome Score Physical Function Short-Form (HOOS PS) and HOOS Pain. METHODS: Patients who underwent primary elective unilateral THA between January 2016 and December 2019 were included (N = 2,868). Multivariable logistic regression assessed the association between BMI and preoperative and postoperative weight change on outcomes while controlling for demographic characteristics. RESULTS: There was no association between preoperative weight change and prolonged length of stay (> 3 days), 90-day readmission, nonhome discharge, patient dissatisfaction at 1 year, or achievement of HOOS Pain or HOOS PS MCID. Postoperative weight loss was an independent risk factor for patient dissatisfaction at 1 year but was not associated with achievement of either HOOS Pain or HOOS PS MCID at 1-year postoperative. Preoperative obesity classes I to III were independent risk factors for nonhome discharge. Nevertheless, preoperative obesity class I and class II were associated with an increased probability of reaching HOOS Pain MCID. Preoperative BMI was not associated with an increased risk of patient dissatisfaction. CONCLUSIONS: Preoperative weight change does not appear to influence health care utilization, satisfaction, or achievement of MCID in pain and function following THA. Postoperative weight loss may play a role as a risk factor for dissatisfaction following THA. Additionally, patients who had a higher baseline BMI may be more likely to see improvement in pain following THA. Therefore, when counseling obese patients for THA, surgeons must balance the risk of perioperative complications with the expectation of greater improvements in pain.

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.

Are Femoral Stems in Primary Total Knee Arthroplasty Cost Effective in High Fracture Risk Patients? A Risk Model and Cost Analysis.

Femoral stemmed total knee arthroplasty (FS TKA) may be used in patients deemed higher risk for periprosthetic fracture (PPF) to reduce PPF risk. However, the cost effectiveness of FS TKA has not been defined. Using a risk modeling analysis, we investigate the cost effectiveness of FS in primary TKA compared with the implant cost of revision to distal femoral replacement (DFR) following PPF. A model of risk categories was created representing patients at increasing fracture risk, ranging from 2.5 to 30%. The number needed to treat (NNT) was calculated for each risk category, which was multiplied by the increased cost of FS TKA and compared with the cost of DFR. The 50th percentile implant pricing data for primary TKA, FS TKA, and DFR were identified and used for the analysis. FS TKA resulted in an increased cost of $2,717.83, compared with the increased implant cost of DFR of $27,222.29. At 50% relative risk reduction with FS TKA, the NNT for risk categories of 2.5, 10, 20, and 30% were 80, 20, 10, and 6.67, respectively. At 20% risk, FS TKA times NNT equaled $27,178.30. A 10% absolute risk reduction in fracture risk obtained with FS TKA is needed to achieve cost neutrality with DFR. FS TKA is not cost effective for low fracture risk patients but may be cost effective for patients with fracture risk more than 20%. Further study is needed to better define the quantifiable risk reduction achieved in using FS TKA and identify high-risk PPF patients.

Despite Greater Improvement in Pain and Function Among Obese Patients Shortly After Total Knee Arthroplasty, There is No Difference in Patient-Reported Outcomes and Satisfaction Between Body Mass Index Classes at 1 Year Postoperatively.

BACKGROUND: Although obesity may be associated with an increased risk of perioperative and postoperative complications after total knee arthroplasty (TKA), body mass index (BMI) cutoffs for TKA patient selection remain a controversial topic. This study aimed to investigate patient-reported outcomes, satisfaction, and pain among BMI classes at 3 months and 1 year following TKA. METHODS: A total of 2,365 patients were categorized into Centers for Disease Control BMI classes according to preoperative values. The BMI distribution over the cohort demonstrated 7 underweight, 340 healthy weight, 731 overweight, 666 Class I, 391 Class II, and 230 Class III obesity. Preoperative and postoperative Knee injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR), satisfaction, and pain scores were compared by BMI class by Analysis of Variance with pairwise comparisons. RESULTS: Preoperative KOOS JR scores and satisfaction scores were both significantly greater for healthy weight patients compared to Class III patients (P < .0001). However, KOOS JR, satisfaction, and pain did not vary by BMI class postoperatively. Changes in scores from baseline suggest larger improvements with increasing BMI class, where Class III patients reported the greatest improvements in KOOS JR (23.24 ± 15.67, P < .0001) and pain scores (-3.56 ± 2.65, P < .0001) at 90 days. Significantly greater improvement with increasing BMI was also present at 1-year postoperatively for KOOS JR scores. A total of 85.8% of Class III patients reached the Minimal Clinically Important Difference for KOOS JR at 90 days compared to 76.8% of the healthy weight group (P = .03). Differences between BMI groups in the proportion reaching Minimal Clinically Important Difference at 1 year were not significant. CONCLUSIONS: Patients of higher BMI reported greater and earlier improvements in satisfaction, knee function, and pain following TKA. Shared decision-making remains paramount to preoperative surgical evaluation. However, rationing of this surgical intervention based on BMI alone may not be warranted.

Diagnosis-Specific Thresholds of the Minimal Clinically Important Difference and Patient Acceptable Symptom State for KOOS After Total Knee Arthroplasty.

BACKGROUND: Literature-reported minimal clinically important difference (MCID) and patient acceptable symptom state (PASS) thresholds for patient-reported outcome measures demonstrate marked variability. The purpose of this study was to determine the minimal detectable change (MDC), MCID, and PASS thresholds for the Knee injury and Osteoarthritis Outcome Score (KOOS) Pain subdomain, Physical Function Short Form (PS), and Joint Replacement (JR) among patients with osteoarthritis (OA) who underwent primary total knee arthroplasty (TKA). METHODS: A prospective cohort of 6,778 patients who underwent primary TKA was analyzed. Overall, 1-year follow-up was completed by 5,316 patients for the KOOS Pain, 5,018 patients for the KOOS PS, and 4,033 patients for the KOOS JR. A total of 5,186 patients had an OA diagnosis; this group had an average age of 67.0 years and was 59.9% female and 80.4% White. Diagnosis-specific MDCs and MCIDs were estimated with use of a distribution-based approach. PASS values were estimated with use of an anchor-based approach, which corresponded to a response to a satisfaction question at 1 year postoperatively. RESULTS: The MCID thresholds for the OA group were 7.9 for the KOOS Pain, 8.0 for the KOOS PS, and 6.7 for the KOOS JR. A high percentage of patients achieved the MCID threshold for each outcome measure (KOOS Pain, 95%; KOOS PS, 88%; and KOOS JR, 94%). The MDC 80% to 95% confidence intervals ranged from 9.1 to 14.0 for the KOOS Pain, 9.2 to 14.1 for the KOOS PS, and 7.7 to 11.8 for the KOOS JR. The PASS thresholds for the OA group were 77.7 for the KOOS Pain (achieved by 73% of patients), 70.3 for the KOOS PS (achieved by 68% of patients), and 70.7 for the KOOS JR (achieved by 70% of patients). CONCLUSIONS: The present study provided useful MCID, MDC, and PASS thresholds for the KOOS Pain, PS, and JR for patients with OA. The diagnosis-specific metrics established herein can serve as benchmarks for clinically meaningful postoperative improvement. Future research and quality assessments should utilize these OA-specific thresholds when evaluating outcomes following TKA. Doing so will enable more accurate determinations of operative success and improvements in patient-centered care. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.