Trends in Gender Diversity Among Total Hip Arthroplasty Surgeons.

INTRODUCTION: A pronounced gender imbalance is evident among orthopaedic surgeons. In the field of arthroplasty, there exists a dearth of comprehensive data regarding gender representation. This study aimed to analyze the gender diversity, or lack thereof, within the field of total hip arthroplasty (THA). In addition, this study used literature review to identify possible reasons for the gender disparity among THA surgeons and identify the best next steps to promote gender equity within orthopaedics. METHODS: A retrospective analysis was conducted using the Medicare Provider Utilization and Payment Data: Physician and Other Practitioners data set to quantify orthopaedic surgeons who performed primary THA procedures from 2013 to 2020. To assess trends in the number of hip surgeons by sex and the evolving female-to-male ratio, two-sided correlated Mann-Kendall tests were conducted. RESULTS: Overall, 3,853 to 4,550 surgeons billed for primary THA annually. Of this number, an average of 1.7% was female. The mean number of services billed for by male surgeons was 31.62 ± 24.78 per year and by female surgeons was 26.43 ± 19.49 per year. Trend analysis of female-to-male ratio demonstrated an increasing trend of statistical significance (P = 0.009). The average number of procedures by female surgeons annually remained stable throughout the study, whereas there was a steady increase in that for male surgeons. CONCLUSION: Results showed a notable and sustained upward trajectory from 2013 to 2020 in the number of female surgeons billing for THA along with the female-to-male ratio. However, female surgeons constitute a mere 2% of surgeons engaging in primary THA billing. Furthermore, the annual average number of THAs conducted by female surgeons exhibited constancy, whereas there was a gradual increase in the median number of annual procedures performed by their male counterparts. Future studies should aim to identify and resolve specific barriers prohibiting female medical students from pursuing and obtaining a career as an orthopaedic THA surgeon. STUDY DESCRIPTION: Retrospective analysis using the Medicare Provider Utilization and Payment Data: Physician and Other Practitioners data set.

Recognizing the Sex Disparity in Surgeons Performing Total Knee Arthroplasty.

BACKGROUND: There is an unambiguous sex disparity in the field of orthopaedic surgery, with women making up only 7.4% of practicing orthopaedic surgeons in 2022. This study seeks to evaluate the sex distribution among orthopaedic surgeons engaged in primary total knee arthroplasty (TKA) between 2013 and 2020, as well as the procedural volume attributed to each provider. METHODS: We retrospectively queried the Medicare dataset to quantify all physicians reporting orthopaedic surgery as their specialty and performing primary TKA from 2013 to 2020. Healthcare Common Procedure Coding System codes for primary TKA procedures were used to extract associated utilization and billing provider information. Trend analyses were performed with 2-sided correlated Mann-Kendall tests to evaluate trends in the number of surgeons by sex and the women-to-men surgeon ratio. RESULTS: During the study period, 6,198 to 7,189 surgeons billed for primary TKA. Of this number, an average of 2% were women. The mean number of procedures billed for by men was 39.02/y (standard deviation: 34.54), and by women was 28.76/y (standard deviation: 20.62) (P < .001). There was no significant trend in the number of men or women surgeons who billed for primary TKA during the study period. Trend analysis of the women-to-men ratio demonstrated an increasing trend of statistical significance (P = .0187). CONCLUSIONS: There was a significant upward trend in the women-to-men ratio of surgeons who billed for primary TKA. However, there remains a colossal gender gap, as women only made up 2.4% of surgeons who billed for the procedure. The current study raises awareness of the notable discrepancy in the average number of TKAs performed by women as compared to men. The orthopaedic community should aim to determine ways to increase the number of women arthroplasty surgeons along with the opportunities that women have to perform TKAs.

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.

Medicare's Post-Acute Care Reimbursement Models as of 2023: Past, Present, and Future.

The Centers for Medicare & Medicaid Services is continually working to mitigate unnecessary expenditures, particularly in post-acute care (PAC). Medicare reimburses for orthopaedic surgeon services in varied models, including fee-for-service, bundled payments, and merit-based incentive payment systems. The goal of these models is to improve the quality of care, reduce health-care costs, and encourage providers to adopt innovative and efficient health-care practices. This article delves into the implications of each payment model for the field of orthopaedic surgery, highlighting their unique features, incentives, and potential impact in the PAC setting. By considering the historical, current, and future Medicare reimbursement models, we hope to provide an understanding of the optimal payment model based on the specific needs of patients and providers in the PAC setting.

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.

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.

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

UPDATE: This article was updated on May 1, 2024 because of a previous error, which was discovered after the preliminary version of the article was posted online. The byline that had read "Ahmed K. Emara, MD 1 *, Ignacio Pasqualini, MD 1 *, Alison K. Klika, MS 1 , Melissa N. Orr, BS 1 , Pedro J. Rullán, MD 1 , Nicolas S. Piuzzi, MD 1 , and the Cleveland Clinic Arthroplasty Group†" now reads "Ahmed K. Emara, MD 1 *, Ignacio Pasqualini, MD 1 *, Yuxuan Jin, MS 1 , Alison K. Klika, MS 1 , Melissa N. Orr, BS 1 , Pedro J. Rullán, MD 1 , Nicolas S. Piuzzi, MD 1 , and the Cleveland Clinic Arthroplasty Group†". 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.

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.

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.

30-day to 10-year mortality rates following total hip arthroplasty: a meta-analysis of the last decade (2011-2021).

BACKGROUND: Mortality after total hip arthroplasty (THA) is a rare but devastating complication. This meta-analysis aimed to: (1) determine the mortality rates at 30 days, 90 days, 1 year, 5 years and 10 years after THA; (2) identify risk factors and causes of mortality after THA. METHODS: Pubmed, MEDLINE, Cochrane, EBSCO Host, and Google Scholar databases were queried for studies reporting mortality rates after primary elective, unilateral THA. Inverse-proportion models were constructed to quantify the incidence of all-cause mortality at 30 days, 90 days, 1 year, 5 years and 10 years after THA. Random-effects multiple regression was performed to investigate the potential effect modifiers of age (at time of THA), body mass index, and gender. RESULTS: A total of 53 studies (3,297,363 patients) were included. The overall mortality rate was 3.9%. The 30-day mortality was 0.49% (95% CI; 0.23-0.84). Mortality at 90 days was 0.47% (95% CI, 0.38-0.57). Mortality increased exponentially between 90 days and 5 years, with a 1-year mortality rate of 1.90% (95% CI, 1.22-2.73) and a 5-year mortality rate of 9.85% (95% CI, 5.53-15.22). At 10-year follow-up, the mortality rate was 16.43% (95% CI, 1.17-22.48). Increasing comorbidity indices, socioeconomic disadvantage, age, anaemia, and smoking were found to be risk factors for mortality. The most commonly reported causes of death were ischaemic heart disease, malignancy, and pulmonary disease. CONCLUSIONS: All-cause mortality remains low after contemporary THA. However, 1 out of 10 patients and 1 out of 6 patients were deceased after 5 years and 10 years of THA, respectively. As expected, age, but not BMI or gender, was significantly associated with mortality.

National Inpatient Datasets May No Longer Be Appropriate for Overall Total Hip and Knee Arthroplasties Projections after Removal from Inpatient-Only Lists.

It is unknown if the National Inpatient Sample (NIS) remains suitable to conduct projections for total knee arthroplasty (TKA) and total hip arthroplasty (THA), after their removal from "inpatient-only lists" in 2018 and 2020, respectively. We aimed to: (1) quantify primary THA and TKA volume from 2008 to 2018; (2) project estimates of future volume of THA and TKA until 2050; and (3) compare projections based on NIS data from 2008 to 2018 and 2008 to 2017, respectively. We identified all primary THA and TKA performed from 2008 to 2018 from the NIS. The projected volumes of THA and TKA were modeled using negative binomial regression models while incorporating log-transformed population data from the Centers for Disease Control and Prevention. Annual volume increased by 26% for THA and 11% for TKA (2008/2018: THA: 360,891/465,559; TKA:592,352/657,294). Based on 2008 to 2018 data, THA volume is projected to grow 120%, to 1,119,942 THAs by 2050. While, based on 2008 to 2017 data, THA volume is projected to grow 136%, to 1,219,852 THAs by 2050. Based on 2008 to 2018 data, TKA volume is projected to grow 4%, to 794,852 TKAs by 2050. While, based on 2008 to 2017 data, TKA volume is projected to grow 28%, to 1,037,474 TKAs by 2050. Projections based on 2008 to 2017 data estimated up to 240,000 (23%) more annual TKAs by 2050, compared with projections based on 2008 to 2018 data. The largest discrepancy among THA projections was an 8.2% difference (99,000 THAs) for 2050. After 2018 for TKA, and potentially 2020 for THA, projections based on the NIS will have to be interpreted with caution and may only be appropriate to estimate future inpatient volume. Level of evidence is prognostic level II.

Cannabis Use Following Total Joint Arthroplasty is Associated With Increased Risks? A Meta-Analysis.

BACKGROUND: With the increased legalization of cannabis, a new unknown emerges for orthopaedic surgeons and their patients. This systematic review aimed to (1) evaluate complications of cannabis use; (2) determine the effects of cannabis on pain and opioid consumption; and (3) evaluate healthcare utilizations associated with cannabis use among patients undergoing total joint arthroplasty (TJA). METHODS: A systematic review was performed. A search of the literature was performed in 5 databases. We included studies between January 2012 and July 2022 reporting cannabis use and complications, pain management, opioid consumption, length of stay, costs, or functional outcomes following TJA. A meta-analysis of odds ratios (ORs) and continuous variables was performed. A total of 19 articles were included in our final analysis. RESULTS: Cannabis use was associated with higher odds for deep vein thrombosis (DVT) (OR: 1.46, 95% Confidence Interval [CI]: 1.13 to 1.89) and revisions (OR: 1.47 [95% CI: 1.41 to 1.53]) in total knee arthroplasty (TKA). Cannabis use was associated with similar odds for DVT in total hip arthroplasty (THA) (OR: 1.30 [95% CI: 0.79 to 2.13]), pulmonary embolus in both TKA (OR: 1.29 [95% CI: 0.95 to 1.77]), THA (OR: 0.55 [95% CI: 0.09 to 3.28]), and cardiovascular complications in TKA (OR: 1.97 [95% Cl: 0.93 to 4.14]). Cannabis use did not alter pain scores, opioid consumption, or cost of care in THA (estimate: $2,550.51 [95% CI: $356.58 to $5,457.62]) but was associated with higher costs in TKA (estimate: $3,552.46 [95% CI: $1,729.71 to $5,375.22]). There was no difference in lengths of stay or functional outcomes; however, there may be a potentially increased risk for prosthetic complications, pneumonia, and cerebrovascular accidents among cannabis users. CONCLUSION: Cannabis use may be associated with an increased risk of DVTs, revisions, pneumonia, cerebrovascular accidents, and cardiac complications after TJA. Higher-level studies are needed to ascertain the impact of cannabis use for patients undergoing TJA.

Are All Patients Going Home after Total Knee Arthroplasty? A Temporal Analysis of Discharge Trends and Predictors of Nonhome Discharge (2011-2020).

Value-based orthopaedic surgery and reimbursement changes for total knee arthroplasty (TKA) are potential factors shaping arthroplasty practice nationwide. This study aimed to evaluate (1) trends in discharge disposition (home vs nonhome discharge), (2) episode-of-care outcomes for home and nonhome discharge cohorts, and (3) predictors of nonhome discharge among patients undergoing TKA from 2011 to 2020. The National Surgical Quality Improvement Program database was reviewed for all primary TKAs from 2011 to 2020. A total of 462,858 patients were identified and grouped into home discharge (n = 378,771) and nonhome discharge (n = 84,087) cohorts. The primary outcome was the annual rate of home/nonhome discharges. Secondary outcomes included trends in health care utilization parameters, readmissions, and complications. Multivariable logistic regression analyses were performed to evaluate factors associated with nonhome discharge. Overall, 82% were discharged home, and 18% were discharged to a nonhome facility. Home discharge rates increased from 65.5% in 2011 to 94% in 2020. Nonhome discharge rates decreased from 34.5% in 2011 to 6% in 2020. Thirty-day readmissions decreased from 3.2 to 2.4% for the home discharge cohort but increased from 5.6 to 6.1% for the nonhome discharge cohort. Female sex, Asian or Black race, Hispanic ethnicity, American Society of Anesthesiology (ASA) class > II, Charlson comorbidity index scores > 0, smoking, dependent functional status, and age > 60 years were associated with higher odds of nonhome discharge. Over the last decade, there has been a major shift to home discharge after TKA. Future work is needed to further assess if perioperative interventions may have a positive effect in decreasing adverse outcomes in nonhome discharge patients.

Establishing patient-centered metrics for the knee injury and osteoarthritis outcome score following medial unicompartmental knee arthropalsty.

BACKGROUND: This study aimed to determine the minimal clinically important difference (MCID) and the patient acceptable symptoms state (PASS) threshold for the knee injury and osteoarthritis outcome score (KOOS) pain subscore, KOOS physical short form (PS), and KOOS joint replacement (JR) following medial unicompartmental knee arthroplasty (mUKA). METHODS: Prospectively collected data from 743 patients undergoing mUKA from a single academic institution from April 2015 through March 2020 were analyzed. Patient-reported outcome measures (PROMs) were collected both pre-operatively and 1-year post-operatively. Distribution-based and anchored-based approaches were used to estimate MCIDs and PASS, respectively. The optimal cut-off point and the percentage of patients who achieved PASS were also calculated. RESULTS: MCID for KOOS-pain, KOOS-PS, and KOOS-JR following mUKA were calculated to be 7.6, 7.3, and 6.2, respectively. The PASS threshold for KOOS pain, PS, and JR were 77.8, 70.3, and 70.7, with 68%, 66%, and 64% of patients achieving satisfactory outcomes, respectively. Cut-off values for delta KOOS pain, PS, and JR were found to be 25.7, 14.3, and 20.7 with 73%, 69%, and 68% of patients achieving satisfactory outcomes, respectively. CONCLUSION: The current study identified useful values for the MCID and PASS thresholds at 1 year following medial UKA of KOOS pain, KOOS PS, and KOOS JR scores. These values may be used as targets for surgeons when evaluating PROMS using KOOS to determine whether patients have achieved successful outcomes after their surgical intervention. Potential uses include the integration of these values into predictive models to enhance shared decision-making and guide more informed decisions to optimize patient outcomes. LEVEL OF EVIDENCE: III.

Forty-Six Years of Technological Innovation in Musculoskeletal Medicine: An Analysis of a Patent Database (1973 to 2018).

BACKGROUND: Technological innovation in orthopaedics is key to advancing patient care. As emerging technologies near maturity, clinicians must be able to objectively assess where and when these technologies can be implemented. Patent databases are an underappreciated resource for quantifying innovation, especially within orthopaedic surgery. This study used a patent database to assess patent activity and relative growth of technologies in musculoskeletal medicine and orthopaedics over a period of 46 years. METHODS: A total of 121,471 patent records were indexed from Lens.org , a patent database. These patents were grouped into subspecialty clusters and technology clusters using patent codes. Five-year (2014 to 2018), 10-year (2009 to 2018), and 30-year (1989 to 2018) compound annual growth rates were calculated and compared for each cluster. RESULTS: Annual patent activity increased from one patent in 1973 to 4,866 patents in 2018. Of the eight subspecialty clusters, the largest number of patents were related to 'Inflammation' (n = 63,128; 40.57%). The 'Elbow', 'Shoulder', and 'Knee' clusters experienced increased annual patent activity since 2000. Of the 12 technological clusters, the largest number of patents were related to 'Drugs' (n = 55,324; 39.75%). The 'Custom/patient-specific instrumentation, 'Computer Modeling', 'Robotics', and 'Navigation' clusters saw growth in the average annual patent activity since 2000. DISCUSSION: Innovation, as measured by patent activity in musculoskeletal medicine and orthopaedics, has seen notable growth since 1973. The 'Robotics' cluster seems poised to experience exponential growth in industry investment and technological developments over the next 5 to 10 years. The 'Diagnostics', 'Computer Modeling', 'Navigation', and 'Design and Manufacturing' clusters demonstrate potential for exponential growth in industry investment and technological developments within the next 10 to 20 years.

Intraincisional Pin Placement is Safe for Robotic-Assisted Total Knee Arthroplasty.

BACKGROUND: While robotic-arm assisted total knee arthroplasty (RA-TKA) has seen a major increase in its utilization, it requires bone array pins to be fixed into the femur and tibia, which intrinsically carries a risk. As it is currently off-label with some robotic platforms to place pins intraincisional, we aimed to evaluate the safety of intraincisional pin placement during RA-TKAs. METHODS: A prospective cohort of 2,343 patients who underwent RA-TKA at a North American Healthcare System between January 2018 and March 2022 was included. Primary outcomes included periprosthetic fracture or infection (eg, superficial or deep). Secondary outcomes included 1-year reoperation rate due to any cause. Cases were retrospectively reviewed to determine whether complications could be attributed to metaphyseal intraincisional pin placement (4.0 mm pins; two tibial and two femoral). The 90-day follow-up was 100% and the 1-year follow-up rate was 70.6% (n = 1,655). RESULTS: The pin-site related periprosthetic fracture incidence at 90 days was 0.09% (2 out of 2,343). The 90-day infection incidence was 1.4% (superficial: 22; deep: 13). The 1-year reoperation rate was 1.8% (29 out of 1,655). The most common causes of reoperation at 1-year were deep infection (n = 14; 0.83%), superficial infection (n = 3; 0.18%), periprosthetic fracture, mechanical symptoms, instability, and hematoma (n = 2; 0.12% for each). CONCLUSIONS: One in 1,172 patients may experience a pin-related periprosthetic fracture after RA-TKA with intraincisional bone array pin placement. There was a low 90-day infection incidence and reoperations within 1-year after RA-TKA were rare.

Effect of operative time in outcomes following surgical fixation of hip fractures: a multivariable regression analysis of 35,710 patients.

BACKGROUND: Prolonged operative time is a risk factor for increased morbidity and mortality after open reduction and internal fixation (ORIF) of hip fractures. However, the quantitative nature of such association, including graduated risk levels, has yet to be described. This study outlines the graduated associations between operative time and (1) healthcare utilisation, and (2) 30-day complications after ORIF of hip fractures. METHODS: The National Surgical Quality Improvement Program (NSQIP) database was queried (January 2016-December 2019) for all patients who underwent ORIF of hip fractures (n = 35,710). Demographics, operative time, fracture type, and comorbidities were recorded. Outcomes included healthcare utilisation (e.g., prolonged length of stay [LOS>2 days], discharge disposition, 30-day readmission, and reoperation), inability to weight-bear (ITWB) on postoperative day-1 (POD-1), and any 30-day complication. Adjusted multivariate regression models evaluated associations between operative time and measured outcomes. RESULTS: Operative time <40 minutes was associated with lower odds of prolonged LOS (odds ratio [OR] 0.77), non-home discharge (OR 0.85), 30-day readmission (OR 0.85), and reoperation (OR 0.72). Operative time ⩾80 minutes was associated with higher odds of ITWB on POD-1 (OR 1.17). Operative time ⩾200 minutes was associated with higher odds of deep infection (OR 7.5) and wound complications (OR 3.2). The odds of blood transfusions were higher in cases ⩾60 minutes (OR1.3) and 5-fold in cases ⩾200 minutes (OR 5.4). The odds of venous thromboembolic complications were highest in the ⩾200-minute operative time category (OR 2.5). Operative time was not associated with mechanical ventilation, pneumonia, delirium, sepsis, urinary tract infection, or 30-day mortality. DISCUSSION: Increasing operative time is associated with a progressive increase in the odds of adverse outcomes following hip fracture ORIF. While a direct cause-effect relationship cannot be established, an operative time of <60 minutes could be protective. Perioperative interventions that shorten operative time without compromising fracture reduction or fixation should be considered.

A Longitudinal Analysis of Weight Changes before and after Total Knee Arthroplasty: Weight Trends, Patterns, and Predictors.

Longitudinal data on patient trends in body mass index (BMI) and the proportion that gains or loses significant weight before and after total knee arthroplasty (TKA) are scarce. This study aimed to observe patients longitudinally for a 2-year period and determine (1) clinically significant BMI changes during the 1 year before and 1 year after TKA and (2) identify factors associated with clinically significant weight changes.A prospective cohort of 5,388 patients who underwent primary TKA at a tertiary health care institution between January 2016 and December 2019 was analyzed. The outcome of interests was clinically significant weight changes, defined as a ≥5% change in BMI, during the 1-year preoperative and postoperative periods, respectively. Patient-specific variables and demographics were assessed as potential predictors of weight change using multinomial logistic regression.Overall, 47% had a stable weight throughout the study period (preoperative: 17% gained, 15% lost weight; postoperative: 19% gained, 16% lost weight). Patients who were older (odds ratio [OR] = 0.95), men (OR = 0.47), overweight (OR = 0.36), and Obese Class III (OR = 0.06) were less likely to gain weight preoperatively. Preoperative weight loss was associated with postoperative weight gain 1 year after TKA (OR = 3.03). Preoperative weight gain was associated with postoperative weight loss 1 year after TKA (OR = 3.16).Most patients maintained a stable weight before and after TKA. Weight changes during the 1 year before TKA were strongly associated with reciprocal rebounds in BMI postoperatively, emphasizing the importance of ongoing weight management during TKA and the recognition of patients at higher risk for weight gain.Level of evidence II (prospective cohort study).

Challenging the Status Quo: Debunking the Necessity of 5-Year to 10-Year Patient-Reported Outcome Measures in Total Hip and Knee Arthroplasties.

BACKGROUND: In the current shift toward value-based healthcare, patient-reported outcome measures (PROMs) have become essential to assess the effectiveness of medical interventions. However, elucidation of the optimal timeframe for PROMs evaluation remains crucial. This study aimed to (1) determine the proportion of patients who experienced clinically meaningful improvements in PROMs scores at each follow-up visit after total hip arthroplasty (THA) and total knee arthroplasty (TKA) and (2) calculate and apply the clinical relevance ratio (CRR) for these long-term PROM collections postoperatively. METHODS: A total of 12 independent studies reporting THA (n = 8 studies) and TKA (n = 4 studies) postoperative PROM data with up to 10 years of follow-up in Europe or the United States were aggregated. A distribution-based minimal clinically important difference threshold and CRR were used to determine which patients had clinically meaningful improvements in PROMs at 1, 5, and 10 years. RESULTS: The proportion of patients who had clinically meaningful improvements in PROM scores stabilized after 1 year following both THA and TKA. Overall, the CRR decreased over time for all PROMs, with the CRR beginning to decrease at 1-year follow-up, bringing into question the robustness and clinical relevance of long-term PROMs data. CONCLUSIONS: The present study challenges the utility of requiring PROMs with a minimum follow-up of 2 years for THA and TKA. Research efforts should be focused on registries evaluating implant survivorship at longer-term follow-up, while PROMs should be better assessed up to 1-year follow-up. Reconsidering the long-term PROMs assessment would lead to more efficient and cost-effective research in orthopedic outcomes, without compromising data quality.

What Drives the Material Costs of Total Knee Arthroplasty in the Operating Room?

INTRODUCTION: Approximately one-third of US healthcare spending is related to surgical care. Optimizing operating room (OR) spending is crucial, specifically for high-volume procedures like total knee arthroplasty (TKA). Therefore, the primary objective was to identify leading material drivers of cost for TKA procedures within the OR. MATERIALS AND METHODS: Patients who underwent a primary, elective TKA from 2018 to 2019 were included (n=8,672). Intraoperative cost details for each TKA patient were captured from the Vizient Clinical Database Resource Manager (CDB/RM) data. Each cost type was categorized into (1) implant, (2) disposables, (3) wound care, and (4) miscellaneous. RESULTS: 7,124 patients undergoing primary TKA were included. Implant-related costs accounted for 87.3% of cost, disposable materials covered 10.7%, and wound care products took 2%. The leading subcategories of implant costs were primary prosthetics (85.1%), revision prosthetics (9.9%), cement (2.8%), and implant instruments (1.7%). Within disposables, surgical products accounted for 81.3% of the cost, patient care products for 8.9%, medical apparel for 7.9%, and electrolytes for 1.8%. For an average individual TKA procedure, 86.4% (±4.4) of total cost went towards the implant, 10.7% (±3.4) towards disposable materials, and 1.6% (±1.4) to wound care products. Within the implant category, 92.5% (± 12.8) of costs were associated with primary implants, 13.3% (± 6.9) with instruments, and 2.5% (± 2.8) with cement. CONCLUSIONS: The primary operative material expense category was costs associated with the TKA prosthesis and its fixation followed by disposable materials. A large amount of variation exists in the percent of the total cost for a given TKA procedure that can be attributed to each category.