What Are the Mortality, Infection, and Nonunion Rates After Periprosthetic Femoral Fractures in the United States?

BACKGROUND: Periprosthetic femoral fractures are a serious complication that put a high burden on patients. However, comprehensive analyses of their incidence, mortality, and complication rates based on large-registry data are scarce. QUESTIONS/PURPOSES: In this large-database study, we asked: (1) What is the incidence of periprosthetic femoral fractures in patients 65 years and older in the United States? (2) What are the rates of mortality, infection, and nonunion, and what factors are associated with these outcomes? METHODS: In this retrospective, comparative, large-database study, periprosthetic femoral fractures occurring between January 1, 2010, and December 31, 2019, were identified from Medicare physician service records encompassing services rendered in medical offices, clinics, hospitals, emergency departments, skilled nursing facilities, and other healthcare institutions from approximately 2.5 million enrollees. These were grouped into proximal, distal, and shaft fractures after TKA and THA. We calculated the incidence of periprosthetic femur fractures by year. Incidence rate ratios (IRR) were calculated by dividing the incidence in 2019 by the incidence in 2010. The Kaplan-Meier method with Fine and Gray subdistribution adaptation was used to calculate the cumulative incidence rates of mortality, infection, and nonunion. Semiparametric Cox regression was applied with 23 measures as covariates to determine factors associated with these outcomes. RESULTS: From 2010 to 2019, the incidence of periprosthetic femoral fractures increased steeply (TKA for distal fractures: IRR 3.3 [95% CI 1 to 9]; p = 0.02; THA for proximal fractures: IRR 2.3 [95% CI 1 to 4]; p = 0.01). One-year mortality rates were 23% (95% CI 18% to 28%) for distal fractures treated with THA, 21% (95% CI 19% to 24%) for proximal fractures treated with THA, 22% (95% CI 19% to 26%) for shaft fractures treated with THA, 21% (95% CI 18% to 25%) for distal fractures treated with TKA , 22% (95% CI 17% to 28%) for proximal fractures treated with TKA, and 24% (95% CI 19% to 29%) for shaft fractures treated with TKA. The 5-year mortality rate was 63% (95% CI 54% to 70%) for distal fractures treated with THA, 57% (95% CI 54% to 62%) for proximal fractures treated with THA, 58% (95% CI 52% to 63%) for shaft fractures treated with THA, 57% (95% CI 52% to 62%) for distal fractures treated with TKA , 57% (95% CI 49% to 65%) for proximal fractures treated with TKA, and 57% (95% CI 49% to 64%) for shaft fractures treated with TKA. Age older than 75 years, male sex, chronic obstructive pulmonary disease (HR 1.48 [95% CI 1.32 to 1.67] after THA and HR 1.45 [95% CI 1.20 to 1.74] after TKA), cerebrovascular disease after THA, chronic kidney disease (HR 1.28 [95% CI 1.12 to 1.46] after THA and HR 1.50 [95% CI 1.24 to 1.82] after TKA), diabetes mellitus, morbid obesity, osteoporosis, and rheumatoid arthritis were clinical risk factors for an increased risk of mortality. Within the first 2 years, fracture-related infections occurred in 5% (95% CI 4% to 7%) of patients who had distal fractures treated with THA, 5% [95% CI 5% to 6%]) of patients who had proximal fractures treated with THA, 6% (95% CI 5% to 7%) of patients who had shaft fractures treated with THA, 6% (95% CI 5% to 7%) of patients who had distal fractures treated with TKA , 7% (95% CI 5% to 9%) of patients who had proximal fractures treated with TKA, and 6% (95% CI 4% to 8%) of patients who had shaft fractures treated with TKA. Nonunion or malunion occurred in 3% (95% CI 2% to 4%) of patients with distal fractures treated with THA, 1% (95% CI 1% to 2%) of patients who had proximal fractures treated with THA, 2% (95% CI 1% to 3%) of patients who had shaft fractures treated with THA, 4% (95% CI 3% to 5%) of those who had distal fractures treated with TKA, , 2% (95% CI 1% to 4%) of those who had proximal fractures treated with TKA, and 3% (95% CI 2% to 4%) of those who had shaft fractures treated with TKA. CONCLUSION: An increasing number of periprosthetic fractures were observed during the investigated period. At 1 and 5 years after periprosthetic femur fracture, there was a substantial death rate in patients with Medicare. Conditions including cerebrovascular illness, chronic kidney disease, diabetes mellitus, morbid obesity, osteoporosis, and rheumatoid arthritis are among the risk factors for increased mortality. After the surgical care of periprosthetic femur fractures, the rates of fracture-related infection and nonunion were high, resulting in a serious risk to affected patients. Patient well-being can be enhanced by an interdisciplinary team in geriatric traumatology and should be improved to lower the risk of postoperative death. Additionally, it is important to ensure that surgical measures to prevent fracture-related infections are followed diligently. Furthermore, there is a need to continue improving implants and surgical techniques to avoid often-fatal complications such as fracture-associated infections and nonunion, which should be addressed in further studies. LEVEL OF EVIDENCE: Level III, therapeutic study.

Strikingly High Rates of Periprosthetic Joint Infection Following Revision Surgery for Periprosthetic Fractures Regardless of Surgery Timing.

BACKGROUND: Periprosthetic fractures following total hip arthroplasty (THA) often occur in the early postoperative period. Recent data has indicated that early revisions are associated with higher complication rates, particularly periprosthetic joint infection (PJI). The purpose of this study was to assess the effect of timing of periprosthetic fracture surgery on complication rates. We hypothesized that complication rates would be significantly higher in revision surgeries performed within 3 months of the index THA. METHODS: The Medicare Part A claims database was queried from 2010 to 2017 to identify patients who underwent surgery for a periprosthetic fracture following primary THA. Patients were divided based on time between index and revision surgeries: <1, 1 to 2, 2 to 3, 3 to 6, 6 to 9, 9 to 12, and >12 months. Complication rates were compared between groups using multivariate analyses to adjust for demographics, comorbidities, and types of revision surgery. RESULTS: Of 492,340 THAs identified, 4,368 (0.9%) had a subsequent periprosthetic fracture requiring surgery: 1,725 (39.4%) at <1 month, 693 (15.9%) at 1 to 2 months, 202 (4.6%) at 2 to 3 months, 250 (5.7%) at 3 to 6 months, 134 (3.1%) at 6 to 9 months, 85 (19.4%) at 9 to12 months, and 1,279 (29.3%) at >12 months. The risk of PJI was 11.0% in the <1 month group, 11.1% at 1 to 2 months, 7.9% at 2 to 3 months, 6.8% at 3 to 6 months, 8.2% at 6 to 9 months, 9.4% at 9 to 12 months, and 8.5% at >12 months (P = .12). Adjusting for confounding factors, risk of PJI following periprosthetic fracture surgery was similar regardless of timing (P > .05). Rates of subsequent dislocation and aseptic loosening were also similar regardless of timing. CONCLUSIONS: The risk of PJI following repeat surgery for a periprosthetic fracture was strikingly high regardless of timing (6.8 to 11.1%), underscoring the high-risk of complications.

Complications and associated risk factors after surgical management of proximal femoral fractures.

Aims: This work aimed at answering the following research questions: 1) What is the rate of mechanical complications, nonunion and infection for head/neck femoral fractures, intertrochanteric fractures, and subtrochanteric fractures in the elderly USA population? and 2) Which factors influence adverse outcomes? Methods: Proximal femoral fractures occurred between 1 January 2009 and 31 December 2019 were identified from the Medicare Physician Service Records Data Base. The Kaplan-Meier method with Fine and Gray sub-distribution adaptation was used to determine rates for nonunion, infection, and mechanical complications. Semiparametric Cox regression model was applied incorporating 23 measures as covariates to identify risk factors. Results: Union failure occured in 0.89% (95% confidence interval (CI) 0.83 to 0.95) after head/neck fracturs, in 0.92% (95% CI 0.84 to 1.01) after intertrochanteric fracture and in 1.99% (95% CI 1.69 to 2.33) after subtrochanteric fractures within 24 months. A fracture-related infection was more likely to occur after subtrochanteric fractures than after head/neck fractures (1.64% vs 1.59%, hazard ratio (HR) 1.01 (95% CI 0.87 to 1.17); p < 0.001) as well as after intertrochanteric fractures (1.64% vs 1.13%, HR 1.31 (95% CI 1.12 to 1.52); p < 0.001). Anticoagulant use, cerebrovascular disease, a concomitant fracture, diabetes mellitus, hypertension, obesity, open fracture, and rheumatoid disease was identified as risk factors. Mechanical complications after 24 months were most common after head/neck fractures with 3.52% (95% CI 3.41 to 3.64; currently at risk: 48,282). Conclusion: The determination of complication rates for each fracture type can be useful for informed patient-clinician communication. Risk factors for complications could be identified for distinct proximal femur fractures in elderly patients, which are accessible for therapeutical treatment in the management.

Epidemiology and treatment of proximal femoral fractures in the elderly U.S. population.

Proximal femoral fractures are a serious complication, especially for elderly patients. Detailed epidemiological analyzes provide a valuable resource for stakeholders in the health care system in order to foresee future development possibly influenceable by adaption of therapeutic procedures and prevention strategies. This work aimed at answering the following research questions: (1) What are the incidence rates of proximal femoral fractures in the elderly U.S. population? (2) What is the preferred treatment procedure for these fractures? Proximal femoral fractures occurred between January 1, 2009 and December 31, 2019 in patients ≥ 65 years were identified from the Medicare Physician Service Records Data Base. The 5% sample of Medicare beneficiaries, equivalent to the records from approximately 2.5 million enrollees formed the basis of this study. Fractures were grouped into head/neck, intertrochanteric, and subtrochanteric fractures. The overall incidence rate, age and sex specific incidence rates as well as incidence rate ratios were calculated. Common Procedural Terminology (CPT) codes were used to identify procedures and operations. In 2019, a total number of 7982 femoral head/neck fractures was recorded. In comparison to 9588 cases in 2009, the incidence substantially decreased by 26.6% from 666.7/100,000 inhabitants to 489.3/100,000 inhabitants (z = - 5.197, p < 0.001). Also, in intertrochanteric fractures, a significant decline in the incidence by 17.3% was evident over the years from 367.7/100,000 inhabitants in 2009 to 304.0 cases per 100,000 inhabitants in 2019 (z = - 2.454, p = 0.014). A similar picture was observable for subtrochanteric fractures, which decreased by 29.6% (51.0 cases per 100,000 to 35.9 cases per 100,000) over the time period (z = - 1.612, p = 0.107). Head/neck fractures were mainly treated with an arthroplasty (n = 36,301, 40.0%). The majority of intertrochanteric fractures and subtrochanteric fractures received treatment with an intramedullary device (n = 34,630, 65.5% and n = 5870, 77.1%, respectively). The analysis indicated that the incidence of all types of proximal femoral neck fractures decreased for the population of elderly patients in the U.S. within the last decade. Treatment of head and neck fractures was mainly conducted through arthroplasty, while intertrochanteric and subtrochanteric fractures predominantly received an intramedullary nailing.

Proximal Humerus Fractures in the Elderly U.S. Population: A Cross-Sectional Study of Treatment Trends and Comparison of Complication Rates after Joint Replacement, Open Reduction and Internal Fixation, and Non-Surgical Management.

Proximal humerus fracture (PHF) treatment remains challenging. Multiple therapy options exist, and the optimal choice of management has been increasingly discussed in the literature. The aim of this study was to (1) analyze trends in the propensity of proximal humerus fracture treatments and (2) compare complication rates after joint replacement, surgical repair, and non-surgical treatment in terms of mechanical complications, union failure, and infection rates. In this cross-sectional study, patients aged 65 years or older with proximal humerus fractures occurring between 1 January 2009 and 31 December 2019 were identified from Medicare physician service claims records. The Kaplan-Meier method with the Fine and Gray adjustment was used to calculate the cumulative incidence rates for malunion/nonunion, infection, and mechanical complications for the following treatment categories: shoulder arthroplasty, open reduction and internal fixation (ORIF), and non-surgical treatment, respectively. Semiparametric Cox regression was performed incorporating 23 demographic, clinical, and socioeconomic covariates to determine risk factors. Between 2009 through 2019, conservative procedures decreased by 0.9%. ORIF procedures decreased from 9.51% (95% CI: 8.7-10.4) to 6.95% (95% CI: 6.2-7.7), whereas shoulder arthroplasties rose from 1.99% (95% CI: 1.6-2.4), to 5.45% (95% CI: 4.8-6.2). PHFs managed through ORIF were associated with higher union failure rates compared to conservatively treated fractures (HR = 1.31, 95% CI: 1.15-1.5, p < 0.001). The risk of developing an infection was increased after joint replacement compared to ORIF (2.66% vs. 1.09%, HR = 2.09, 95% CI: 1.46-2.98, p < 0.001). Mechanical complications were more common after joint replacement (6.37% vs. 4.85%, HR = 1.66, 95% CI: 1.32-2.09, p < 0.001). Complication rates differed significantly across treatment modalities. This should be considered when choosing a management procedure. Vulnerable elderly patient cohorts could be identified, and the optimization of modifiable risk factors might lead to a decrease of complication rates in both surgically and non-surgically treated patients.

Femoral shaft fractures in eldery patients - An epidemiological risk analysis of incidence, mortality and complications.

OBJECTIVES: This work aimed at answering the following research questions: (1) What is the incidence of femoral shaft fractures in the geriatric population in the U.S.? (2) What is the rate of mortality, mechanical complications, nonunion and infection, and what are the associated risk factors? STUDY DESIGN AND SETTING: In this cross-sectional study, femoral shaft fractures occurred between January 1, 2009, and December 31, 2019, were identified from Medicare records. Rates of mortality, nonunion, infection, and mechanical complications were calculated with the Kaplan-Meier method with Fine and Gray sub-distribution adaptation. Semiparametric Cox regression was applied with twenty-three covariates to determine risk factors. RESULTS: Between 2009 through 2019 the incidence of femoral shaft fractures decreased by 12.07% to 40.8/100,000 inhabitants (p = 0.549). The 5-year mortality risk was 58.5%. Male sex, age over 75 years, chronic obstructive pulmonary disease, cerebrovascular disease, chronic kidney disease, congestive heart failure, diabetes mellitus, osteoporosis, tobacco dependence, and lower median household income were significant risk factors. The infection rate was 2.22% [95%CI: 1.90-2.58] and the union failure rate 2.52% [95%CI: 2.17-2.92] after 24 months. CONCLUSION: An early assessment of individual patient risk factors may be beneficial in the care and treatment of patients with these fractures.

Revision Rates and Associated Risk Factors after Shoulder Arthroplasty.

This study aims at answering the following questions (1) How high is the revision rate after osteoarthritis-, and rotator cuff-related compared to proximal humerus fracture (PHF)-related shoulder arthroplasty? (2) What are the associated risk factors for a revision after shoulder arthroplasty? Shoulder arthroplasty procedures occurring between 1 January 2009 and 31 December 2019 were identified from the Medicare database. First, revision rates for PHF patients and age- and sex-matched non-fracture patients, grouped into osteoarthritis-related and rotator cuff-related arthroplasty, were compared. Second, revision rates between total shoulder arthroplasty and hemiarthroplasty after PHF were compared. Semiparametric Cox regression was applied, incorporating 23 demographic, clinical, and socioeconomic covariates, to investigate risk factors for revision surgery. Between the considered time period from 2009 through 2019, a total number of 47,979 PHFs was identified. A shoulder arthroplasty procedure was performed in n = 2639 (5.5%, 95%CI: 4.8-6.1) of the cases. The five-year survivorship of the implant was 96.3 (95%CI: 93.8-97.9) after hemiarthroplasty and 96.1% (05%CI: 94.2-97.3) after total shoulder arthroplasty. To compare the revision rates, n = 14,775 patients with osteoarthritis and n = 4268 patients with rotator cuff arthropathy, who received a shoulder arthroplasty, served as a non-fracture control group. Patients receiving a rotator cuff-related arthroplasty were more likely to require a revision compared to patients treated for osteoarthritis (HR: 1.27, 95%CI: 1.04-1.44, p = 0.018). Identified significant risk factors for revision surgery after shoulder arthroplasty included age ≤ 75 years, male sex, and osteoporosis. High implant survival was found for hemiarthroplasty and total shoulder arthroplasty for the treatment of PHF in elderly patients. The risk of revision surgery was elevated in patients receiving a rotator cuff-related arthroplasty as well as in patients with osteoporosis, male patients and patients older than 75 years.

Prevalence of spine degeneration diagnosis by type, age, gender, and obesity using Medicare data.

Identifying the prevalence of degenerative spinal pathologies and relevant demographic risk factors is important for understanding spine injury risk, prevention, treatment, and outcome, and for distinguishing acute injuries from degenerative pathologies. Prevalence data in the literature are often based on small-scale studies focused on a single type of pathology. This study evaluates the prevalence of diagnosis of selected degenerative spinal pathology diagnoses using Medicare insurance claim data in the context of published smaller-scale studies. In addition, the data are used to evaluate whether the prevalence is affected by age, sex, diagnosed obesity, and the use of medical imaging. The Medicare Claims 5% Limited Data Set was queried to identify diagnoses of degenerative spinal pathologies. Unique patient diagnoses per year were further evaluated as a function of age, gender, and obesity diagnosis. Participants were also stratified by coding for radiological imaging accompanying each diagnosis. The overall prevalence of diagnosed spinal degenerative disease was 27.3% and increased with age. The prevalence of diagnosed disc disease was 2.7 times greater in those with radiology. The results demonstrate that degenerative findings in the spine are common, and, since asymptomatic individuals may not receive a diagnosis of degenerative conditions, this analysis likely underestimates the general prevalence of these conditions.

Rear-seat occupant demographics in rear impacts: Analysis of NASS-CDS.

PURPOSE: This study analyzes field accidents to identify rear-occupant exposure and injury by crash types. Occupant demographics and injury were assessed by body region and crash severity to understand rear-occupant injury mechanisms in rear crashes. METHODS: The exposure and serious-to-fatal injury was determined by crash type for non-ejected second- and third- row occupants in 1994+ MY vehicles using 1994-2015 NASS-CDS. Selected occupant demographics and serious injury distributions were assessed over a range of delta V for rear crashes. RESULTS: Rear crashes accounted for 8.7% of exposed and 5.4% of serious-to-fatally injured rear-seat occupants. On average, rear-seat occupants were 14.3 ± 1.5 years old (median 10.3, 90th CI 0.08-29.6), weighed 44.7 ± 2.6 kg (median 44.4, 90th CI 7.9-81.7) and were 130.3 ± 4.1 cm tall (median 141.4, 90th CI 67.3-178.4). With serious injury, the average rear occupant was 18.1 ± 5.8 years old (median 13.1, 90th CI 0.0-47.2), weighed 42.6 ± 10.7 kg (median 31.4, 90th CI 7.0-82.4) and was 120.6 ± 15.4 cm tall (median 145.4, 90th CI 48.8-174.1). More than 72% of rear-seat occupants were in delta V less than 24 km/h. Less than 2% were in delta V 48 km/h or greater. The overall rate of serious-to-fatally injured (MAIS 3 + F) was 0.73% ± 0.37%. For serious-to-fatally injured rear-seat occupants, the average delta V was 37.4 ± 3.1 km/h (median 29.8, 90th CI 28.6-62.1). None were involved in delta Vs less than 24 km/h, about 78% were in a delta V between 24-48 km/h and 22% were in a delta V of 48 km/h or greater. Head and chest were most commonly injured, irrespective of crash severity. CONCLUSIONS: The height and weight of a 10-year old and 5th Hybrid III ATD are representative of the average rear-seat occupant involved in rear crashes based on NASS-CDS. Crash tests with a delta V of between 30 and 37 km/h represent the typical collision causing serious-to-fatal injury.

Revision Surgery for Instability After Total Hip Arthroplasty: Does Timing Matter?

BACKGROUND: Instability is a common reason for revision surgery after total hip arthroplasty (THA). Recent studies suggest that revisions performed in the early postoperative period are associated with higher complication rates. The purpose of this study is to assess the effect of timing of revision for instability on subsequent complication rates. METHODS: The Medicare Part A claims database was queried from 2010 to 2017 to identify revision THAs for instability. Patients were divided based on time between index and revision surgeries: <1, 1-2, 2-3, 3-6, 6-9, 9-12, and >12 months. Complication rates were compared between groups using multivariate analyses to adjust for demographics and comorbidities. RESULTS: Of 445,499 THAs identified, 9298 (2.1%) underwent revision for instability. Revision THA within 3 months had the highest rate of periprosthetic joint infection (PJI): 14.7% at <1 month, 12.7% at 1-2 months, and 10.6% at 2-3 months vs 6.9% at >12 months (P < .001). Adjusting for confounding factors, PJI risk remained elevated at earlier periods: <1 month (adjusted odds ratio [aOR]: 1.84, 95% confidence interval [CI]: 1.51-2.23, P < .001), 1-2 months (aOR: 1.45, 95% CI: 1.16-1.82, P = .001), 2-3 months (aOR: 1.35, 95% CI: 1.02-1.78, P = .036). However, revisions performed within 9 months of index surgery had lower rates of subsequent instability than revisions performed >12 months (aOR: 0.67-0.85, P < .050), which may be due to lower rates of acetabular revision and higher rates of head-liner exchange in this later group. CONCLUSION: When dislocation occurs in the early postoperative period, delaying revision surgery beyond 3 months from the index procedure may be warranted to reduce risk of PJI.

Corrosion Concerns? Trends in Metal-on-Polyethylene Total Hip Arthroplasty Revision Rates and Comparisons Against Ceramic-on-Polyethylene up to 10 Years of Follow-Up.

BACKGROUND: We compared the revision risk between metal-on-polyethylene (MOP) and ceramic-on-polyethylene (COP) total hip arthroplasty patients and evaluated temporal changes in short-term revision risks for MOP patients. METHODS: Primary MOP (n = 9480) and COP (n = 3620) total hip arthroplasties were evaluated from the Medicare data set (October 2005 to December 2015) for revision risk, with up to 10 years of follow-up using multivariate analysis. Temporal change in the short-term revision risk for MOP was evaluated (log-rank and Wilcoxon tests). RESULTS: Revision incidence was 3.8% for COP and 4.3% for MOP. MOP short-term revision risk did not change over time (P ≥ .844 at 1 year and .627 at 2 years). Dislocation was the most common reason for revision (MOP: 23.5%; COP: 24.8%). Overall adjusted revision risks were not different between MOP and COP up to 10 years of follow-up (P ≥ .181). CONCLUSIONS: Concerns with corrosion for metal heads do not appear to result in significantly elevated revision risk for MOP at up to 10 years. Corrosion does not appear as a primary reason for revision compared to other mechanisms.

Smoking, air pollution, and lung cancer risk in the Nurses' Health Study cohort: time-dependent confounding and effect modification.

The proportional hazards (PH) model is commonly used in epidemiology despite the stringent assumption of proportionality of hazards over time. We previously showed, using detailed simulation data, that the impact of a modest risk factor cannot be estimated reliably using the PH model in the presence of confounding by a strong, time-dependent risk factor. Here, we examine the same and related issues using a real dataset. Among 97,303 women in the prospective Nurses' Health Study cohort from 1994 through 2010, we used PH regression to investigate how effect estimates for cigarette smoking are affected by increasingly detailed specification of time-dependent exposure characteristics. We also examined how effect estimates for fine particulate matter (PM2.5), a modest risk factor, are affected by finer control for time-dependent confounding by smoking. The objective of this analysis is not to present a credible estimate of the impact of PM2.5 on lung cancer risk, but to show that estimates based on the PH model are inherently unreliable. The best-fitting model for cigarette smoking and lung cancer included pack-years, duration, time since cessation, and an age-by-pack-years interaction, indicating that the hazard ratio (HR) for pack-years was significantly modified by age. In the fully adjusted best-fitting model for smoking including pack-years, the HR per 10-µg/m3 increase in PM2.5 was 1.06 (95% confidence interval (CI) = 0.90, 1.25); the HR for PM2.5 in the full cohort ranged between 1.02 and 1.10 in models with other smoking adjustments, indicating a residual confounding effect of smoking. The HR for PM2.5 was statistically significant only among former smokers when adjusting for smoking pack-years (HR = 1.35, 95% CI = 1.00, 1.82 in the best-fitting smoking model), but not in models adjusting for smoking duration and average packs (pack-years divided by duration). The association between cumulative smoking and lung cancer is modified by age, and improved model fit is obtained by including multiple time-varying components of smoking history. The association with PM2.5 is residually confounded by smoking and modified by smoking status. These findings underscore limitations of the PH model and emphasize the advantages of directly estimating hazard functions to characterize time-varying exposure and risk. The hazard function, not the relative hazard, is the fundamental measure of risk in a population. As a consequence, the use of time-dependent PH models does not address crucial issues introduced by temporal factors in epidemiological data.

Risk of Reinfection after Irrigation and Debridement of Acute Periprosthetic Joint Infection following TKA.

The purpose of this study was to determine the risk factors associated with reinfection in patients treated with irrigation and debridement (I&D) with liner exchange for an acute (less than 3 months) prosthetic joint infection following the index primary total knee arthroplasty (TKA). Medicare claims database was queried to identify patients with periprosthetic joint infection within 3 months of their index TKA who underwent I&D with tibial polyethylene liner exchange. Exclusion criteria included age < 65 years and < 1 year of claims prior to TKA. A total of 341 patients met our criteria and were analyzed by age, sex, diabetes, obesity, Charlson comorbidity score, and time between TKA and I&D with liner exchange. Average time to I&D with liner exchange following primary TKA was 38.5 ± 21.3 days and multivariate analysis showed a significantly higher risk of reinfection within 1 year in patients > 85 years old (p < 0.001) and diabetes (p < 0.02). The risk of reinfection was lowest for patients treated with I&D with liner exchange within 14 days after TKA (p = 0.028). The incidence of reinfection was 223% greater if I&D with liner exchange was performed 2 to 4 weeks after primary TKA (p < 0.03), and 277% higher if performed > 6 weeks after index procedure compared with those performed within 2 weeks. Patients older than 85 years, diabetics, or treated with I&D with liner exchange > 14 days following the primary TKA had a significantly higher risk of reinfection within 1 year. Patients should be cautioned on the risk of reinfection prior to proceeding with I&D with liner exchange > 2 weeks following the index procedure.

What Are the Migration Patterns for U.S. Primary Total Joint Arthroplasty Patients?

BACKGROUND: Evaluation of total joint arthroplasty (TJA) patient-reported outcomes and survivorship requires that records of the index and potential revision arthroplasty procedure are reliably captured. Until the goal of the American Joint Replacement Registry (AJRR) of more-complete nationwide capture is reached, one must assume that patient migration from hospitals enrolled in the AJRR to nonAJRR hospitals occurs. Since such migration might result in loss to followup and erroneous conclusions on survivorship and other outcomes of interest, we sought to quantify the level of migration and identify factors that might be associated with migration in a specific AJRR population. QUESTIONS/PURPOSES: (1) What are the out-of-state and within-state migration patterns of U.S. Medicare TJA patients over time? (2) What patient demographic and institutional factors are associated with these patterns? METHODS: Hospital records of Medicare fee-for-service beneficiaries enrolled from January 1, 2004 to December 31, 2015, were queried to identify primary TJA procedures. Because of the nationwide nature of the Medicare program, low rates of loss to followup among Medicare beneficiaries, as well as long-established enrollment and claims processing procedures, this database is ideal for examining patient migration after TJA. We identified an initial cohort of 5.33 million TJA records from 2004 to 2016; after excluding patients younger than 65 years of age, those enrolled solely due to disability, those enrolled in a Medicare HMO, or residing outside the United States, the final analytical dataset consisted of 1.38 million THAs and 3.03 million TKAs. The rate of change in state or county of residence, based on Medicare annual enrollment data, was calculated as a function of patient demographic and institutional factors. A multivariate Cox model with competing risk adjustment was used to evaluate the association of patient demographic and institutional factors with risk of out-of-state or out-of-county (within-state) migration. RESULTS: One year after the primary arthroplasty, 0.61% (95% confidence interval [CI], 0.60-0.61; p < 0.001 for this and all comparisons in this Results section) of Medicare patients moved out of state and another 0.62% (95% CI, 0.60-0.63) moved to a different county within the same state. Five years after the primary arthroplasty, approximately 5.41% (95% CI, 5.39-5.44) of patients moved out of state and another 5.50% (95% CI, 5.46-5.54) Medicare patients moved to a different county within the same state. Among numerous factors of interest, women were more likely to migrate out of state compared with men (hazard ratios [HR], 1.06), whereas black patients were less likely (HR, 0.82). Patients in the Midwest were less likely to migrate compared with patients in the South (HR, 0.74). Patients aged 80 and older were more likely to migrate compared with 65- to 69-year-old patients (HR, 1.19). Patients with higher Charlson Comorbidity Index scores compared with 0 were more likely to migrate (index of 5+; HR, 1.19). CONCLUSIONS: Capturing detailed information on patients who migrate out of county or state, with associated changes in medical facility, requires a nationwide network of participating registry hospitals. At 5 years from primary arthroplasty, more than 10% of Medicare patients were found to migrate out of county or out of state, and the rate increases to 18% after 10 years. Since it must be assumed that younger patients might exhibit even higher migration levels, these findings may help inform public policy as a "best-case" estimate of loss to followup under the current AJRR capture area. Our study reinforces the need to continue aggressive hospital recruitment to the AJRR, while future research using an increasingly robust AJRR database may help establish the migration patterns of nonMedicare patients. LEVEL OF EVIDENCE: Level III, therapeutic study.

Does Timing of Primary Total Hip Arthroplasty Prior to or After Lumbar Spine Fusion Have an Effect on Dislocation and Revision Rates?

BACKGROUND: Patients undergoing primary total hip arthroplasty (THA) following lumbar spine fusion have an increased incidence of dislocation compared to those without prior lumbar fusion. The purpose of this study is to determine if timing of THA prior to or after lumbar fusion would have an effect on dislocation and revision incidence in patients with both hip and lumbar spine pathology. METHODS: One hundred percent Medicare inpatient claims data from 2005 to 2015 were used to compare dislocation and revision risks in patients with primary THA with pre-existing lumbar spine fusion vs THA with subsequent lumbar spine fusion within 1, 2, and 5 years after the index THA. A total of 42,300 patients met inclusion criteria, 28,668 patients of which underwent THA with pre-existing lumbar spinal fusion (LSF) and 13,632 patients who had prior THA and subsequent LSF. Patients who had THA first followed by LSF were further stratified based on the interval between index THA and subsequent LSF (1, 2, and 5 years), making 4 total groups for comparison. Multivariate cox regression analysis was performed adjusting for age, socioeconomic status, race, census region, gender, Charlson score, pre-existing conditions, discharge status, length of stay, and hospital characteristics. RESULTS: Patients with prior LSF undergoing THA had a 106% increased risk of dislocation compared to those with LSF done 5 years after THA (P < .001). Risk of revision THA was greater in the pre-existing LSF group by 43%, 41%, and 49% at 1, 2, and 5 years post THA compared to the groups with THA done first with subsequent LSF. Dislocation was the most common etiology for revision THA in all groups, but significantly higher in the prior LSF group (26.6%). CONCLUSION: Results of this study demonstrate that sequence of surgical intervention for concomitant lumbar and hip pathology requiring LSF and THA respectively significantly impacts the fate of the THA performed. Patients with prior LSF undergoing THA are at significantly higher risk of dislocation and subsequent revision compared to those with THA first followed by delayed LSF. LEVEL OF EVIDENCE: 3.

Risk of Opioid-Related Adverse Events After Primary and Revision Total Knee Arthroplasty.

Postoperative analgesia after primary total knee arthroplasty (TKA) and revision knee arthroplasty (RKA) can be reliant on the use of opioids and may lead to opioid-related adverse events (ORAEs). This study evaluated the risk of ORAEs following TKA and RKA using the 5% Medicare claims (2010-2013) database. There were 41,702 TKA and 3817 RKA patients who met the inclusion criteria. At 90 days, respiratory complications were the most common complication (TKA: 6.12%; RKA: 8.01%), followed by postoperative nausea and vomiting (TKA: 2.86%; RKA: 3.95%), and urinary retention complications (TKA: 2.79%; RKA: 3.20%). For TKA, risk factors for respiratory complications included older age, lower socioeconomic status, more comorbidities, obesity, chronic obstructive pulmonary disease, white race, and patients in the Midwest and West (vs. South) (p 002). The average Medicare payment for treating complications within 90 days of a TKA was $6206 and $6222 following RKA. Awareness risks for ORAEs in select patients can assist in developing a multimodal postoperative pain control and patient education protocols. (Journal of Surgical Orthopaedic Advances 27(2):148-154, 2018).

Are We Winning or Losing the Battle With Periprosthetic Joint Infection: Trends in Periprosthetic Joint Infection and Mortality Risk for the Medicare Population.

BACKGROUND: Periprosthetic joint infection (PJI) is a potentially deadly complication of total joint arthroplasty. This study was designed to address how the incidence of PJI and outcome of treatment, including mortality, are changing in the population over time. METHODS: Primary total hip arthroplasty (THA) and total knee arthroplasty (TKA) patients with PJI from the 100% Medicare inpatient data set (2005-2015) were identified. Cox proportional hazards regression models for risk of PJI after THA/TKA (accounting for competing risks) or risk of all-cause mortality after PJI were adjusted for patient and clinical factors, with year included as a covariate to test for time trends. RESULTS: The unadjusted 1-year and 5-year risk of PJI was 0.69% and 1.09% for THA and 0.74% and 1.38% for TKA, respectively. After adjustment, PJI risk did not change significantly by year for THA (P = .63) or TKA (P = .96). The unadjusted 1-year and 5-year overall survival after PJI diagnosis was 88.7% and 67.2% for THA and 91.7% and 71.7% for TKA, respectively. After adjustment, the risk of mortality after PJI decreased significantly by year for THA (hazard ratio = 0.97; P < .001) and TKA (hazard ratio = 0.97; P < .001). CONCLUSION: Despite recent clinical focus on preventing PJI, we are unable to detect substantial decline in the risk of PJI over time, although mortality after PJI has declined. Because PJI risk appears not to be changing over time, the incidence of PJI is anticipated to scale up proportionately with the demand for THA and TKA, which is projected to increase substantially in the coming decade.