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BackgroundPatient, surgeon, health system, and device factors are all known to influence outcomes in THA. However, patient-related factors associated with an increased risk of early failure are poorly understood, particularly in elderly patients.Questions/purposesWe identified specific demographic and clinical characteristics associated with increased risk of early revision in Medicare patients with THA.MethodsThe Medicare 5% national sample administrative database was used to calculate the relative risk of revision within 12 months following primary THA as a function of baseline medical comorbidities in 56,030 Medicare patients who underwent primary THA between 1998 and 2010. The impact of 29 comorbid conditions on risk of early revision was examined using Cox regression, controlling for age, sex, race, US Census region, socioeconomic status, and all other baseline comorbidities.ResultsDepression, rheumatologic disease, psychoses, renal disease, chronic urinary tract infection, and congestive heart failure were associated with revision THA within 12 months of the index arthroplasty (p ≤ 0.038 for all comparisons; risk factors listed in order of significance).ConclusionsThis information is important when counseling elderly patients with THA regarding the risk of early failure and for risk stratifying publicly reported outcomes in Medicare patients with THA.

BackgroundPatient, surgeon, health system, and device factors are all known to influence outcomes in total knee arthroplasty (TKA). However, patient-related factors associated with an increased risk of early failure are not well understood, particularly in elderly patients.Questions/purposesThe purpose of this study was to identify specific comorbid conditions associated with increased risk of early revision in Medicare patients undergoing TKA.MethodsA total of 117,903 Medicare patients who underwent primary TKA between 1998 and 2010 were identified from the Medicare 5% national sample administrative database and used to determine the relative risk of revision within 12 months after primary TKA as a function of baseline medical comorbidities. Cox regression was used to evaluate the impact of 29 comorbid conditions on risk of early failure controlling for age, sex, race, census region, socioeconomic status, and all other baseline comorbidities.ResultsThe most significant independent risk factors for revision TKA within 12 months were chronic pulmonary disease, depression, alcohol abuse, drug abuse, renal disease, hemiplegia or paraplegia, and obesity.ConclusionsThis information could be valuable to patients and their surgeons when making shared medical decisions regarding elective TKA and for risk-stratifying publicly reported outcomes in Medicare patients undergoing TKA.

BackgroundAlthough risk factors for periprosthetic joint infection (PJI) and mortality after total hip arthroplasty (THA) have been identified, interactions between specific patient risk factors are poorly understood. Therefore, it is difficult for surgeons to counsel patients on their individual risk of PJI or mortality after THA.Questions/purposesWe evaluated the interaction between patient clinical and demographic factors on the risk of PJI and mortality after THA and developed an electronic risk calculator for estimating the patient-specific risk of PJI and mortality in Medicare patients with THA.MethodsWe used the Medicare 5% sample claims database to calculate the risk of PJI within 2 years and mortality within 90 days after THA in 53,252 Medicare patients with primary THAs between 1998 and 2009. Logistic regression using 29 comorbid conditions, age, sex, race, and socioeconomic status were used as inputs to develop an electronic risk calculator to estimate patient-specific risk of PJI and mortality after THA.ResultsThe overall 2-year risk of PJI and 90-day risk of mortality after primary THA were 2.07% and 1.30%, respectively. White women aged 70 to 74 years with alcohol abuse, depression, electrolyte disorder, peptic ulcer disease, urinary tract infection, rheumatologic disease, preoperative anemia, cardiopulmonary (cardiac arrhythmia, congestive heart failure, ischemic heart disease, chronic pulmonary disease) comorbidities, and peripheral vascular disease were at highest risk for PJI. White women aged 65 to 69 years with electrolyte disorder, hemiplegia/paraplegia, hypertension, hypothyroidism, metastatic tumor, preoperative anemia, coagulopathy, cardiopulmonary (congestive heart failure, chronic pulmonary disease) and psychiatric (psychoses, depression) comorbidities, malignancies, and peripheral vascular disease were at highest risk for mortality. An electronic risk calculator was developed to estimate the risk of PJI and mortality in Medicare patients with THA.ConclusionsThis electronic risk calculator can be used to counsel Medicare patients regarding their patient-specific risks of PJI and mortality after THA.Level of evidenceLevel II, prognostic study. See the Instructions for Authors for a complete description of levels of evidence.

To address the long-term problems of bearing surface wear and osteolysis associated with conventional metal-polyethylene (M-PE) total hip arthroplasty (THA), metal-metal (M-M), and ceramic-ceramic (C-C) bearings have been introduced. These bearing surfaces are associated with unique risks and benefits and higher costs. However the relative risks of these three bearings in an older population is unknown.We compared the short-term risk of complication and revision THA among Medicare patients having a primary THA with metal-polyethylene (M-PE), metal-metal (M-M), and ceramic-ceramic (C-C) bearings.We used the 2005 to 2007 100% Medicare inpatient claim files to perform a matched cohort analysis in three separate cohorts of THA patients (M-PE, M-M, and C-C) who were matched by age, gender, and US census region. Multivariate Cox proportional-hazards models were constructed to compare complication and revision THA risk among cohorts, adjusting for medical comorbidities, race, socioeconomic status, and hospital factors.After adjusting for patient and hospital factors, M-M bearings were associated with a higher risk of periprosthetic joint infection (hazard ratio, 3.03; confidence interval, 1.02–9.09) when compared with C-C bearings (0.59% versus 0.32%, respectively). There were no other differences among bearing cohorts in the adjusted risk of revision THA or any other complication.The risk of short-term complication (including dislocation) and revision THA were similar among appropriately matched Medicare THA patients regardless of bearing surface. Hard-on-hard THA bearings are of questionable value in Medicare patients, given the higher cost associated with their use and uncertain long-term benefits in older patients.Level II, prognostic study. See Guidelines for Authors for a complete description of levels of evidence.

Understanding the cause of failure and type of revision total knee arthroplasty (TKA) procedures performed in the United States is essential in guiding research, implant design, and clinical decision making in TKA. We assessed the causes of failure and specific types of revision TKA procedures performed in the United States using newly implemented ICD-9-CM diagnosis and procedure codes related to revision TKA data from the Nationwide Inpatient Sample (NIS) database. Clinical, demographic, and economic data were reviewed and analyzed from 60,355 revision TKA procedures performed in the United States between October 1, 2005 and December 31, 2006. The most common causes of revision TKA were infection (25.2%) and implant loosening (16.1%), and the most common type of revision TKA procedure reported was all component revision (35.2%). Revision TKA procedures were most commonly performed in large, urban, nonteaching hospitals in Medicare patients ages 65 to 74. The average length of hospital stay (LOS) for all revision TKA procedures was 5.1 days, and the average total charges were $49,360. However, average LOS, average charges, and procedure frequencies varied considerably by census region, hospital type, and procedure performed. Level of Evidence: Level II, economic and decision analysis. See Guidelines for Authors for a complete description of levels of evidence.