While preoperative bloodwork is routinely ordered, its value in determining which patients are at risk of postoperative readmission following total knee arthroplasty (TKA) and total hip arthroplasty (THA) is unclear. The objective of this study was to determine which routinely ordered preoperative blood markers have the strongest association with acute hospital readmission for patients undergoing elective TKA and THA. Two population-based retrospective cohorts were assembled for all adult primary elective TKA (n = 137,969) and THA (n = 78,532) patients between 2011 to 2018 across 678 North American hospitals using the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) registry. Six routinely ordered preoperative blood markers - albumin, haematocrit, platelet count, white blood cell count (WBC), estimated glomerular filtration rate (eGFR), and sodium level - were queried. The association between preoperative blood marker values and all-cause readmission within 30 days of surgery was compared using univariable analysis and multivariable logistic regression adjusted for relevant patient and treatment factors.Aims
Methods
Advances in surgical technique and implant design may influence the incidence and mechanism of failure resulting in revision total hip arthroplasty (rTHA). The purpose of the current study was to characterize aetiologies requiring rTHA, and to determine whether temporal changes existed in these aetiologies over a ten-year period. All rTHAs performed at a single institution from 2009 to 2019 were identified. Demographic information and mode of implant failure was obtained for all patients. Data for rTHA were stratified into two time periods to assess for temporal changes: 2009 to 2013, and 2014 to 2019. Operative reports, radiological imaging, and current procedural terminology (CPT) codes were cross-checked to ensure the accurate classification of revision aetiology for each patient.Aims
Methods
Medical comorbidities are a critical factor in the decision-making process for operative management and risk-stratification. The Hierarchical Condition Categories (HCC) risk adjustment model is a powerful measure of illness severity for patients treated by surgeons. The HCC is utilized by Medicare to predict medical expenditure risk and to reimburse physicians accordingly. HCC weighs comorbidities differently to calculate risk. This study determines the prevalence of medical comorbidities and the average HCC score in Medicare patients being evaluated by neurosurgeons and orthopaedic surgeon, as well as a subset of academic spine surgeons within both specialities, in the USA. The Medicare Provider Utilization and Payment Database, which is based on data from the Centers for Medicare and Medicaid Services’ National Claims History Standard Analytic Files, was analyzed for this study. Every surgeon who submitted a valid Medicare Part B non-institutional claim during the 2013 calendar year was included in this study. This database was queried for medical comorbidities and HCC scores of each patient who had, at minimum, a single office visit with a surgeon. This data included 21,204 orthopaedic surgeons and 4,372 neurosurgeons across 54 states/territories in the USA.Aims
Methods
