The current study aimed to compare robotic arm-assisted (RA-THA), computer-assisted (CA-THA), and manual (M-THA) total hip arthroplasty regarding in-hospital metrics including length of stay (LOS), discharge disposition, in-hospital complications, and cost of RA-THA versus M-THA and CA-THA versus M-THA, as well as trends in use and uptake over a ten-year period, and future projections of uptake and use of RA-THA and CA-THA. The National Inpatient Sample was queried for primary THAs (2008 to 2017) which were categorized into RA-THA, CA-THA, and M-THA. Past and projected use, demographic characteristics distribution, income, type of insurance, location, and healthcare setting were compared among the three cohorts. In-hospital complications, LOS, discharge disposition, and in-hospital costs were compared between propensity score-matched cohorts of M-THA versus RA-THA and M-THA versus CA-THA to adjust for baseline characteristics and comorbidities.Aims
Methods
With the removal of total hip arthroplasty (THA) from the Centers for Medicare & Medicaid Services (CMS) inpatient-only list, understanding predictors of length of stay (LOS) after THA is critical. Thus, we aimed to determine the influence of patient- and procedure-related risk factors as predictors of >1-day LOS after THA. A prospective cohort of 5,281 patients underwent primary THA between January 2016 and April 2019. Risk factors increased LOS were categorized as patient-related (demographics, smoking status, baseline Veterans RAND 12 Item Health Survey Mental Component Summary score [VR-12 MCS], Charlson Comorbidity Index [CCI], surgical indication, baseline Hip Injury and Osteoarthritis Outcome Score [HOOS] pain subscore and baseline HOOS physical function shortform (HOOS-PS), range of motion, and predicted discharge disposition) or procedure-related (hospital site, surgeon, approach, day of surgery, and surgery start time). By using the Akaike information criterion (AIC) and internally-validated concordance probabilities (C-index) for discriminating a 1-day LOS from a >1-day LOS, we compared performance between a patient-related risk factors only model and a model containing both patient- and procedure-related risk factors.Introduction
Methods
The diagnosis of periprosthetic joint infection (PJI) is difficult and requires a battery of tests and clinical findings. The purpose of this review is to summarize all current evidence for common and new serum biomarkers utilized in the diagnosis of PJI. We searched two literature databases, using terms that encompass all hip and knee arthroplasty procedures, as well as PJI and statistical terms reflecting diagnostic parameters. The findings are summarized as a narrative review.Objectives
Methods
