The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC.Aims
Methods
Emergency department (ED) visits following primary total knee arthroplasty (TKA) can lead to poor patient satisfaction, potentially unnecessary readmissions, and greater overall healthcare costs. Reasons for post-operative ED visits are often entirely medical in nature and can be independent of the recent operation. Several strategies have been developed to help reduce ED visits. However, one major factor that can play a critical role in addressing potentially avoidable visits is provider and patient education. A major factor that can play a crucial role in addressing potentially avoidable visits is provider and patient education. It follows that a thorough understanding of which patients are visiting the ED and why can help in avoiding the visits. Therefore, the purpose of this study was to investigate: 1) causes and 2) patient-related factors (demographics and comorbidities) associated with ED visits following primary TKA. A national private payer database was queried for primary TKAs performed between 2007 and 2016 using the International Classification of Disease, ninth revision (ICD-9) procedural code 81.54. ED visits were identified using Current Procedural Terminology (CPT) codes 99281 to 99285. Patients with 90-day ED visits were in the study group (n=28,044) whereas those without 90-day ED visits served as controls (n=82,289). Causes for ED visits were divided into cardiopulmonary, gastrointestinal, renal, thromboembolic, leg pain, or wound-related. Patient demographics and risk factors assessed included age, gender, and body mass index (BMI) as well as several comorbidities (Table 1). Pearson's chi-square tests were performed to compare patient demographics and comorbidities between the cohorts. In order to adjust for potential confounders, multivariate binomial logistic regression analysis was performed to further evaluate the associations between patient factors and 90-day ED visits. A p-value less than 0.01 was considered statistically significant.Introduction
Methods
The purpose of this study was to analyze trends in the surgical management of ON in recent years. Specifically, we evaluated the annual prevalences of: 1) joint preserving procedures (osteotomies and core decompression/grafts) and 2) joint non-preserving procedures (total hip arthroplasties [THAs], revision THAs, partial THAs) for the treatment of osteonecrosis of the femoral head (ONFH) between 2009 and 2016. A total of 406,239 ONFH patients who were treated between 2009 and 2016 were identified from a nationwide database. Treatment procedures were extracted using ICD-9-CM and ICD-10-CM procedure codes. Annual rates of each of the above procedures were calculated and the trends in the procedure types were also evaluated. Chi-square tests were performed to compare the annual prevalence of each procedure. The mean annual prevalence over the 8-year study period was calculated for each procedure.Introduction
Background
Much effort has been aimed at strategies for patient optimization, perioperative standards of care, and postoperative risk stratification to reduce the incidence of SSI. Examples include, newer dressing modalities, antibiotic-impregnated bone cement, intra-wound powdered antibiotics, as well as novel suture types and techniques, all of which have shown great potential. However, the question remains as to whether these changes in practice have led to lower overall infections over the past few years. Therefore, the purpose of this study was to track the annual rates and trends of: 1) overall; 2) deep; and 3) superficial SSI following total hip arthroplasty (THA) using the most recent data (2012 to 2016) from a large nationwide database. The National Surgical Quality Improvement Program database was queried for all primary THAs (CPT code 27130) between 2012 and 2016, yielding 122,451 cases. Cases with reported superficial and/or deep SSIs were combined for an overall rate, and then independently analyzed as deep and superficial SSIs. The infection incidence for each year was calculated. After an overall 5-year correlation and trends, univariate analysis was also performed to compare the most recent year, 2016, with each of the preceding 4 years. Furthermore, a comparison of overall and deep SSI incidences from this study were compared to meta-analysis of pooled data from 2001 to 2011. Pearson correlation coefficients and chi-squared tests were used to determine correlation and statistical significance which was maintained at a p-value less than 0.05.Background
Methods
