Blood transfusion and postoperative anaemia are complications of total knee arthroplasty (TKA) that are associated with substantial healthcare costs, morbidity, and mortality. There are few data from large datasets on the risk factors for these complications. We retrospectively reviewed the records of TKA patients from a single tertiary care institution from February 2016 to December 2020. There were a total of 14,901 patients in this cohort with a mean age of 67.9 years (SD 9.2), and 5,575 patients (37.4%) were male. Outcomes included perioperative blood transfusion and postoperative anaemia, defined a priori as haemoglobin level < 10 g/dl measured on the first day postoperatively. In order to establish a preoperative haemoglobin cutoff, we investigated a preoperative haemoglobin level that would limit transfusion likelihood to ≤ 1% (13 g/dl) and postoperative anaemia likelihood to 4.1%. Risk factors were assessed through multivariable Poisson regression modelling with robust error variance.Aims
Methods
This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA). Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.Aims
Methods
The aim of this study was to determine the general postoperative opioid consumption and rate of appropriate disposal of excess opioid prescriptions in patients undergoing primary unilateral total knee arthroplasty (TKA). In total, 112 patients undergoing surgery with one of eight arthroplasty surgeons at a single specialty hospital were prospectively enrolled. Three patients were excluded for undergoing secondary procedures within six weeks. Daily pain levels and opioid consumption, quantity, and disposal patterns for leftover medications were collected for six weeks following surgery using a text-messaging platform.Aims
Patients and Methods
