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
Smoking is known to have an adverse effect on wound healing and musculoskeletal conditions. This case-controlled study looked at whether smoking has a deleterious effect in the outcome of autologous chondrocyte implantation for the treatment of full thickness chondral defects of the knee. The mean Modified Cincinatti Knee score was statistically significantly lower in smokers (n = 48) than in non-smokers (n = 66) both before and after surgery (p <
0.05). Smokers experienced significantly less improvement in the knee score two years after surgery (p <
0.05). Graft failures were only seen in smokers (p = 0.016). There was a strong negative correlation between the number of cigarettes smoked and the outcome following surgery (Pearson’s correlation coefficient −0.65, p = 0.004). These results suggest that patients who smoke have worse pre-operative function and obtain less benefit from this procedure than non-smokers. The counselling of patients undergoing autologous chondrocyte implantation should include smoking, not only as a general cardiopulmonary risk but also because poorer results can be expected in smokers following this procedure.
