Rates of readmission and reoperation following primary total knee arthroplasty (TKA) are under scrutiny due to new payment models, which penalize these negative outcomes. Some risk factors are more modifiable than others, and some conditions considered modifiable such as obesity may not be as modifiable in the setting of advanced arthritis as many propose. We sought to determine whether controlling for hypoalbuminaemia would mitigate the effect that prior authors had identified in patients with obesity. We reviewed the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database for the period of January 2008 to December 2016 to evaluate the rates of reoperation and readmission within 30 days following primary TKA. Multivariate logistic regression modelling controlled for preoperative albumin, age, sex, and comorbidity status.Aims
Methods
Rates of readmission and reoperation following primary total knee arthroplasty (TKA) are under scrutiny due to new payment models, which penalize these negative outcomes. Many prior studies have demonstrated the risk of perioperative complications among patients with obesity. However, an elevated complication rate among patients with poor nutrition, as measured by hypoalbuminemia, has also been reported. We sought to determine whether controlling for hypoalbuminemia would mitigate the effect that prior authors had identified in patients with obesity. In addition, we hoped to identify an albumin threshold above which risk of readmission and reoperation would be minimized. We reviewed the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database for the period of 2008–2016 to evaluate the rates of perioperative complications among primary TKA patients by obesity category and albumin level. Patients were divided into groups according to World Health Organization obesity category and continuous as well as dichotomous albumin level. The primary outcomes were readmission and reoperation within 30 days of surgery. Patients without BMI or albumin data were excluded, as were patients undergoing surgery for the treatment of fracture or bone tumor. Univariate logistic regression compared predictive value of body mass index and albumin on incidence of these outcomes, using the normal weight and albumin > 3.5 g/dL groups as controls. Multivariate logistic regression modeling controlled for age, gender, and comorbidity status. Receiver operator curves (ROC) were generated to determine if an albumin threshold could be determined, above which risk for these complications would be minimized.Introduction
Materials and Methods
