Statistical methods dictate the estimated impact of body mass index on major and minor complications after total joint arthroplasty

Background Elevated body mass index (BMI) is considered a risk factor for complications after THA and TKA. Stakeholders have proposed BMI cutoffs for those seeking arthroplasty. The research that might substantiate BMI cutoffs is sensitive to the statistical methods used, but the impact of the statistical methods used to modelBMI has not been defined. Questions/purposes (1) How does the estimated postarthroplasty risk of minor and major complications vary as a function of the statistical method used to model BMI? (2) What is the prognostic value of BMI for predicting complications with each statistical method? Methods Using the American College of Surgeons National Surgical Quality Improvement Program from 2005 to 2012, we investigated the impact of BMI on major and minor complication risk for THA and TKA. Analyses were weighted with covariate-balancing propensity scores to account for the differential rate of comorbidities across the range of BMI. We specified BMI in two ways: (1) categorically by World Health Organization (WHO) BMI classes; and (2) as a smooth, continuous variable using splines. Models of risk for major complications (deep surgical site infection [SSI], pulmonary embolism, stroke, cardiac arrest, myocardial infarction, wound disruption, implant failure, unplanned intubation, > 48 hours on a ventilator, acute renal insufficiency, coma, sepsis, reoperation, or mortality) and minor complications (superficial SSI, pneumonia, urinary tract infection, deep vein thrombosis, or peripheral nerve injury) were constructed and were adjusted for confounding variables known to correlate with complications (eg, American Society of Anesthesiologists classification). Results were compared for different specifications of BMI. Receiver operating characteristic (ROC) curves were compared to determine the additive prognostic value of BMI. Results The type of BMI parameterization leads to different assessments of risk of postarthroplasty complications for BMIs > 30 kg/m² and < 20 kg/m² with the spline specification showing better fit in all adjusted models (Akaike Information Criteria favors spline). Modeling BMI categorically using WHO classes indicates that BMI cut points of 40 kg/m2 for TKA or 35 kg/m² for THA are associated with higher risks of major complications. Modeling BMI continuously as a spline suggests that risk of major complications is elevated at a cut point of 44 kg/m² for TKA and 35 kg/m² for THA. Additionally, in these models, risk does not uniformly increase with increasing BMI. Regardless of the method of modeling, BMI is a poor prognosticator for complications with area under the ROC curves between 0.51 and 0.56, false-positive rates of 96% to 97%, and false-negative rates of 2% to 3%. Conclusions The statistical assumptions made when modeling the effect of BMI on postarthroplasty complications dictate the results. Simple categorical handling of BMI creates arbitrary cutoff points that should not be used to inform larger policy decisions. Spline modeling of BMI avoids arbitrary cut points and provides a better model fit at extremes of BMI. Regardless of statistical management, BMI is an inadequate independent prognosticator of risk for individual patients considering total joint arthroplasty. Stakeholders should instead perform comprehensive risk assessment and avoid use of BMI as an isolated indicator of risk.