Turcotte JJ, Menon N, Aja JM, et al. - A predictive model was developed to guide preoperative inpatient admission decisions based upon readily available patient demographic and comorbidity data. Between January 2018 and October 2019, researchers conducted a retrospective review including a total of 1,415 patients undergoing elective unilateral primary total hip arthroplasty (THA). Researchers applied multiple logistic regression to develop a model for predicting length of stay (LOS) ≥ 2 days based on preoperative demographics and comorbidities. The data exhibited that increased age, female gender, chronic obstructive pulmonary disorder, congestive heart failure, and multiple comorbidities are risk factors for inpatient hospital LOS of 2 or more days for patients undergoing primary THA. It was revealed that this predictive model based on readily available patient presentation and comorbidity characteristics may aid surgeons in preoperatively distinguishing individuals requiring inpatient admission with removal of THA from the Medicare inpatient-only list.