Development of a Risk Stratification Model for Delayed Inpatient Recovery of Physical Activities in Patients Undergoing Total Hip Replacement

STUDY DESIGN: Prospective cohort design using data derived from usual care. BACKGROUND: It is important that patients are able to function independently as soon as possible after total hip replacement. However, the speed of regaining activities differs significantly. OBJECTIVES: To develop a risk stratification model (RSM) to predict delayed inpatient recovery of physical activities in people who underwent total hip replacement surgery. METHODS: This study was performed in 2 routine orthopaedic seings: Diakonessenhuis Hospital (seing A) and Nij Smellinghe Hospital (seing B). Preoperative screening was performed for all consecutive patients. In-hospital recovery of activities was assessed with the Modified Iowa Level of Assistance Scale. Delayed inpatient recovery of activities was defined as greater than 5 days. The RSM, developed using logistic regression analysis and bootstrapping, was based on data from seing A (n = 154). External validation was performed on the data set from seing B (n = 271). RESULTS: Twenty-one percent of the patients in seing A had a delayed recovery of activities during their hospital stay. Multivariable logistic regression modeling yielded a preliminary RSM that included the following factors: male sex (odds ratio [OR] = 0.8; 95% confidence interval [CI]: 0.2, 2.6), 70 or more years of age (OR = 1.2; 95% CI: 0.4, 3.4), body mass index of 25 kg/m2 or greater (OR = 2.2; 95% CI: 0.7, 7.4), an American Society of Anesthesiologists score of 3 (OR = 1.2; 95% CI: 0.3, 4.4), a Charnley score of B or C (OR = 6.1; 95% CI: 2.2, 17.4), and a timed up-and-go score of 12.5 seconds or greater (OR = 3.1; 95% CI: 1.1, 9.0). The area under the receiver operating characteristic (ROC) curve was 0.82 (95% CI: 0.74, 0.90) and the Hosmer-Lemeshow test score was 3.57 (P>.05). External validation yielded an area under the ROC curve of 0.71 (95% CI: 0.61, 0.81). CONCLUSION: We demonstrated that the risk for delayed recovery of activities during the hospital stay can be predicted by using preoperative data.