Beamy S Sharma1, Matthew W Swisher1, Christina N Doan1, Bahareh Khatibi1, Rodney A Gabriel2. 1. Department of Anesthesiology, University of California, San Diego, San Diego, CA, United States of America. 2. Department of Anesthesiology, University of California, San Diego, San Diego, CA, United States of America; Department of Medicine, Division of Biomedical Informatics, University of California, San Diego, San Diego, CA, United States of America. Electronic address: ragabriel@ucsd.edu.
Abstract
STUDY OBJECTIVE: We sought to develop a predictive model for discharge to post-acute care facilities in patients undergoing unilateral total hip replacement (THR). Furthermore, we sought to determine if the use of neuraxial anesthesia was an important covariate for the predictive model. DESIGN: Retrospective observational study. SETTING: Preoperative care and operating room at a single institution. PATIENTS: Patients (n = 960) who underwent an elective primary THR between 2014 and 2016. INTERVENTIONS: No intervention was performed. MEASUREMENTS: We collected variables that were known preoperatively including age, sex, body mass index (BMI), preoperative opioid use, functional status based on metabolic equivalents (METS), preoperative anemia, thrombocytopenia, osteoarthritis and contralateral osteoarthritis grade, anesthesia type, comorbidities and surgical approach. We then performed multivariable logistic regression to develop a predictive model. MAIN RESULTS: Female sex, preoperative opioid use, older age, general anesthesia, anemia, hypertension, a psychiatric diagnosis, use of dialysis, metabolic equivalents <4 and obesity are all risk factors for a post-acute facility discharge. The use of general anesthesia compared to neuraxial anesthesia was associated with increased odds (odds ratio 1.98, 95% confidence interval 1.31-3.00, p = 0.001) for post-acute facility discharge. Model performance was assessed using ten-fold cross-validation - the average area under the receiver operating characteristic curve calculated was 0.794. CONCLUSIONS: We developed a predictive model for post-acute care facility discharge following THR. The use of neuraxial anesthesia was associated with decreased odds for post-acute care facility discharge.
STUDY OBJECTIVE: We sought to develop a predictive model for discharge to post-acute care facilities in patients undergoing unilateral total hip replacement (THR). Furthermore, we sought to determine if the use of neuraxial anesthesia was an important covariate for the predictive model. DESIGN: Retrospective observational study. SETTING: Preoperative care and operating room at a single institution. PATIENTS: Patients (n = 960) who underwent an elective primary THR between 2014 and 2016. INTERVENTIONS: No intervention was performed. MEASUREMENTS: We collected variables that were known preoperatively including age, sex, body mass index (BMI), preoperative opioid use, functional status based on metabolic equivalents (METS), preoperative anemia, thrombocytopenia, osteoarthritis and contralateral osteoarthritis grade, anesthesia type, comorbidities and surgical approach. We then performed multivariable logistic regression to develop a predictive model. MAIN RESULTS: Female sex, preoperative opioid use, older age, general anesthesia, anemia, hypertension, a psychiatric diagnosis, use of dialysis, metabolic equivalents <4 and obesity are all risk factors for a post-acute facility discharge. The use of general anesthesia compared to neuraxial anesthesia was associated with increased odds (odds ratio 1.98, 95% confidence interval 1.31-3.00, p = 0.001) for post-acute facility discharge. Model performance was assessed using ten-fold cross-validation - the average area under the receiver operating characteristic curve calculated was 0.794. CONCLUSIONS: We developed a predictive model for post-acute care facility discharge following THR. The use of neuraxial anesthesia was associated with decreased odds for post-acute care facility discharge.
Authors: Kevin T Pritchard; Ickpyo Hong; James S Goodwin; Jordan R Westra; Yong-Fang Kuo; Kenneth J Ottenbacher Journal: J Am Med Dir Assoc Date: 2020-10-09 Impact factor: 7.802