PURPOSE: To identify factors that independently predict extended length of stay after unicompartmental knee arthroplasty (UKA) surgery (defined as length of stay longer than 3 days), and to identify factors predicting early post-operative complications. METHODS: A retrospective analysis of all patients undergoing UKA from January 2016-January 2019 at our institution was performed. Clinical notes were reviewed to determine the following information: Patient age (years), gender, American Society of Anesthesiologists (ASA) grade, weight (kg), height (meters), body mass index (BMI), co-morbidities, indication for surgery, surgeon, surgical volume, surgical technique (navigated or patient-specific instrumentation), implant manufacturer, estimated blood loss (ml), application of tourniquet during the surgery, application of drain, hospital length of stay (days) and surgical complications. RESULTS: Multivariate regression analysis showed that ASA 3-4 vs. ASA 1-2 [OR 4.4 (CI; 1.8-10.8, p = 0.001)] and a history of cardiovascular disease [OR 2.8 (CI; 1.4-5.5), p = 0.004)] were significant independent predictors of prolonged length of stay. Hosmer-Lemeshow goodness of fit of the model showed a p-value of 0.214. Nagelkerke R-Square was 0.2. For complications, multivariate regression analysis showed that ASA 3-4 vs. ASA 1-2 [OR 5.8 (CI; 1.7-20.7)] and high BMI (BMI >30) [OR 4.3 (CI; 1.1-17.1)] were significant independent predictors of complications. Hosmer-Lemeshow goodness of fit was 0.89 and Nagelkerke R-Square was 0.2. Patients treated with robotics (Navio) techniques had shorter length of stay median 51 h (IQR; 29-96) when compared to other techniques 72 h (IQR; 52-96), p = 0.008. CONCLUSION: Based on the results of our study, high ASA grade (≥3) appears to be the most important factor excluding eligibility for fast-track UKA. Any number of co-morbidities may increase ASA, but in and of themselves, apart from a history of cardiovascular disease, they should not be seen as contraindications. Appropriate patient selection, technical tools and details during the surgery could facilitate fast track surgery. Crown
PURPOSE: To identify factors that independently predict extended length of stay after unicompartmental knee arthroplasty (UKA) surgery (defined as length of stay longer than 3 days), and to identify factors predicting early post-operative complications. METHODS: A retrospective analysis of all patients undergoing UKA from January 2016-January 2019 at our institution was performed. Clinical notes were reviewed to determine the following information: Patient age (years), gender, American Society of Anesthesiologists (ASA) grade, weight (kg), height (meters), body mass index (BMI), co-morbidities, indication for surgery, surgeon, surgical volume, surgical technique (navigated or patient-specific instrumentation), implant manufacturer, estimated blood loss (ml), application of tourniquet during the surgery, application of drain, hospital length of stay (days) and surgical complications. RESULTS: Multivariate regression analysis showed that ASA 3-4 vs. ASA 1-2 [OR 4.4 (CI; 1.8-10.8, p = 0.001)] and a history of cardiovascular disease [OR 2.8 (CI; 1.4-5.5), p = 0.004)] were significant independent predictors of prolonged length of stay. Hosmer-Lemeshow goodness of fit of the model showed a p-value of 0.214. Nagelkerke R-Square was 0.2. For complications, multivariate regression analysis showed that ASA 3-4 vs. ASA 1-2 [OR 5.8 (CI; 1.7-20.7)] and high BMI (BMI >30) [OR 4.3 (CI; 1.1-17.1)] were significant independent predictors of complications. Hosmer-Lemeshow goodness of fit was 0.89 and Nagelkerke R-Square was 0.2. Patients treated with robotics (Navio) techniques had shorter length of stay median 51 h (IQR; 29-96) when compared to other techniques 72 h (IQR; 52-96), p = 0.008. CONCLUSION: Based on the results of our study, high ASA grade (≥3) appears to be the most important factor excluding eligibility for fast-track UKA. Any number of co-morbidities may increase ASA, but in and of themselves, apart from a history of cardiovascular disease, they should not be seen as contraindications. Appropriate patient selection, technical tools and details during the surgery could facilitate fast track surgery. Crown
Authors: Youssef F El Bitar; Kenneth D Illingworth; Steven L Scaife; John V Horberg; Khaled J Saleh Journal: J Arthroplasty Date: 2015-05-08 Impact factor: 4.757
Authors: Benjamin F Ricciardi; Kathryn K Oi; Steven B Daines; Yuo-Yu Lee; Amethia D Joseph; Geoffrey H Westrich Journal: J Arthroplasty Date: 2016-10-21 Impact factor: 4.757
Authors: Michael P Bolognesi; Melissa A Greiner; David E Attarian; Tyler Steven Watters; Samuel S Wellman; Lesley H Curtis; Keith R Berend; Soko Setoguchi Journal: J Bone Joint Surg Am Date: 2013-11-20 Impact factor: 5.284
Authors: Richard A Berger; Sharat K Kusuma; Sheila A Sanders; Elizabeth S Thill; Scott M Sporer Journal: Clin Orthop Relat Res Date: 2009-02-24 Impact factor: 4.176
Authors: Joseph S Gondusky; Leera Choi; Naila Khalaf; Jay Patel; Steven Barnett; Robert Gorab Journal: J Arthroplasty Date: 2013-10-31 Impact factor: 4.757