Prediction of suitable outpatient candidates following revision total knee arthroplasty using machine learning.

Aims: To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Methods: Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC), calibration, and decision curve analysis. Important and significant variables were identified from the models. Results: Of the 5,600 patients included in this study, 342 (6.1%) underwent SDD. The random forest (RF) model performed the best overall, with an internally validated AUC of 0.810. The ten crucial factors favoring SDD in the RF model include operating time, anaesthesia type, age, BMI, American Society of Anesthesiologists grade, race, history of diabetes, rTKA type, sex, and smoking status. Eight of these variables were also found to be significant in the MLR model. Conclusion: The RF model displayed excellent accuracy and identified clinically important variables for determining candidates for SDD following rTKA. Machine learning techniques such as RF will allow clinicians to accurately risk-stratify their patients preoperatively, in order to optimize resources and improve patient outcomes.

Extraoral anterior approach for the treatment of os odontoideum: illustrative case.

BACKGROUND: Os odontoideum is typically treated with instrumented fusion through a posterior cervical approach. When this approach fails, limited options for revision are available. Occipitocervical fusion and transoral anterior fusions have been utilized in the past but are associated with high morbidity and complications. OBSERVATIONS: Here the authors report a case of os odontoideum that was treated with an anterior cervical extraoral approach after failed posterior instrumented fusion. They discuss the challenges that can be encountered with the failure of fusion and the limited options when it comes to approach and fixation of os odontoideum. LESSONS: To the authors' knowledge and based on a review of the literature, this case represents the first use of an anterior extraoral prevascular approach to the high cervical spine to address os odontoideum. They demonstrate that this approach can be utilized as a reasonable alternative to transoral surgery and should be considered in cases where additional or alternative fixation is desired without the morbidity and complications associated with occipitocervical fusion or a transoral approach, especially in a younger patient population.