Machine Learning Models to Predict Withdrawal of Life-Sustaining Therapy in Patients With Severe Traumatic Brain Injury

In this study of using ML to predict WLST after severe TBI, our models reliably predict the decision to WLST. We found that institutional withdrawal culture is a strong independent determinant of WLST, irrespective of clinical condition. As TBI care improves, our findings underscore the importance of refining prognosticating tools to prevent premature WLST decisions which may be influenced by biases associated with self-fulfilling prophecies and institutional practice patterns.