• Christos Lazaridis, Ali Mansour, and Manasvini Singh.
• Division of Neurocritical Care, Departments of Neurology and Neurosurgery, University of Chicago Medical Center, Chicago, Illinois, USA. Electronic address: lazaridis@uchicago.edu.
• World Neurosurg. 2022 Jan 1; 157: e327-e332.

BackgroundDecompressive craniectomy (DC) is highly effective in relieving intracranial hypertension; however, patient selection, intracranial pressure threshold, timing, and long-term functional outcomes are all subject to controversy. Recently, recommendations were made to update the Brain Trauma Foundation guidelines in regards to the use of DC based on the DECRA (Decompressive Craniectomy in Patients with Severe Traumatic Brain Injury) and RESCUEicp (Trial of Decompressive Craniectomy for Traumatic Intracranial Hypertension) clinical trials. Neither the updated recommendations, nor the aforementioned trials, provide a method in incorporating individualized patient or surrogate decision-maker preferences into decision making.MethodsIn this manuscript, we aimed to redress the gap of not incorporating patient preferences in such value-laden decision making as in the case of DC for refractory post-traumatic intracranial hypertension. We proposed a decision aid based on principles of Decision Theory, and specifically of Expected Utility Theory.ResultsWe showed that 1) early secondary DC as studied in DECRA, and based on the 1-year outcome data, is associated with decreased expected utility for all possible preference rankings of outcomes; and 2) recommending a late secondary DC versus tier-3 medical therapy, as studied in RESCUEicp, should be informed by individualized patient preference rankings of outcomes as elicited via shared decision-making.ConclusionsThe 1-year outcomes from DECRA and RESCUEicp have served as the basis for updated guidelines. However, unaided interpretation of trial data may not be adequate for individualized decision-making; we suggest that the latter can be significantly supported by decision aids such as the one described here and based on expected utility theory.Copyright © 2021 Elsevier Inc. All rights reserved.

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