Abstract
BACKGROUND: The low organ donation rate in Germany is associated with deficiencies in the identification of patients at risk of developing brain death. An automated digital clinical support system (DETECT) was designed to prospectively identify intensive care patients who are at risk of developing brain death. The objective of the study is to evaluate the effectiveness of DETECT in the detection of patients with severe brain injury who progress toward brain death compared to standard practice without DETECT. METHODS: The study will follow a multicentre, cluster-randomized, controlled design conducted at 19 sites in Germany over a 30-month period. The study will include patients aged ≥ 18 years with primary or secondary acute brain injury, requiring mechanical ventilation and death during hospital stay. DETECT periodically processes real-time data from the ICU information system to screen for a combination of coma and absent bilateral pupillary light reflexes-both considered early indicators of impending brain death. In the event of a positive screen, an automated notification will be sent to the designated transplant coordinators. The email is intended to prompt clinical assessment of the detected patient and, if necessary, initiate a guideline-based brain death evaluation. The primary endpoint is the identification of patients who develop brain death during hospitalization. Secondary endpoints encompass missed identification of potential brain death cases and deceased organ donations. Upon completion of the study, a survey will be conducted to investigate the stakeholders' experiences with DETECT. DISCUSSION: Findings will provide insights into the effectiveness of an automated digital support system for the detection of patients at risk of developing brain death and potential organ donors. Automation may enhance ICU workflow efficiency and timely decision-making in organ donation processes. TRIAL REGISTRATION: ClinicalTrials.gov NCT06293170. Registered on March 5, 2024.