Brain Death

This first-in-human pilot study will test an investigational miniature breathing device called the Hope inVent. The device is a small, single-use, in-line respirator that connects to a breathing tube and uses compressed oxygen to help move air in and out of the lungs. It has no moving parts and is designed to provide short-term breathing support in situations where standard ventilators may not be available, such as emergencies, disasters, battlefield settings, transport, or ventilator shortages. The study will enroll up to 5 brain-dead organ donors who are already receiving mechanical ventilation at the Gift of Life Donor Care Center at the Hospital of the University of Pennsylvania. Donors will only be included after authorization for organ donation and research has been obtained through standard procedures. Donors who may donate lungs or who have significant lung disease will not be included. During the study, investigators will briefly replace the standard ventilator with the Hope inVent device for up to 15 minutes. The standard ventilator will remain immediately available, and the donor will be continuously monitored by the clinical and research teams. Investigators will measure whether the device can maintain acceptable breathing measures, including oxygen level and carbon dioxide level. They will also record breathing pressures and tidal volume, which is the amount of air delivered with each breath. If the device does not perform as expected or if any safety concern occurs, the donor will be returned immediately to the standard ventilator. There is no direct benefit to the organ donor. Information from this study may help determine whether this type of simple, low-cost breathing device could be useful for future patients who need emergency or short-term ventilator support when standard ventilators are not available.

The aim of the study is to verify the reliability of the current purely clinical examination of the pupils (without the support of a pupillometer) in the context of clinically suspected brain death, compared to the results of a non-invasive, automated, and highly precise monocular pupillometric examination.

Background: Recent electroencephalography (EEG) data indicate that the transition from clinical death to cellular death is marked by highly organized neurophysiological events, including significant surges in gamma-band power, cross-frequency coupling, and distinct spreading depolarization waves. This prospective, observational feasibility study utilizes rapid-deployment, high-density, noninvasive BCI hardware paired with proprietary AI analytics to detect, classify, and securely archive these terminal neurocognitive signals. Objectives: (1) Quantify transient gamma-band activity and cross-frequency connectivity post-clinical death; (2) Validate the efficacy of machine learning models for real-time signal classification in high-noise clinical environments; (3) Establish a highly secure, encrypted bio-informational archive of peri-life EEG data. Design: Prospective, open-label, multicenter, observational cohort (n\>20).