Experiences of substitute decision-makers with requests for consent to non-therapeutic research participation during the dying process, including to what degree such requests are perceived as burdensome, have not been well described. In this study, we explored the lived experiences of family members who consented to non-therapeutic research participation on behalf of an imminently dying patient. We interviewed 33 family members involved in surrogate research consent decisions for dying patients in intensive care. Non-therapeutic research involved continuous physiological monitoring of dying patients (...) prior to and for 30 min following cessation of circulation. At some study centres participation involved installation of bedside computers. At one centre electroencephalogram monitoring was used with a subset of participants. Aside from additional monitoring, the research protocol did not involve deviations from usual end-of-life care. Thematic analysis of interviews suggests most family members did not perceive this minimal-risk, non-therapeutic study to affect their time with patients during the dying process, nor did they perceive research consent as an additional burden. In our analysis, consenting for participation in perimortem research offered families of the dying an opportunity to affirm the intrinsic value of patients’ lives and contributions. This opportunity may be particularly important for families of patients who consented to organ donation but did not proceed to organ retrieval. Our work supports concerns that traditional models of informed consent fail to account for possible benefits and harms of perimortem research to surviving families. Further research into consent models which integrate patient and family perspectives is needed. All data relevant to the study are included in the article. (shrink)

This manuscript reports on a landmark symposium on the ethical, legal and technical challenges of xenotransplantation in the UK. King’s College London, with endorsement from the British Transplantation Society (BTS), and the European Society of Organ Transplantation (ESOT), brought together a group of experts in xenotransplantation science, ethics and law to discuss the ethical, regulatory and technical challenges surrounding translating xenotransplantation into the clinical setting. The symposium was the first of its kind in the UK for 20 years. This paper (...) summarises the content of the expert lectures showcasing the progress which has been made in xenotransplantation including—the history of xenotransplantation, advances in gene edited animals and progress towards clinical xenotransplantation. We then set out the ethical and legal issues still to be resolved. Finally, we report the themes of the roundtable discussion highlighting areas of consensus and controversy. While the detail of the legal discussion was directed towards the UK, the principles and summary reported here are intended to be applicable to any jurisdiction seeking to implement clinical xenotransplantation. (shrink)

The Journal of Medical Ethics can sometimes read part Men Like Gods and part A Brave New World. At times, we learn how all controversies can resolved with reference to four principles. At other times, we learn how “every discovery in pure science is potentially subversive”.1 This issue is no exception. Here, we can read about the utopia of gene editing, manufactured organs, and machine learnt algorithmic decision-making. We can also read about the dystopia of inherited disorders from edited germlines, (...) the testing of xenotransplants on braindead patients, and misdiagnosis by artificial intelligence. What we see in the three papers that I will foreground here is the application of medical ethics to avoid the dystopia while preserving the promises of medical science. But as I seek to explain here, our ability to address the controversies that we anticipate in medical science depend on our ability to refine our understanding of what medical ethics requires of us now. From the diagnosis of eye diseases from fungus images to predicting the risk of imminent risk of suicide attempts, machine learnt medical decision making has, in some high profile instances, outperformed clinicians in medical diagnosis and treatment recommendations. While clinician and machine learnt diagnoses will both involve degrees of uncertainty and fallibility, Thomas Grote2 asks us to consider is how much weight a clinician ought to give an algorithmic diagnosis which she disagreements with. Since a clinician is held to account for …. (shrink)