Ethics of non-therapeutic research on imminently dying patients in the intensive care unit
Bibliographic record
Abstract
Non-therapeutic research with imminently dying patients in intensive care presents complex ethical issues. The vulnerabilities of the imminently dying, together with societal disquiet around death and dying, contribute to an intuition that such research is beyond the legitimate scope of scientific inquiry. Yet excluding imminently dying patients from research hinders the advancement of medical science to the detriment of future patients. Building on existing ethical guidelines for research, we propose a framework for the ethical design and conduct of research involving the imminently dying. To enable rapid translation to practice, we frame the approach in the form of eight ethical questions that researchers and research ethics committees ought to answer prior to conducting any research with this patient population. (1) Does the study hypothesis require the inclusion of imminently dying patients? (2) Are non-therapeutic risks and burdens minimised consistent with sound scientific design? (3) Are the risks of these procedures no more than minimal risk? (4) Are these non-therapeutic risks justified insofar as they are reasonable in relation to the anticipated benefits of the study? (5) Will valid informed consent be obtained from an authorised surrogate decision maker? (6) How will incidental findings be handled? (7) What additional steps are in place to protect families and significant others of research participants? (8) What additional steps are in place to protect clinical staff and researchers? Several ethical challenges hinder research with imminently dying patients. Nonetheless, provided adequate protections are in place, non-therapeutic research with imminently dying patients is ethically justifiable. Applying our framework to an ongoing study, we demonstrate how our question-driven approach is well suited to guiding investigators and research ethics committees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.299 | 0.295 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.037 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.016 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".