The unexpected death of a patient in the clinical setting: some ethical reflections.
Bibliographic record
Abstract
The death of a patient is always a significant event; however, the unexpected death of a patient is immeasurably more significant and can strike the physician with devastating force, stressing her or his ability to cope to the very limit. There are several reasons for this. They range from professional (Was the death a result of incompetence or negligence? Were other professional factors involved that could have been foreseen, dealt with, or avoided?) to psychological (Was the professional psychologically attached to her patients, in general, and to this patient, in particular?) to spiritual (Did her personal beliefs and values affect her outlook on death in a way that might cause personal turmoil?). However, there is one factor that is almost invariably overlooked, yet it goes to the very heart of the situation. It concerns the ethical legitimacy of the feelings that are being experienced, and centers on 3 notions that are basic to medicine as a profession: the notion of a patient, the concept of healthcare, and the nature of medicine itself. What follows is a brief sketch of how these factors function, how they are interrelated, and how they may be resolved. Readers are encouraged to respond to George Lundberg, MD, Editor of MedGenMed, for the editor's eye only or for possible publication via email: ten.epacsdem@grebdnulg
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.028 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.046 | 0.050 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".