Respecting Patient Autonomy Versus Protecting the Patient's Health
Bibliographic record
Abstract
A 74-year-old man with multiple chronic medical problems was hospitalized for respiratory distress. He experienced recurrent aspiration and required frequent suctioning and endotracheal intubation on several occasions. The patient was deemed competent and steadfastly refused feeding tube placement. The patient demanded that he be allowed to eat a normal diet despite being told that it could lead to his death. The patient wanted to go home, but there was no one there to care for him. Additionally, neither a nursing home nor hospice would accept him in his present condition. The case is especially interesting because of the symbolic value of food and the plight of the patient who has no alternative to hospitalization. The hospital staff experienced considerable stress at having to care for him. They were uncertain whether their obligation was to respect his autonomy and continue to provide food or to protect his health by avoiding aspiration, pneumonia, and possible death by denying him food. This ethical dilemma posed by the professionals' duty to do what is in the patient's best interest versus the patient's right to decide treatment serves as the focus for this case study. Ethical, legal, and healthcare practitioners' considerations are explored. The case study concludes with specific recommendations for treatment.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".