Supplementary Material for: Clinical Considerations in Physician-Assisted Death for Probable Alzheimer’s Disease: Decision-Making Capacity, Anosognosia, and Suffering
Bibliographic record
Abstract
Background: Requests for physician-assisted death (PAD) in patients with cognitive impairment are complex and require careful consideration. Of particular difficulty is determination of whether the request is voluntary and well considered. Results: Euthanasia and physician-assisted suicide (PAS) are both legal in The Netherlands, Luxemburg, Colombia, and Canada. Euthanasia is legal in Belgium, while PAS is legal in Switzerland and Oregon, Washington, Montana, Vermont, and California (USA). Upon a PAD request, evaluation of the capacity to consent medical treatment is relevant for the decision-making process, while evaluation of testamentary capacity is appropriate before an advance euthanasia directive is written. Anosognosia assessment throughout the Alzheimer’s disease continuum provides essential and relevant information regarding the voluntary and well-considered nature of the PAD request; meanwhile, early assessment of hypernosognosia or subjective cognitive decline assists in formulation of a clinical prognosis. Furthermore, the assessment of physical and psychological suffering should incorporate verbal and nonverbal cues as well as consideration of the psychosocial factors that might affect due care criteria. Conclusion: The clinical approach to a PAD request should consider the legal framework and the decision-making capacity, assess memory deficit awareness and the perception of suffering, and evaluate mental competency when considered pertinent.
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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 | 0.001 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.834 | 0.215 |
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".