Characteristics of Belgian "life-ending acts without explicit patient request": a large-scale death certificate survey revisited
Bibliographic record
Abstract
BACKGROUND: "Life-ending acts without explicit patient request," as identified in robust international studies, are central in current debates on physician-assisted dying. Despite their contentiousness, little attention has been paid to their actual characteristics and to what extent they truly represent nonvoluntary termination of life. METHODS: We analyzed the 66 cases of life-ending acts without explicit patient request identified in a large-scale survey of physicians certifying a representative sample of deaths (n = 6927) in Flanders, Belgium, in 2007. The characteristics we studied included physicians' labelling of the act, treatment course and doses used, and patient involvement in the decision. RESULTS: In most cases (87.9%), physicians labelled their acts in terms of symptom treatment rather than in terms of ending life. By comparing drug combinations and doses of opioids used, we found that the life-ending acts were similar to intensified pain and symptom treatment and were distinct from euthanasia. In 45 cases, there was at least 1 characteristic inconsistent with the common understanding of the practice: either patients had previously expressed a wish for ending life (16/66, 24.4%), physicians reported that the administered doses had not been higher than necessary to relieve suffering (22/66, 33.3%), or both (7/66, 10.6%). INTERPRETATION: Most of the cases we studied did not fit the label of "nonvoluntary life-ending" for at least 1 of the following reasons: the drugs were administered with a focus on symptom control; a hastened death was highly unlikely; or the act was taken in accordance with the patient's previously expressed wishes. Thus, we recommend a more nuanced view of life-ending acts without explicit patient request in the debate on physician-assisted dying.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".