Verbalized desire for death or euthanasia in advanced cancer patients receiving palliative care
Bibliographic record
Abstract
OBJECTIVE: We aimed to address the prevalence of desire-to-die statements (DDSs) among terminally ill cancer patients in an acute palliative care unit. We also intended to compare the underlying differences between those patients who make desire-to-die comments (DDCs) and those who make desire-for-euthanasia comments (EUCs). METHOD: We conducted a one-year cross-sectional prospective study in all patients receiving palliative care who had made a DDC or EUC. At inclusion, we evaluated symptom intensity, anxiety and depression, and conducted a semistructured interview regarding the reasons for these comments. RESULTS: Of the 701 patients attended to during the study period, 69 (9.8%; IC 95% 7.7-12.3) made a DDS: 51 (7.3%) a DDC, and 18 (2.5%) an EUC. Using Edmonton Symptom Assessment Scale (ESAS) DDC group showed higher percentage of moderate-severe symptoms (ESAS > 4) for well-being (91 vs. 25%; p = 0.001), depression (67 vs. 25%; p = 0.055), and anxiety (52 vs. 13%; p = 0.060) than EUC group. EUC patients also considered themselves less spiritual (44 vs. 84%; p = 0.034). The single most common reason for a DDS was pain or physical suffering, though most of the reasons given were nonphysical. SIGNIFICANCE OF RESULTS: Almost 10% of the population receiving specific oncological palliative care made a DDC (7.3%) or EUC (2.5%). The worst well-being score was lower in the EUC group. The reasons for both a DDC and EUC were mainly nonphysical. We find that emotional and spiritual issues should be identified and effectively addressed when responding to a DDS in terminally ill cancer patients.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".