Prognosticating in Palliative Care: A survey of Canadian Palliative Care Physicians
Bibliographic record
Abstract
OBJECTIVE: To determine how palliative care physicians view the accuracy and importance of prognostication, what information they consider, and what processes they use. METHODS: A questionnaire was sent to members of the Canadian Society of Palliative Care Physicians (CSPCP). Respondents recorded their perceptions about prognostication and the factors they considered when predicting survival. A patient scenario was described in which a prognosis was requested by two different people: a patient's daughter and a palliative care admissions coordinator. RESULTS: 90 responses were received from 219 CSPCP members (41.1 percent). There was moderate agreement between respondents' perceptions of their own accuracy and that of other physicians (K = 0.549). Of all the respondents, 89.9 percent believed that prognosticating was somewhat or very important. They considered clinical factors most commonly when prognosticating. A range of predictions was given for the scenario; often, the same physician gave different answers to the two people requesting a prognosis. CONCLUSION: Palliative care physicians believe that prognostication is important and use clinical factors to estimate survival. They often give different estimates to different information recipients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".