Referrals of Cancer versus Non-Cancer Patients to A Palliative Care Consult Team: Do They Differ?
Bibliographic record
Abstract
This retrospective study compared 100 consecutive non-cancer (NC) patients referred to a palliative care consult team (PCT) in a Swiss university hospital to 506 cancer (C) patients referred during the same period. The frequencies of reported symptoms were similar in both groups. The main reasons for referral in the NC group were symptom control, global evaluation, and assistance with discharge. Requests for symptom control predominated in the C group. Prior to the first visit, 50% of NC patients were on opioids, compared to 58% of C patients. After the first visit, the proportion of NC patients on opioids increased to 64% and the proportion of C patients to 73%. The median daily oral morphine equivalent dose for NC patients taking opioids prior to the first PCT visit was higher than that for C patients (60 mg versus 45 mg). At the time of death or discharge, the percentage of NC patients on opioids was 64%, while that of C patients was 76%. Moreover, NC patients were on significantly lower median doses of opioids than C patients (31 mg versus 60 mg). Over half the NC patients died during hospitalization, as compared to 33% of C patients. Only 6% of NC patients were discharged to palliative care units, as compared to 22% of C 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".