Outpatient palliative medicine consultations: urgent or routine?
Bibliographic record
Abstract
BACKGROUND: Although outpatient palliative care clinics (OPCCs) provide a venue for early, pre-emptive referral to palliative care on a routine basis, some patients will continue to require urgent referrals. The purpose of this study was to characterise these urgent referrals to determine whether they reflect clinical need or convenience. METHODS: We retrospectively compared new patients in an OPCC who were seen urgently versus those seen at routine appointments. Descriptive statistics compared the two groups in terms of clinical characteristics, referring teams, symptoms, performance status and outcomes. Logistic regression was used to identify factors associated with urgent referral to the OPCC. Overall survival was compared using the log-rank test. RESULTS: Between January 2016 and December 2017, a total of 113 urgent referrals were reviewed in the OPCC; these were compared with a random sample of 217 routine referrals. Patients seen urgently were more likely to be referred by surgical oncology, and to report worse symptom scores for pain (p=0.0007), tiredness (p=0.02), well-being (p=0.001), constipation (p=0.02) and sleep (p=0.01). More patients seen urgently required direct admission to hospital following the visit (17.7% vs 0.9%, p<0.001). Median survival was shorter for patients seen urgently (4.3 months, 95% CI 3.4 to 7.8) versus routinely (8.1 months, 95% CI 7.2 to 9.5). CONCLUSIONS: Compared with routine referrals, new patients seen urgently in the OPCC had higher symptom burden, shorter median survival and a greater chance of direct admission to hospital. Palliative care clinics should consider how best to accommodate urgent referrals.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".