Clinical needs of patients referred early to supportive and palliative care.
Bibliographic record
Abstract
9065 Background: Palliative care is evolving from delivering care to patients at the end-of-life to those earlier in the disease trajectory. We evaluated the differences in clinical characteristics, symptoms burdens, and service utilization between traditional palliative care patients (late referrals, LR) and the new patients group who are in earlier in their course of disease (early referrals, ER). Methods: We reviewed consecutive cancer patients referred to the Supportive Care Clinic with follow up visit within 30 days between August 2008 and October 2010. Patients were divided into two groups: ER (defined as patients with expected survival ≥ 2 years or receiving treatment for curative intent) and LR (all others). We compared clinical characteristics, symptoms and service utilization between both groups using chi-square test and Wilcoxon rank sum test. Results: 58% (695/1208) patients had a 2nd visit within 30 days. Among them, 100 patients were classified as ER (14.4%) and 100/595 LR were randomly selected as the comparison group. ER patients were younger (median age 54 years vs 60 years, p=0.009), more likely to have head and neck cancer (67% vs 6%, p<0.001) and to have a shorter interval between cancer diagnosis and palliative care consultation (3.8 m vs 16.2 m, <0.001). ER patients were also more likely to be CAGE positive (15% vs 4%, p=.014), referred from radiation oncology (49% vs 3%, p<0.001), referred for treatment related side effects (70% vs 9%, p<0.001), and receiving active anti-cancer treatment at the time of consultation (74% vs 48%, p=0.0002). Baseline symptoms (Edmonton Symptom Assessment Scale) were similar between ER and LR except for insomnia (1.8 vs 2, p=0.004). LR patients experienced greater improvement in the symptom distress score (-5.5 vs -3, p=0.007). Overall median number of medical visits was 24 for ER vs 10.5 for LR (p<0.001); however, median visit per month was 4.3 for LR and 2.1 for ER (p<0.001). Conclusions: ER was associated with different patient characteristics; patients have similar distress but different needs and outcomes as compared to traditional LR 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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".