An Interprofessional Palliative Care Oncology Rehabilitation Program: Effects on Function and Predictors of Program Completion
Bibliographic record
Abstract
BACKGROUND: After treatment, patients with active cancer face a considerable burden from the effects of both the disease and its treatment. The Palliative Rehabilitation Program (prp) is designed to ameliorate disease effects and to improve the patient's functioning. The present study evaluated predictors of program completion and changes in functioning, symptoms, and well-being after the program. METHODS: The program received referrals for 173 patients who had finished anticancer therapy. Of those 173 patients, 116 with advanced cancer were eligible and enrolled in the 8-week interprofessional prp; 67 completed it. Measures of physical, nutritional, social, and psychological functioning were evaluated at entry to the program and at completion. RESULTS: Participants experienced significant improvements in physical performance (p < 0.000), nutrition (p = 0.001), symptom severity (p = 0.005 to 0.001), symptom interference with functioning (p = 0.003 to 0.001), fatigue (p = 0.001), and physical endurance, mobility, and balance or function (p = 0.001 to 0.001). Reasons that participants did not complete the prp were disease progression, geographic inaccessibility, being too well (program not challenging enough), death, and personal or unknown reasons. A normal level of C-reactive protein (<10 mg/L, p = 0.029) was a predictor of program completion. CONCLUSIONS: Patients living with advanced cancers who underwent the interprofessional prp experienced significant improvement in functioning across several domains. Program completion can be predicted by a normal level of C-reactive protein.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".