Fatigue and quality of life outcomes of palliative care consultation: A prospective, observational study in a tertiary cancer center
Bibliographic record
Abstract
PURPOSE: Fatigue is one of the most common symptoms seen in patients with advanced cancer. It is known to influence the Quality of Life (QoL) of patients. This study examines the interrelationship of fatigue and QoL in patients with advanced cancer on palliative care. METHODS: A prospective cohort study was conducted in the outpatient clinic of the Department of Palliative Medicine from January to June 2014. Patients with advanced cancer registered with hospital palliative care unit, meeting the inclusion criteria (Eastern Cooperative Oncology Group [ECOG] ≤3, Edmonton Symptom Assessment Scale [ESAS] fatigue score ≥1), and willing to participate in the study were assessed for symptom burden (ESAS) and QoL (European Organization for Research and Treatment of Cancer QoL Core 15-Palliative module [EORTC-QoL PAL15]). All study patients received standard palliative care consultation and management. They were followed up in person or telephonically within 15-30 days from the first consult for assessment of outcomes. RESULTS: < 0.001) at follow-up. Improvement in physical functioning and insomnia were significantly associated with better fatigue outcomes. CONCLUSIONS: Fatigue improved with the standard palliative care delivered at our specialty palliative care clinic. Certain clinical, biochemical factors and QoL aspects were associated with fatigue severity at baseline, improvement of which lead to lesser fatigue at follow-up.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".