Appetite in Palliative Cancer Patients and Its Association with Albumin, CRP and Quality of Life in Men and Women—Cross-Sectional Data from the Palliative D-Study
Bibliographic record
Abstract
Albumin is an important biochemical marker in palliative cancer care, used for assessment of nutritional status, disease severity and prognosis. Our primary aim was to investigate sex differences in the association between appetite and albumin levels in palliative cancer patients. We also aimed to study associations between appetite and C-reactive protein (CRP), Quality of Life (QoL), pain and fatigue. In the Palliative D-cohort, consisting of 266 men and 264 women, we found a correlation between appetite and albumin; low appetite, measured with the Edmonton Symptom Assessment System, correlated significantly with low albumin in men: (r = −0.33, p < 0.001), but not in women (r = −0.03, p = 0.65). In a regression analysis adjusted for confounding factors, results were similar. Lower appetite was correlated with higher CRP in men (r = 0.27, p < 0.001), but not in women (r = 0.12, p = 0.05). Appetite was correlated with QoL, fatigue and pain in both men and women; those with a low appetite had a low QoL and high fatigue- and pain-scores (p < 0.001). In conclusion, our results indicated possible sex differences in the associations between appetite and albumin, and between appetite and CRP, in palliative care patients. Understanding these associations could provide additional value for clinical practice.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".