Nutritional status, symptoms, and inflammation among older adults with different functional levels with cancer in palliative care
Bibliographic record
Abstract
Abstract Objectives This study aimed to assess the nutritional status, symptoms, food intake, and inflammatory activity of older adults with cancer with the Karnofsky Performance Status scale (KPS) ≥50% receiving palliative care. Methods Cross-sectional study with outpatients divided into two groups by the Karnofsky Performance Status scale: 80 to 100% (Group 1) and 50 to 70% (Group 2). Nutritional status was assessed using the Mini Nutritional Assessment (MAN), food intake using the 24-hour food recall, symptoms using the Edmonton Symptom Assessment System and serum interleukin-6 (IL-6) levels were measured. Results Age was 69.6±5.9 years. MNA was higher for Group 1 (23.4±2.7 vs 19.4±3.1, p<0.001). Group 2 ingested lower amounts of total energy (p=0.003), carbohydrates (p=0.017), protein (p=0.007), total fat (p=0.004), saturated fat (p=0.006), fiber (p=0.012), and dietary cholesterol (p=0.009). Group 2 had a greater intensity of symptoms such as pain (p=0.02), nausea (p=0.01), shortness of breath (p=0.04) and lack of sensation of wellbeing. There was no difference in IL-6 between groups (p=0.13); however, higher IL-6 was associated with a higher prevalence of dyspnea and a lower calorie, carbohydrate, and dietary cholesterol intake. Conclusions The lower the functional capacity of older cancer patients under palliative care, the worse their nutritional status, with lower intake of nutrients and increased number of symptoms. This study brings an important scientific contribution to older adults with cancer in palliative care, supporting nutritional and symptom assessment in health care.
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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 | 0.001 |
| 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 | 0.000 |
| 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".