Psychological symptoms of illness and emotional distress in advanced cancer cachexia
Bibliographic record
Abstract
PURPOSE OF REVIEW: Cachexia induces both physical and psychological symptoms of illness in patients with advanced cancer and may generate emotional distress in patients and families. However, physical symptoms of cachexia received the most emphasis. The aims of this review are to elucidate a link between systemic inflammation underlying cachexia and psychological symptoms and emotional distress, and to advance care strategy for management of psychological symptoms and emotional distress in patients and families. RECENT FINDINGS: The main themes in the literature covered by this review are psychological symptoms in patients and emotional distress in patients and families. Studies of the underlying biology of cachexia identify the role of the central nervous system to amplify tumor-induced systemic inflammation. The brain mediates a cluster of symptoms, such as sleep disruption, anxiety, cognitive impairment, and reduction in motivated behavior (notably anorexia). These are distressing to patients as well as to families. SUMMARY: There is growing recognition that holistic multimodal interventions are needed to alleviate psychological symptoms and emotional distress and to improve quality of life in patients with cancer cachexia and families. This is an approach that addresses not only physical health but also psychological, emotional, and social well being issues.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".