Malnutrition, fatigue, frailty, vulnerability, sarcopenia and cachexia
Bibliographic record
Abstract
PURPOSE OF REVIEW: Malnutrition, fatigue, frailty, vulnerability, sarcopenia and cachexia all phenotypically present with the same features because they are subject to the operation of similar mechanistic factors. However, the conditions referred to above differ by which mechanism dominates the cause of the clinical condition. This review discusses the overlap and differences, which distinguish as well as unite these different conditions and allow a rationale for treatment. RECENT FINDINGS: In the continuum of malnutrition, cachexia, sarcopenia and frailty the recent activities focus on two areas. The first is a better understanding of the mechanisms of cachexia and sarcopenia and frailty. In particular, the differential effects of cytokines on muscle and on the hypothalamic system. The effects of inactivity promoting the loss of body mass in cachexia and sarcopenia as well as the positive effects of exercise. The second is the development of a synthesis of available literature to develop consensus documents about the definition, causes, diagnosis and treatment of cachexia, sarcopenia and frailty. SUMMARY: Loss of body tissues resulting in wasting is a common phenotype for several different conditions which can be caused by a combination of reduced food intake, excessive requirements, altered metabolism, sepsis, trauma, ageing and inactivity. They have been referred to loosely as malnutrition but in not all will respond to simply providing nutrients. In this review the common features and the differences as they relate to cause and response to treatment are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".