CT Derived Muscle Measures, Inflammation, and Frailty in a Cohort of Older Cancer Patients
Bibliographic record
Abstract
BACKGROUND/AIM: Muscle loss, inflammation, and frailty are prevalent among older cancer patients. We aimed to evaluate whether inflammatory markers could identify muscle loss, and if muscle measures differed between frail and non-frail patients. PATIENTS AND METHODS: A total of 115 patients ≥70 years old with solid tumors were included. Inflammation was measured using the Glasgow Prognostic Score (GPS), which is based on C-reactive protein (CRP) and albumin levels, and CRP alone. Frailty was evaluated using a modified geriatric assessment (mGA) of eight domains affecting older patients' health status. Computed tomography-derived muscle measures were collected at the level of the third lumbar vertebra. RESULTS: Patients with GPS=2 and CRP>27 mg/l exhibited poorer muscle measures compared to patients with lower levels. No associations between mGA-based frailty and muscle mass were found. CONCLUSION: Inflammation has detrimental effects on muscle mass. However, GPS or CRP alone cannot be used to identify muscle loss, and muscle measures were not associated with frailty in this series.
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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 | 0.001 | 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".