Mid-thigh cross-sectional area and lower limb muscle function in patients with lung cancer
Bibliographic record
Abstract
Background: Patients with lung cancer (LC) often experience cachexia which cause fatigue, weight loss, muscle wasting and associated with reduced physical function. Even though, skeletal muscle is the main site of muscle depletion in these patients, little is known about thigh muscle area and function. Aim: To assess and compare mid-thigh cross sectional muscle area (CSA) and quadriceps muscle function of patients with LC at diagnosis to healthy subjects. Method: A computed tomography of the two legs was obtained in 11 LC patients and 6 healthy age-matched controls. CSA was calculated using standard tissue attenuation (At) range and separated into normal At (35-100HU), low At (0-34HU) and residual muscle (-1 to -29HU).Mean At was also calculated to assess muscle adiposity. Subjects performed also a quadriceps isokinetic endurance test (30 reps at 90°/sec). Results: LC patients (Stage I-II=7;III-IV=4) and controls were matched for age (69±7yr vs 67±9yr) and BMI (27±5Kg/m2 vs 27±2 Kg/m2).Data on CSA and muscle function are shown in the table. Conclusion: Despite similar BMI and CSA, LC patients had greater muscle adiposity accompanied with reduced muscle strength and endurance.Thus, assessing muscle function and composition may enable a more comprehensive assessment of cachexia and physical function in LC patients.
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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) | 0.002 | 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".