Rectus Femoris Ultrasound to Evaluate Muscle During Prehabilitation for Patients With Cancer
Bibliographic record
Abstract
INTRODUCTION: Skeletal muscle wasting is prevalent in patients awaiting cancer surgery. In preparation for surgery, prehabilitation has been shown to enhance functional capacity; however, its impact on muscle remains inconsistent. This exploratory study evaluated muscle changes using ultrasound of rectus femoris before and after prehabilitation in patients with cancer scheduled for surgery. METHODS: Adults referred to a prehabilitation clinic before elective cancer surgery, with a preoperative window of ≥4 wk, were prospectively enrolled in this pre-post interventional study. Participants completed a 4-6 wk prehabilitation program consisting of exercise, nutritional, and psychosocial interventions. Ultrasound assessments of the rectus femoris thickness and echo intensity of the dominant thigh were conducted at baseline and post intervention, alongside physical function assessments. RESULTS: Forty-seven participants (53% female) with a mean age of 69 y were included in the analysis. The most common cancer types were lung (34%) and esophagogastric (28%). Nineteen participants (40%) were receiving neoadjuvant therapy. No significant changes were observed in muscle thickness (0.3 mm; 95% confidence interval [CI], -0.3 to 0.9; P = 0.311) or echo intensity (0.5 arbitrary units; 95% CI, -3.7 to 4.7; P = 0.807) following prehabilitation. However, the 6 minute walk distance increased by 19 m (95% CI, 2 to 37; P = 0.031), reflecting a clinically meaningful improvement in functional capacity. Participants who demonstrated maintenance or improvement in muscle thickness and echo intensity exhibited significant improvements in leg strength and walking capacity. CONCLUSIONS: Ultrasound assessment of rectus femoris is feasible and reliable for monitoring muscle changes during prehabilitation. Prehabilitation may help preserve muscle in patients with cancer during the preoperative period.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".