Comparing Indices of Neuromuscular Fatigue with Subjective Fatigue in Cancer Survivors
Bibliographic record
Abstract
Cancer-related fatigue (CRF) is the most common patient reported side effect of cancer treatment. There is no universally accepted definition of CRF, thus it is rarely addressed in cancer patients and survivors. Although it is a multi-dimensional concept, including physiological and psychological aspects, it currently is quantified almost exclusively through subjective scales, thereby missing key physiological factors, specifically indicators of neuromuscular (NM) fatigue. Traditional NM fatigue tests are often single-joint isometric contractions and do not reflect activities of daily living (ADL) corresponding to quality of life. Since cycling is a whole-body dynamic exercise and a common exercise in rehabilitation for cancer survivors, we evaluated NM function before, during and after an incremental cycling test in cancer survivors. PURPOSE: To determine if there are differences in knee extensors (KE) NM function at rest and during exercise between subjectively fatigued and non-fatigued cancer survivors. METHODS: Cancer survivors (n=17, age 53 ±12 years) completed the FACIT-F Scale and NM function testing before, during and following an incremental cycling test to task failure consisting of 3-minute stages separated by an isometric maximal voluntary contraction (MVC) and evoked stimulation of the femoral nerve. Pre-testing occurred on a chair with KE force measured isometrically by force transducer. Testing during cycling took place on a recumbent ergometer with instrumented pedals, which were immobilized instantaneously at the end of each stage, to measure isometric force. Unpaired t-tests compared resting twitch and MVC on the ergometer prior to exercise in 6 fatigued (FACIT-F: 25 ± 3) and 11 non-fatigued (FACIT-F: 44 ± 6) subjects based on FACIT-F 34/52 cut off for significant fatigue. RESULTS: KE twitch at rest normalized to body mass was significantly lower in the fatigued group than the non-fatigued group (0.85 ± 0.18 vs 1.05 ± 0.18 N·kg-1, p=0.04). There was no significant difference between groups for MVC (p=0.14) or any fatigue index (i.e. Δ % voluntary activation, peak twitch, MVC). CONCLUSION: Preliminary results show that fatigued cancer survivors may have a deteriorated muscle function at rest but are not more fatigable with an exercise that mimics ADL. Study funded by an anonymous donor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".