Cardiopulmonary exercise performance and factors associated with aerobic capacity in neuromuscular diseases
Bibliographic record
Abstract
Abstract Introduction/Aims Aerobic deconditioning, due to lower levels of physical activity, could impact independence for people with neuromuscular conditions. We report the maximal cardiopulmonary response in a cohort of people with Charcot Marie Tooth disease type 1A (CMT 1A) and inclusion body myositis (IBM). We also explored potential predictors of aerobic capacity with measures of physical impairment and functional performance. Methods Participants underwent maximal cardiopulmonary exercise testing (CPET) using a semi‐recumbent cycle ergometer. Data were analyzed to determine the peak O2 consumption (VO2 peak), anaerobic threshold (AT), maximum heart rate (MHR), ventilatory equivalent for CO2 slope (VE/VCO2), and respiratory exchange ratio (RER). Impairment, functional and patient reported measures were also recorded. Predicted CPET variables were calculated based on published normative data for age, gender, and weight. Results Twenty‐two people with CMT and 17 people with IBM were recruited. Both groups showed significantly lower VO2 peak, MHR, AT, and VE/VCO2. The CMT group overall performed better than the IBM group, with significantly higher VO2 peak, MHR, and AT, but lower VE/VCO2. Linear regression analysis demonstrated that VO2 peak was related to body fat percentage and 6‐min walk distance for both groups, and steps per day for the IBM group. Discussion Lower than predicted CPET variables were observed that were not explained by cardiopulmonary limitations or reduced effort, implicating peripheral factors in limiting the cycling task. Regression analysis implied prediction of VO2 peak by body fat percentage and 6‐min walk distance. Six‐minute walk distance could be a potential proxy measure of cardiopulmonary fitness.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".