Beneficial effects of an intradialytic cycling training program in patients with end-stage kidney disease
Bibliographic record
Abstract
In chronic kidney disease (CKD), oxidative stress (OS) plays a central role in the development of cardiovascular diseases. This pilot program aimed to determine whether an intradialytic aerobic cycling training protocol, by increasing physical fitness, could reduce OS and improve other CKD-related disorders such as altered body composition and lipid profile. Eighteen hemodialysis patients were randomly assigned to either an intradialytic training (cycling: 30 min, 55%-60% peak power, 3 days/week) group (EX; n = 8) or a control group (CON; n = 10) for 3 months. Body composition (from dual-energy X-ray absorptiometry), physical fitness (peak oxygen uptake and the 6-minute walk test (6MWT)), lipid profile (triglycerides (TG), total cholesterol, high-density lipoprotein, and low-density lipoprotein (LDL)), and pro/antioxidant status (15-F2α-isoprostanes (F2-IsoP) and oxidized LDL in plasma; superoxide dismutase, glutathione peroxidase, and reduced/oxidized glutathione in erythrocytes) were determined at baseline and 3 months later. The intradialytic training protocol did not modify body composition but had significant effects on physical fitness, lipid profile, and pro/antioxidant status. Indeed, at 3 months: (i) performance on the 6MWT was increased in EX (+23.4%, p < 0.001) but did not change in CON, (ii) plasma TG were reduced in EX (-23%, p < 0.03) but were not modified in CON, and (iii) plasma F2-IsoP concentrations were lower in EX than in CON (-35.7%, p = 0.02). In conclusion, our results show that 30 min of intradialytic training, 3 times per week for 3 months, are enough to exert beneficial effects on the most sensitive and reliable marker of lipid peroxidation (IsoP) while improving CKD-associated disorders (lipid profile and physical fitness). Intradialytic aerobic cycling training represents a useful and easy strategy to reduce CKD-associated disorders. These results need to be confirmed with a larger randomized study.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".