Physical functioning in end‐stage renal disease patients: Update 2005
Bibliographic record
Abstract
Physical functioning in patients with end-stage renal disease treated with dialysis is low, whether measured using objective laboratory measures, physical performance testing, or self-reported measures. Peak oxygen uptake (VO2peak), self-reported functioning measures, and physical activity levels are independent predictors of mortality in these patients. Cardiovascular exercise training studies result in improvements in VO2peak, physical performance tests, and self-reported functioning. Resistance exercise training improves muscle strength. Exercise training may have positive benefits on other factors that are important clinical issues in dialysis patients, including cardiovascular risk profile, oxidative stress, and inflammation. Endothelial function, a surrogate marker of atherosclerosis, has been shown to improve with exercise training in dialysis patients. Although there have been numerous recent studies on benefits of exercise, few dialysis clinics or nephrologists provide encouragement or programs as a part of their routine care of their patients. There are many national guidelines that include exercise or increasing physical activity as a part of the treatment of many conditions that are relevant in dialysis patients, including hypertension, hyperlipidemia, and high cardiovascular disease risk. The nephrology community continues to state concern for outcomes; however, a simple, low-tech intervention that has many benefits to their patients (i.e., encouragement, recommendations, and opportunity for increasing physical activity) has not been adopted as part of the standard care. Adoption of routine counseling and encouragement for physical activity has the potential to improve outcomes, improve physical functioning, and optimize quality of life and overall health of dialysis patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".