Making the Case for Standardized Outcome Measures in Exercise and Physical Activity Research in Chronic Kidney Disease
Bibliographic record
Abstract
Physical activity and exercise are core components of lifestyle modification strategies for the management of chronic kidney disease (CKD). Yet, physical activity levels have consistently remained poor across all stages of CKD. Exercise interventions, including aerobic and resistance training, and lifestyle interventions promoting physical activity, have been shown to improve a multitude of clinical endpoints and factors important to patients; however, despite the evidence, the provision of physical activity in clinical practice is still inadequate. The usefulness of any study hinges on the adequacy and clinical relevance of the outcomes and outcome measures used. Inconsistent reporting and wide disparities in outcome use across studies limit evidence synthesis to help guide clinical practice. The kidney exercise and physical activity field has been particularly prone to inconsistent outcome reporting. To ensure research is relevant and able to influence clinical practice and future research, we need to ensure the use (and reporting) of standardized, relevant outcome measures. Core outcome sets (COS) have been widely developed across many chronic conditions, yet these COS have not been tailored to physical activity and exercise in CKD. Outcomes in clinical research need to be relevant to the intervention being employed. From this perspective, we summarize the importance that standardizing outcomes and outcome measures may have in relation to physical activity and exercise interventions for people living with kidney disease.
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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 | 0.831 | 0.864 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.012 | 0.017 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.010 | 0.015 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.002 | 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; the direct Gemma label and the distilled Codex classifier 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".