An International Delphi Survey on Exercise Priorities in CKD
Bibliographic record
Abstract
INTRODUCTION: Defining the role of exercise in chronic kidney disease (CKD) is a top research priority for people with CKD. We aimed to achieve consensus on specific research priorities in exercise and CKD among an international panel of stakeholders. METHODS: Using the Delphi method, patients/caregivers, researchers, clinicians, and policymakers submitted their top research priorities in round 1 and ranked their importance in rounds 2 and 3 using a 9-point Likert scale. The mean, median, and proportion of scores ranked 7 to 9 were calculated. Consensus was defined as priorities that scored above the overall mean and median score within each stakeholder panel. Qualitative description was used to understand participants' rankings. RESULTS: Seventy participants (78% response) completed round 1: 15 (21.4%) clinicians, 33 (47.1%) researchers, 13 (18.6%) policymakers, and 9 (12.9%) patients; (85.7%) completed round 3. The top research priorities were defining exercise-related outcomes meaningful to patients, identifying patients' motivation and perspective towards exercise, understanding the effect of exercise on the risk of institutionalization, mortality, and mobility, and understanding the effect of pre- and post-transplant exercise on postoperative recovery. Themes from the qualitative analysis were individualization, personal experience, and holistic approach to exercise (patients), the need to address common clinical problems (clinicians), developing targeted interventions (researchers), and the importance of evidence-based development versus implementation (policymakers). CONCLUSIONS: Preventing physical disability was a common priority. Policymakers emphasized that more efficacy studies were needed. Other panels expressed the need for holistic and targeted exercise interventions and for outcomes that address common clinical problems.
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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 | 0.059 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| 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; 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".