Outcomes for clinical trials involving adults with chronic kidney disease: a multinational Delphi survey involving patients, caregivers and health professionals
Bibliographic record
Abstract
BACKGROUND: Many outcomes of high priority to patients and clinicians are infrequently and inconsistently reported across trials in chronic kidney disease (CKD), which generates research waste and limits evidence-informed decision making. We aimed to generate consensus among patients/caregivers and health professionals on critically important outcomes for trials in CKD prior to kidney failure and the need for kidney replacement therapy, and to describe the reasons for their choices. METHODS: This was an online two-round international Delphi survey. Adult patients with CKD (all stages and diagnoses), caregivers and health professionals who could read English, Spanish or French were eligible. Participants rated the importance of outcomes using a Likert scale (7-9 indicating critical importance) and a Best-Worst Scale. The scores for the two groups were assessed to determine absolute and relative importance. Comments were analysed thematically. RESULTS: In total, 1399 participants from 73 countries completed Round 1 of the Delphi survey, including 628 (45%) patients/caregivers and 771 (55%) health professionals. In Round 2, 790 participants (56% response rate) from 63 countries completed the survey including 383 (48%) patients/caregivers and 407 (52%) health professionals. The overall top five outcomes were: kidney function, need for dialysis/transplant, life participation, cardiovascular disease and death. In the final round, patients/caregivers indicated higher scores for most outcomes (17/22 outcomes), and health professionals gave higher priority to mortality, hospitalization and cardiovascular disease (mean difference >0.3). Consensus was based upon the two groups yielding median scores of ≥7 and mean scores >7, and the proportions of both groups rating the outcome as 'critically important' being >50%. Four themes reflected the reasons for their priorities: imminent threat of a health catastrophe, signifying diminishing capacities, ability to self-manage and cope, and tangible and direct consequences. CONCLUSION: Across trials in CKD, the outcomes of highest priority to patients, caregivers and health professionals were kidney function, need for dialysis/transplant, life participation, cardiovascular disease and death.
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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 | 0.094 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| 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".