Identifying Research Priorities for Cognition in CKD
Bibliographic record
Abstract
Key Points Cognitive impairment is prevalent in CKD, affecting quality of life, self-management, and decision-making. It worsens with disease progression. This Delphi study engaged diverse stakeholders to identify 27 critical research questions on cognitive impairment in CKD for future focus. Top priorities include preventing cognitive decline, preserving cognition, routine monitoring, and adjusting dialysis treatment to reduce cognitive impairment. Background Cognition is a research priority for people living with CKD, but identification of critical research questions is lacking. This study aimed to determine which cognition-related research questions are most important to CKD stakeholders. Methods A modified Delphi technique with three survey rounds was used. The study sample included three panels ( People with lived CKD experience, Researchers, and Clinicians ) recruited through international patient and kidney research networks, kidney societies, and snowball sampling with email invitations. Survey rounds were distributed electronically through Research Electronic Data Capture. In round 1 (October 2021–May 2022), respondents contributed three important research questions regarding cognition in CKD (free text). After deduplication and qualitative synthesis, respondents ranked the importance of these questions on a nine-point Likert scale in round 2 (February–April 2023). Questions with mean and median ratings of >7 by at least two respondent panels or rated critically important by the lived experience panel were reranked in round 3 (August–September 2023) and assessed for consensus to identify the final list of priority research questions. Results Respondents ( n =152) identified 125 and 44 discrete questions after rounds 1 and 2, respectively. The final shortlist included 27 questions in eight categories. The most critical research question identified was “What factors prevent cognitive impairment in people receiving dialysis?” Overall, respondents prioritized questions focusing on prevention and treatment of cognitive impairment. Scores between the panels were significantly different for 16 questions. Those with lived CKD experience prioritized quality of life, researchers emphasized developing interventions to mitigate cognitive impairment, and clinicians prioritized the effect of CKD treatment on cognitive impairment. Conclusions Through an established consensus methodology involving key stakeholder groups, we identified 27 critical research questions about cognition in CKD. These questions should guide future study design and outcome selection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".