The Ottawa Statement implementation guidance document for cluster randomized trials in the hemodialysis setting
Bibliographic record
Abstract
Research teams are increasingly interested in using cluster randomized trial (CRT) designs to generate practice-guiding evidence for in-center maintenance hemodialysis. However, CRTs raise complex ethical issues. The Ottawa Statement on the Ethical Design and Conduct of Cluster Randomized Trials, published in 2012, provides 15 recommendations to address ethical issues arising within 7 domains: justifying the CRT design, research ethics committee review, identifying research participants, obtaining informed consent, gatekeepers, assessing benefits and harms, and protecting vulnerable participants. But applying the Ottawa Statement recommendations to CRTs in the hemodialysis setting is complicated by the unique features of the setting and population. Here, with the help of content experts and patient partners, we co-developed this implementation guidance document to provide research teams, research ethics committees, and other stakeholders with detailed guidance on how to apply the Ottawa Statement recommendations to CRTs in the hemodialysis setting, the result of a 4-year research project. Thus, our work demonstrates how the voices of patients, caregivers, and all stakeholders may be included in the development of research ethics guidance.
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 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 | 0.522 | 0.709 |
| Meta-epidemiology (narrow) | 0.005 | 0.014 |
| Meta-epidemiology (broad) | 0.008 | 0.019 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.021 | 0.013 |
| Open science | 0.014 | 0.013 |
| Research integrity | 0.067 | 0.057 |
| Insufficient payload (model declined to judge) | 0.036 | 0.041 |
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".