Clinicians’ and researchers’ perspectives on establishing and implementing core outcomes in haemodialysis: semistructured interview study
Bibliographic record
Abstract
Objectives To describe the perspectives of clinicians and researchers on identifying, establishing and implementing core outcomes in haemodialysis and their expected impact. Design Face-to-face, semistructured interviews; thematic analysis. Stetting Twenty-seven centres across nine countries. Participants Fifty-eight nephrologists (42 (72%) who were also triallists). Results We identified six themes: reflecting direct patient relevance and impact (survival as the primary goal of dialysis, enabling well-being and functioning, severe consequences of comorbidities and complications, indicators of treatment success, universal relevance, stakeholder consensus); amenable and responsive to interventions (realistic and possible to intervene on, differentiating between treatments); reflective of economic burden on healthcare; feasibility of implementation (clarity and consistency in definition, easily measurable, requiring minimal resources, creating a cultural shift, aversion to intensifying bureaucracy, allowing justifiable exceptions); authoritative inducement and directive (endorsement for legitimacy, necessity of buy-in from dialysis providers, incentivising uptake); instituting patient-centredness (explicitly addressing patient-important outcomes, reciprocating trial participation, improving comparability of interventions for decision-making, driving quality improvement and compelling a focus on quality of life). Conclusions Nephrologists emphasised that core outcomes should be relevant to patients, amenable to change, feasible to implement and supported by stakeholder organisations. They expected core outcomes would improve patient-centred care and outcomes.
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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 | 0.103 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| 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; 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".