Identifying patient‐important outcomes in polycystic kidney disease: An international nominal group technique study
Bibliographic record
Abstract
AIM: Patients with autosomal dominant polycystic kidney disease (ADPKD) are at increased risk of premature mortality, morbidities and complications, which severely impair quality of life. However, patient-centered outcomes are not consistently reported in trials in ADPKD, which can limit shared decision-making. We aimed to identify outcomes important to patients and caregivers and the reasons for their priorities. METHODS: Nominal group technique was adopted involving patients with ADPKD and caregivers who were purposively selected from eight centres across Australia, France and the Republic of Korea. Participants identified, ranked and discussed outcomes for trials in ADPKD. We calculated an importance score (0-1) for each outcome and conducted thematic analyses. RESULTS: Across 17 groups, 154 participants (121 patients, 33 caregivers) aged 19 to 78 (mean 54.5 years) identified 55 outcomes. The 10 highest ranked outcomes were: kidney function (importance score 0.36), end-stage kidney disease (0.32), survival (0.21), cyst size/growth (0.20), cyst pain/bleeding (0.18), blood pressure (0.17), ability to work (0.16), cerebral aneurysm/stroke (0.14), mobility/physical function (0.12), and fatigue (0.12). Three themes were identified: threatening semblance of normality, inability to control and making sense of diverse risks. CONCLUSION: For patients with ADPKD and their caregivers, kidney function, delayed progression to end-stage kidney disease and survival were the highest priorities, and were focused on achieving normality, and maintaining control over health and lifestyle. Implementing these patient-important outcomes may improve the meaning and relevance of trials to inform clinical care in ADPKD.
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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 | 0.063 | 0.127 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".