Scope and heterogeneity of outcomes reported in randomized trials in patients receiving peritoneal dialysis
Bibliographic record
Abstract
BACKGROUND: Randomized trials can provide evidence to inform decision-making but this may be limited if the outcomes of importance to patients and clinicians are omitted or reported inconsistently. We aimed to assess the scope and heterogeneity of outcomes reported in trials in peritoneal dialysis (PD). METHODS: We searched the Cochrane Kidney and Transplant Specialized Register for randomized trials in PD. We extracted all reported outcome domains and measurements and analyzed their frequency and characteristics. RESULTS: From 128 reports of 120 included trials, 80 different outcome domains were reported. Overall, 39 (49%) domains were surrogate, 23 (29%) patient-reported and 18 (22%) clinical. The five most commonly reported domains were PD-related infection [59 (49%) trials], dialysis solute clearance [51 (42%)], kidney function [45 (38%)], protein metabolism [44 (37%)] and inflammatory markers/oxidative stress [42 (35%)]. Quality of life was reported infrequently (4% of trials). Only 14 (12%) trials included a patient-reported outcome as a primary outcome. The median number of outcome measures (defined as a different measurement, aggregation and metric) was 22 (interquartile range 13-37) per trial. PD-related infection was the most frequently reported clinical outcome as well as the most frequently stated primary outcome. A total of 383 different measures for infection were used, with 66 used more than once. CONCLUSIONS: Trials in PD include important clinical outcomes such as infection, but these are measured and reported inconsistently. Patient-reported outcomes are infrequently reported and nearly half of the domains were surrogate. Standardized outcomes for PD trials are required to improve efficiency and relevance.
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 | 0.495 | 0.799 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.022 | 0.023 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| 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; 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".