Implementing core outcomes in kidney disease: report of the Standardized Outcomes in Nephrology (SONG) implementation workshop
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There are an estimated 14,000 randomized trials published in chronic kidney disease. The most frequently reported outcomes are biochemical endpoints, rather than clinical and patient-reported outcomes including cardiovascular disease, mortality, and quality of life. While many trials have focused on optimizing kidney health, the heterogeneity and uncertain relevance of outcomes reported across trials may limit their policy and practice impact. The international Standardized Outcomes in Nephrology (SONG) Initiative was formed to identify core outcomes that are critically important to patients and health professionals, to be reported consistently across trials. We convened a SONG Implementation Workshop to discuss the implementation of core outcomes. Eighty-two patients/caregivers and health professionals participated in plenary and breakout discussions. In this report, we summarize the findings of the workshop in two main themes: socializing the concept of core outcomes, and demonstrating feasibility and usability. We outline implementation strategies and pathways to be established through partnership with stakeholders, which may bolster acceptance and reporting of core outcomes in trials, and encourage their use by end-users such as guideline producers and policymakers to help improve patient-important outcomes.
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.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it