Programs and processes for advancing pediatric acute kidney support therapy in hospitalized and critically ill children: a report from the 26th Acute Disease Quality Initiative (ADQI) consensus conference
Bibliographic record
Abstract
Pediatric acute kidney support therapy (paKST) programs aim to reliably provide safe, effective, and timely extracorporeal supportive care for acutely and critically ill pediatric patients with acute kidney injury (AKI), fluid and electrolyte derangements, and/or toxin accumulation with a goal of improving both hospital-based and lifelong outcomes. Little is known about optimal ways to configure paKST teams and programs, pediatric-specific aspects of delivering high-quality paKST, strategies for transitioning from acute continuous modes of paKST to facilitate rehabilitation, or providing effective short- and long-term follow-up. As part of the 26th Acute Disease Quality Initiative Conference, the first to focus on a pediatric population, we summarize here the current state of knowledge in paKST programs and technology, identify key knowledge gaps in the field, and propose a framework for current best practices and future research in paKST.
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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 | 0.076 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".