Consensus-Based Recommendations on Priority Activities to Address Acute Kidney Injury in Children
Bibliographic record
Abstract
Importance: Increasing evidence indicates that acute kidney injury (AKI) occurs frequently in children and young adults and is associated with poor short-term and long-term outcomes. Guidance is required to focus efforts related to expansion of pediatric AKI knowledge. Objective: To develop expert-driven pediatric specific recommendations on needed AKI research, education, practice, and advocacy. Evidence Review: At the 26th Acute Disease Quality Initiative meeting conducted in November 2021 by 47 multiprofessional international experts in general pediatrics, nephrology, and critical care, the panel focused on 6 areas: (1) epidemiology; (2) diagnostics; (3) fluid overload; (4) kidney support therapies; (5) biology, pharmacology, and nutrition; and (6) education and advocacy. An objective scientific review and distillation of literature through September 2021 was performed of (1) epidemiology, (2) risk assessment and diagnosis, (3) fluid assessment, (4) kidney support and extracorporeal therapies, (5) pathobiology, nutrition, and pharmacology, and (6) education and advocacy. Using an established modified Delphi process based on existing data, workgroups derived consensus statements with recommendations. Findings: The meeting developed 12 consensus statements and 29 research recommendations. Principal suggestions were to address gaps of knowledge by including data from varying socioeconomic groups, broadening definition of AKI phenotypes, adjudicating fluid balance by disease severity, integrating biopathology of child growth and development, and partnering with families and communities in AKI advocacy. Conclusions and Relevance: Existing evidence across observational study supports further efforts to increase knowledge related to AKI in childhood. Significant gaps of knowledge may be addressed by focused efforts.
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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 | 0.110 | 0.245 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.011 | 0.012 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".