Extracorporeal pediatric renal replacement therapy: diversifying application beyond kidney failure
Bibliographic record
Abstract
The utilization of extracorporeal renal replacement therapy (RRT), including continuous renal replacement therapy (CRRT) and hemodialysis (HD), beyond the treatment of volume overload and acute kidney injury (AKI) has witnessed a significant shift, demonstrating the potential to improve patient outcomes for a range of diseases. This comprehensive review explores the non-kidney applications for RRT platforms in critically ill children, focusing on diverse clinical scenarios such as sepsis, inborn errors of metabolism, liver failure, drug overdose, tumor lysis syndrome, and rhabdomyolysis. In the context of sepsis and septic shock, RRT not only facilitates fluid, electrolyte, and acid/base homeostasis, but may offer benefits in cytokine regulation, endotoxin clearance, and immunomodulation which may improve multi-organ dysfunction as well as hemodynamic challenges posed by this life-threatening condition. RRT modalities also have an important role in caring for children with inborn errors of metabolism, liver failure, and tumor lysis syndrome as they can control metabolic derangements with the efficient clearance of endogenous toxins in affected children. In cases of drug overdose, RRT is a crucial tool for rapid extracorporeal clearance of exogenous toxins, mitigating potential organ damage. The intricate interplay between liver failure and kidney function is examined, elucidating the role of RRT and plasma exchange in maintaining fluid and electrolyte balance when hepatic dysfunction complicates the clinical picture. Furthermore, RRT and HD are explored in the context of rhabdomyolysis, highlighting their utility in addressing AKI secondary to traumatic events and crush syndrome.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".