Continuous Renal Replacement Therapy (CRRT) for Nonrenal Indications among Critically Ill Children with Malignancy
Bibliographic record
Abstract
The role of continuous renal replacement therapy (CRRT) has been expanding beyond support for acute kidney injury (AKI) in recent years. Children with malignancy are particularly at risk of developing conditions that may require CRRT. We reported three children with malignancy who received CRRT for non‐AKI indications. Patient 1 was a 17‐year‐old teenage girl who developed refractory type B lactic acidosis due to relapse of acute lymphoblastic leukemia (ALL). Her peak lactate level was 18 mmol/L, and the lowest pH and bicarbonate level was 7.13 and 6.0 mmol/L, respectively. She received three sessions of high‐volume hemodiafiltration to bring down the lactate level. Patient 2 was a 15‐year‐old male with T‐cell ALL who developed cytokine storm requiring mechanical ventilatory and high‐dose inotropic support due to necrotizing enterocolitis complicated by pneumoperitoneum and Klebsiella pneumoniae septicemia. He received two sessions of hemoperfusion using a specific filter capable of endotoxin absorption and cytokine removal and was successfully weaned off all inotropes after the treatment. Patient 3 was an 8‐year‐old boy who received bone marrow transplantation and developed worsening hyperbilirubinemia and deteriorating liver function. He received a session of single‐pass albumin dialysis for bilirubin removal prior to liver biopsy. Except for mild electrolyte disturbances, no major CRRT complication was encountered. Our report demonstrated that CRRT is an effective and safe procedure for a wide spectrum of nonrenal conditions among children with oncological diagnoses in the pediatric intensive care unit. However, the optimal dose, regime, timing of initiation, and monitoring target for these indications remain to be determined.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".