Successful Treatment of Rhabdomyolysis‐Associated Acute Kidney Injury with Haemoadsorption and Continuous Renal Replacement Therapy
Bibliographic record
Abstract
We report two children with rhabdomyolysis-associated acute kidney injury who were successfully treated with a haemoadsorption column CytoSorb® in addition to continuous renal replacement therapy (CRRT). A 14-year-old girl with multiorgan failure requiring extracorporeal membrane oxygenation developed rhabdomyolysis due to reperfusion injury. Her creatine kinase (CK) and lactate levels continued to escalate despite high-dose CRRT. A haemoadsorption column was therefore added post-CRRT filter, which brought down the CK level from 264,500 IU/L to 97,436 IU/L after 8 hours of therapy. Another 4-year-old boy with epilepsy and cerebral palsy who was admitted for gastroenteritis with dehydration developed acute kidney injury and rhabdomyolysis with a peak CK level of 946,060 IU/L. He was initially treated with CRRT for 40 hours, which reduced his CK level to 147,580 IU/L. Two sessions of haemoadsorption were then performed in addition to the CRRT, which further lowered his CK level to 32,306 IU/L in 48 hours. Both patients demonstrated enhanced reduction of CK levels when the haemoadsorption column was used in addition to the CRRT, and no specific complication related to the haemoadsorption therapy was reported. Our cases showed that haemoadsorption can be considered as an adjunctive therapy for children with severe rhabdomyolysis-associated acute kidney injury.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".