Acute hemolysis and renal failure associated with charcoal hemoperfusion for valproic acid intoxication
Bibliographic record
Abstract
Charcoal hemoperfusion is an effective treatment in acute drug intoxication with small volume of distribution. For certain drugs, clearance rates are higher with hemoperfusion than hemodialysis. We describe a patient with severe valproic acid overdose who developed severe hemolysis and acute renal failure related to charcoal hemoperfusion treatment. A 50‐year‐old female was admitted to the hospital following valproic acid overdose. Initial valproic acid level was 73.6 mg/L, and she was treated with oral activated charcoal. Four hours later she developed mental status changes with valproic acid level at 490.9 mg/L and prolonged QT interval. Charcoal hemoperfusion was started with blood flow rate 400 ml/min. Patient developed bleeding with evidence of severe Before( * C.H.) After (C.H.) Hemoglobin 12.1 gm/DL 7.6 gm/DL Hematocrit 35.5 gm/DL 21.1 gm/DL Platelet count 268,000 tho/ul 43,000 tho/ul L.D.H 90 IU/L 2494 IU/L Valproic Acid 490.9 mg/L 74.1 mg/L C.H. (Charcoal Hemoperfusion) Blood – evidence of massive hemolysis intra‐vascular hemolysis, shown in table (no evidence of HUS/TTP). She received transfusion of packed red blood cells, platelets, and fibrin. Over the next few days she developed oligouric acute renal failure requiring hemodialysis for 2 weeks. Eventually hemolysis resolved and the renal function improved (kidney biopsy was consistent with acute tubular necrosis). To our knowledge, this is the first reported case of severe intravascular hemolysis occurring during the charcoal hemoperfusion treatment. Etiology includes mechanical trauma to the red cells, probably related to high blood flow rate through the charcoal column.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".