DAMPAned Methotrexate: A Case Report and Review of the Management of Acute Methotrexate Toxicity
Bibliographic record
Abstract
RATIONALE: Consensus guidelines on the management of methotrexate-induced nephrotoxicity using glucarpidase (Voraxaze) may be relatively unfamiliar to the nephrology community. PRESENTING CONCERNS OF THE PATIENT: A 61-year-old man with intravascular large B-cell lymphoma was admitted for cycle #1 of high-dose methotrexate (HDMTX) following 2 cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) chemotherapy. On admission, he was clinically euvolemic and had a creatinine clearance of 98 mL/min. He received standard HDMTX toxicity prophylaxis with volume expansion, urinary alkalinization, and leucovorin rescue. DIAGNOSES: Despite prophylactic efforts, he developed a severe acute kidney injury, creatinine 63 to 226 µmol/L (2.56 mg/dL), following HDMTX, impaired methotrexate clearance, and neurotoxicity manifested by status epilepticus. INTERVENTIONS: -methylpteroic acid) at 52 hours post-HDMTX. Cross-reactivity between commercial methotrexate immunoassays with DAMPA led to falsely elevated methotrexate concentrations for much longer than expected based on the current guideline (5 days instead of <48 hours). This required ongoing monitoring of methotrexate concentration by mass spectrometry. OUTCOMES: The patient remained nonoliguric and did not develop acute indications for dialysis. Serum creatinine peaked at 608 µmol/L (6.88 mg/dL) 6 days after HDMTX. He ultimately had a full renal and neurologic recovery. LESSONS LEARNED: Glucarpidase is an effective option for nonrenal elimination of methotrexate-induced nephrotoxicity. Timing of methotrexate concentration monitoring to assess for toxicity, how to access the drug, and the need for ongoing monitoring by mass spectrometry beyond the guideline recommendation are highlighted for centers where HDMTX therapy may be used.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".