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Record W2149248543 · doi:10.1592/phco.27.1.111

Clarifying the Role of Rasburicase in Tumor Lysis Syndrome

2006· review· en· W2149248543 on OpenAlexaff
Amy R. Sood, Lisa Burry, Doret K. F. Cheng

Bibliographic record

VenuePharmacotherapy The Journal of Human Pharmacology and Drug Therapy · 2006
Typereview
Languageen
FieldMedicine
TopicMethemoglobinemia and Tumor Lysis Syndrome
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsRasburicaseTumor lysis syndromeHyperuricemiaMedicineHyperphosphatemiaHyperkalemiaAllopurinolInternal medicineChemotherapyIntensive care medicineOncologySurgeryUrologyUric acidKidney disease

Abstract

fetched live from OpenAlex

Tumor lysis syndrome (TLS) is a complication of malignancies with high tumor cell proliferation, tumor burden, and chemosensitivity. It manifests with the release of intracellular components and results in hyperkalemia, hyperphosphatemia, hypocalcemia, and hyperuricemia. These biochemical abnormalities may lead to serious complications such as renal failure, cardiac dysrhythmias, and death. Rasburicase, a recombinant urate oxidase enzyme, is a new agent indicated in the treatment or prophylaxis of hyperuricemia in pediatric patients with cancer who are at high risk for TLS. We reviewed the evidence for treatment with this agent compared with standard therapy with allopurinol. Rasburicase may be considered for use in patients with hyperuricemia at presentation and in patients at high risk for TLS that would otherwise result in a delay in chemotherapy. However, randomized controlled trials are required to establish the comparative efficacy of rasburicase in the adult population. Preliminary evidence suggests that single-dose or reduced-dose rasburicase may be effective in the prophylaxis and the treatment of hyperuricemia and TLS. However, to our knowledge, there is no evidence comparing clinically relevant outcomes such as acute renal failure or dialysis.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.034
GPT teacher head0.375
Teacher spread0.341 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations27
Published2006
Admission routes1
Has abstractyes

Explore more

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